mesinfos.fing.org

“WHAT IF CITIES TOOK A CENTRAL ROLE IN RETURNING CITIZENS’ PERSONAL DATA TO THEM?”

2020 THE “MESINFOS - SELF DATA ACKNOWLEDGEMENTS: CITIES” TEAM AT FING: Special thanks to Virginie Steiner (La Rochelle), Manon Molins, Chloé Friedlander, Guillaume Jacquart, Sylvie Turck (Nantes Métropole), and Maria-Inés Léal Fanny Maurel // Sarah Medjek for MyData France. (Grand Lyon), as well as to Guillaume Chanson, Cécile What if cities took a central role in returning > an analysis of the relevant governance models Christodoulou, Aurialie Jublin, and Mathilde Simon. citizens’ personal data to them, so their citizens can when considering how to share personal data with individuals; TRANSLATION: Jianne Whelton use personal data to make their lives easier, get to know each other better, contribute to territorial > a survey of cities efforts to share data, including decision making or participate in public interest some examples to draw inspiration from (and some CREATIVE COMMONS projects? to avoid); > illustrated methodologies you can use to This document is available under a Creative Commons Attribution 4.0 License (France): For the past year, Fing has been working with three https://creativecommons.org/licenses/by/4.0/deed.fr. implement a Self Data initiative in your region major French cities — Nantes Métropole, (the energy (plus examples drawn from our work with Nantes You are free to share — copy and redistribute the material in any medium or format — and adapt — remix, transform, and build upon the material for transition), La Rochelle (sustainable mobility), and Métropole, La Rochelle and Greater Lyon): identify any purpose, even commercially — under the following terms: attribution — you must give appropriate credit, provide a link to the license, and indicate Greater Lyon (social welfare) — to enable them to the relevant personal data, imagine use cases if changes were made. You may do so in any reasonable manner, but not in any way that suggests that Fing endorses you or your use. You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits. implement a Self Data experiment of their own as that utilize these data, look towards governance early as 2020. This playbook is the fruit of our work models to frame your use cases, and select your together. Its central objective is to put Fing methods experimental scenario(s); FING IS SUPPORTED BY into the hands of other metropolitan areas looking PARTENAIRES > some advice born of our experience working with to dive into Self Data, so they can do so feeling Self Data since 2011, which we would have loved to suitably equipped. In this kit you will find: have ourselves when we first started experimenting with Self Data at Fing. > an introduction to the notion of Self Data — sharing personal data with the individuals they Happy experimenting with Self Data in your region! pertain to — and the major issues that Self Data PARTENAIRES ASSOCIÉS implies for cities; Mathieu Drouet

La Fing a le soutien de ses grands partenaires GRAPHICS AND LAYOUT: “MESINFOS: SELF DATA CITIES” — WHAT IF CITIES TOOK A CENTRAL ROLE IN RETURNING CITIZENS’ PERSONAL DATA TO THEM? 01

P - 02 >> Self Data: the concept P - 07 >> Can Self Data be a lever for metropolitan innovation? P - 09 >> Sharing personal data: governance models

“CITIES AND PERSONAL DATA” — OVERVIEW OF GLOBAL INITIATIVES 19 P - 20 >> Cities and personal data, what ways ahead for citizens? P - 26 >> A closer look at cities’ personal data initiatives

“SELF DATA DIY” — CREATE A LOCALIZED, RELEVANT SELF DATA INITIATIVE FOR YOUR REGION: THE EXAMPLES OF THE CITY OF NANTES, LA ROCHELLE, AND GREATER LYON. 39

P - 40 >> Understanding the stakes associated with Self Data and choosing an appropriate project P - 42 >> Defining the data parameters P - 43 >> Potential use cases and relevant models of governance P - 66 >> In practice: outline an experimental scenario for your region

“SHALL WE BEGIN?” — PROTIPS FROM EXPERT SELF DATA ACTORS 71 P - 74 >> A Self Data experiment: 10 questions to ask P - 76 >> A Self Data experiment: 10 levers to activate P - 78 >> A Self Data experiment: 7 pitfalls to avoid P - 80 >> A Self Data experiment: 10 cardinal rules to respect

APPENDICES — READY-MADE METHODOLOGIES 82 P - 84 >> 1) The seminar P - 88 >> 2) The datablitz P - 92 >> 3) The use cases P - 96 >> 4) The governance models P - 100 >> 5) The experimental scenarios “MESINFOS: SELF DATA CITIES” — WHAT IF CITIES TOOK A CENTRAL ROLE IN RETURNING CITIZENS’ PERSONAL DATA TO 01 THEM? “MesInfos: Self Data Cities” — What if cities took a central role in

returning citizens’ personal data to them? 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Self Data make holding organization to data their and manage store Personally 2) #PIMS #PDS #PODs securely. it possible make Self Data imperative: The second and manage their perso- store individuals to for them a offering be by This may nal data securely. personal space personal digital home: an online,

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returning citizens’ personal data to them? P stored on different on different stored recorded devices, ap- across several and so- plications, metimes misplaced The aca- at Google". on is working demy that an experiment particiwill provide - pants with personal Cloud) clouds (Cozy their of and a copy personal education More on this data. its members with a perso- provides In line with the MesInfos pilot, insurer Maif pilot, In line with the MesInfos now of where it shares the details nal cloud, policies with them. their home insurance Health "My Fing’s of context the in Likewise, health care and disease prevention Data" Self Group is concepting Vyv the efforts, personal health data that use Data services Fair&Smart by and a solution implemented meaning — that enables data reversibility consent their withdraw can individuals that immedia- erased is data their all have and an individual’s the services, of In terms tely. can be used example, for results, blood test be file, prevention disease their augment to with air cross-referencing enriched after experiment in the next chapter. chapter. next in the experiment » » - - - Other good news on the Self Data front: Other good news conduct those we beyond — experiments In Brit are emerging everywhere. — at Fing is conduc de Rennes Académie the tany, helping national education ting a project mastery gain to teachers and students their data throughout their learning over Oli- to According trajectories. and career personal data is scat lot of "a Adam, vier in the digital education ecosystem, tered trate the value of reusing what is shared shared is what reusing of value the trate In companies. linking up with innovative by a white has published a collective France, pre- have which they paper on portability, and seeks Assembly, the National to sented consortium on the a cross-sector create to governance). of form (a new subject » » - - , the Open Bank now seeks to demons- to seeks now Bank Open the , a way to create value that establishes a vir- a that establishes value create to a way tuous cycle. in data also are the advances Noteworthy across entire sec taking place portability long have institutions health France’s tors, à la fran- "Blue Button a calling for been of the sharing facilitate would that çaise" in- organizations and health data between course, of would, which dividual patients, - Re Shared Medical France’s to be linked With the Digital Health (DMP) system. cord the by existence into voted (ENS), Space individuals in 2019, Assembly National from platform a have potentially might share to their consent manage which to re- their treatment and prescription data, and other manual- and reuse these cords, services trusted data thanks to entered ly has sector telecom The third-parties. and ef- to related initiatives launched several in conjunc procedures portability fective Cooperation tion with the Data Portability in England On the banking side, project. where — the firstworld’s initiativefor per- the MiData program, sonal data portability, lets Project the Open Bank — was born data with third par- banks share customers’ of benefit the for and control the under ties, The program is similar to those customers. a rocky After directive. "DSP2" the European start » » , Data Protection Data Protection , Energy providers Enedis and GRDF have have GRDF and Enedis providers Energy (Enedis Data and projects set up processes with individuals allow Adict) to GRDF Connect, recover to Gazpar) (Linky, meter a connected better identify to — them their data and reuse their consumption, manage better contracts, - compa These services. via third-party — etc. vanguard among data the form nies presently rather unique: be- Their position is holders. them required regulations code cause energy the data sharing long before contemplate to and given effect, came into portability right to not service — distributors their role as energy share more inclined to were they — providers en- with individuals in ways that data directly emerge. to market service abled a third-party making are sectors and organizations Other for reality a concrete portability the right to French on- startedAn initiative by their users. line classified advertisingLeBonCoin is giant "data takeout its rarity: for worth mentioning, and download to you that allows is a feature - Accor personal data autonomously". your view Damien Dégremont ding to the when 25, May "Since LeBonCoin, at Officer been have we operational, became feature per- for thousand requests several receiving the handful we versus sonal data per week, is Curiosity it." before year per receiving were reuse ! Enabling individuals to . . spreading is services via third-party their personal data » » » » "Data takes 4th edition takes an officially-recognized Finnish non-profit hundred members. more than four comprising indivi- making wider goal of the Fueled by the personal data, their of masters duals the MyData movement became a fully-fledged non-profit organization based Its local hubs around the world. with twenty in Helsinki, whose — conference annual catalyst. acts as its principal — in 2019 place the of hands in the lies Data Self to key The proper chan- establish the They data holders. data transmission and facilitate data nels for docu- the correct observe reuse when they generate to and work mentation practices Self Data these, Without datasets. synthetic thanks alive kept but a concept, be would - data scraping tech permissible vaguely to are jockeying actors few very Today, niques. hitters heavy digital’s Some of position. for data transmis- the ones with longstanding — are — and Google Facebook sion channels like coalitions and forming launching initiatives portability to right the address to actors of position to or seeking ), Project (Data Transfer to ready as experts on the subject, themselves Facebook’s (see other sectors to advice give entitled report 2019, from September however, are, There ). Privacy" and Portability and invested, some data holders who are truly example. who are leading by » » search track in France — has been carrying the carrying been has — in France search track is project MesInfos and its 2011, since torch support the to thanks of year, in its sixth now exploring by began We partnersits allies. and at what others were Self Data and looking Buttons Green (the Blue and doing elsewhere the MiData in England, States, in the United the re- testing before etc.), community, VRM 300 participants personal data with turn of in a — 2013 worldwide We first. worked on the challenges re- and legal economic technical, the on specifically then and Data, Self to lated The issue and health data. energy sharing of then spun off we self-data health-related of into the "My Data, My Health" project. Natu- at closely spent time looking have we rally, worked have We data portability. the right to - wor our Dataccess with members of closely Pilot stu- and across an expansive king group, 2016 and 2018, between place that took dy 2000 testers over with collaborated we where the demonstrate and multiple data holders to Self Data. of scaling potential a into MyData has evolved Internationally, all collaborators, of community worldwide generated benefits the recalibrate to working more towards the personal data economy by network the 2018, of In October individuals. a small - group launched inte of in 2015 by — Fin- including Open Knowledge actors rested was reborn as MyData Global, — land and Fing » » “MesInfos: Self Data Cities” — What if cities took a central role in

returning citizens’ personal data to them? P avert the ongoing Therecrisis is of confidence. lay could These actors however. an alternative, with relationship a new for the foundations the same At and inhabitants. customers users, data for frameworks new building by time, could they control, sharing under individuals’ garner for and be partrevolution, the data of in the emerging a solid position themselves applications, (platforms, market data services indivi- can transform Self Data practices etc.). and enrich the traditional apprehensions duals’ creation, (service actors regional activities of etc.). production, knowledge planning, per- on based services where contexts urban In cities and citizens yet and sonal data are legion, a them, value from of way in the obtain little the turn well very might approach Data Self protect to it seeks because only not — tables but although that is crucial, privacy, people’s individual and it is sustained by because largely use. through data empowerment collective at Fing on ci- work of years more than 10 After pro- 2.0" "Cities from our 2008 — ties & digital Governing "Audacities: recent the more to gram, one thing — (in French) digital city" a real-world in- urban that is over and over seen have we cities at the helm to need initiatives novation open things big questions, ask guide processes, mul- models of new and imagine debate, to up "a is are seeing What we governance. ti-actor - tors do, individuals would be able to produce, produce, be able to individuals would do, tors personal and and retrieve collect capture, share choose to could They data. non-personal - contri or even themselves use them for them, production studies and knowledge them to bute perso- based on their In short, the region. for to the agency have individuals would nal data, — services new of participate in the emergence a part play — or collaboratively independently environments in planning their metropolitan - contri urban fabrics, cities’ of and the weaving collective advance decisions, political to bute creation… knowledge gain from retur- also stand to actors Regional are People Individuals. ning personal data to ill at ease about the increasingly becoming are pro- organizations and private ways public legislative while data, personal their cessing Mere and tighter. tighter are getting restrictions will not be enough to with the law compliance source of value creation not only at the indi- the at not only creation value of source and wider (public but also at the vidual level, be Self Data could level. metropolitan private) transition, energy region’s the of service the at questions, mobility to answers generate could private) and (public new for be the springboard This is what a data . . inhabitants. for services where data is shared like, might look commons all parties between concerned. equally ac metropolitan and regional Just as massive - So who will So who will take it? Who is capable of managing the scope managing the scope of Who is capable it? take one that project, this kind of of and complexity (sometimes competing) private brings together lay- researchers, entities, public organizations, We ecosystem? plus an entire innovation men, have become increasingly confident in our- fee the pilot that months of these last few ling over in the future of play to role a special cities have Self Data. are fa- authorities a time when regional At challenges on an unprecedented cing complex - deve social, economic, scale (environmental, is emerging revolution "smart" the lopmental), sys- more intelligent there are more and apace: tems and service that optimize flows, Is there perhaps . reduce . risk. mitigate consumption, and one that is less integrated another way, and re- inhabitants one that offers more open, What if explore? to some space gional actors the Self an entire metropolitan area adopted Data concept, and then managed the flow of and from ac and methods to tools information, fos pilot during all these years, we have proven proven have we years, these pilot during all fos Data ini- a Self implementing of capable are we to intended never we grand scale, on a tiative indefinitely. torch Data Self the carry - all contri that they in order small, big and tors as a matter work, making the project to bute pro- data are often Personal interest? public of them crossing context; metropolitan a in duced a powerful create with local Open Data would exchange best practices, sometimes compete and compete sometimes best practices, exchange cooperate. sometimes DATA SELF CAN FOR LEVER A BE METROPOLITAN INNOVATION? has years the last 7 over on MesInfos Our work in an incredibly actor central a made France development, culture digital of wave powerful and one of the pioneers in the fieldof personal in the preceding All the good news data sharing. maybe causes us (or us happy paragraphs makes make we can how but in practical terms, worry), to Between widespread? more the concept of uptake project carried out a major pilot we 2016-2018, data-holding organizations, together that brought one of and government the citizens a platform, - ecosys and an entire innovation in France region of the hidden potential explore concretely to tem The data holder partner organizations Self Data. regain to 2000 individuals than more enabled holding, were data they the personal of control however . . reuse it. so that the individuals could pleased. they the MesIn- in our role coordinating though, Even

"Industry "Industry is seeking . And in England, the And in England, program. open innovation studio, and lauded the studio, open innovation Supporting the emergence of data mar- data Supporting of the emergence digm shift" that "enable individuals to regain regain to individuals "enable that digm shift" explicitly and has their data", over control Tenders support. European Union called for for H2020 project proposals are appearing (eg: which most of — ) and the data economy kets the head of Finland, oriented. "Self Data" are European Union at the time of the of Council a create to "need has embedded the writing, where individuals data economy, competitive in- promoting access, seat, are in the driving data while res- use of and the teroperability individuals" of rights and privacy the pecting in its official in consumers Putting "Smart Data Review: enabling innovation" their data and of control led by Her Majesty’s Government in can play understand the role they better to - develop and services technology data-driven company Development State Finland’s ment. launched a Self Data-themed Vake Hack" national Post Office for its newly-designed of a series Launching steps? Its next PIMS. - will enable thou that studies pilot MyData their data. of control regain Finns to sands of What all these initiatives have in common is that in common have What all these initiatives — frameworks accountability tabling new are they are gone Long about them. thinking at least or services isolated of minor examples the days of each other, to talk All these actors and platforms. " is supporting the " looking at facilitating looking at facilitating startup garage MyData pilot study emergence of services at various points on at services of emergence so are many and — spectrum the data control the 2016, October In administrations! public Supervisor (EDPS) European Data Protection - "para represent a that PIM systems estimated Growth in the PIMS market is also very pro- very is also the PIMS market in Growth not launched, when MesInfos In 2011, mising. of dozens Today, operational. one was truly Di- position: for entrepreneurs are jockeying Onecub, Fair&Smart, Matchupbox, Cozy, gime, the of the granddaddy — Tim Berners-Lee etc. has launched a personal — Web Wide World Even called Solid. hub/platform data control with is jumping on the bandwagon, Microsoft in France, Back as Bali. known PIMS, its own " Facebook’s mobility data sharing, and the Finnish Natio- and sharing, data mobility avenues is considering Agency nal Education sharing education data. toward quality data or other benchmarks, serve as a serve benchmarks, data or other quality their of the state their monitoring means of know get to to help them overall, health and better. themselves hap- experiments There are also large-scale - Digime and the Ice Iceland’s pening abroad. are setting up a health data Ministry landic the Finnish individuals, for sharing service Department spearheading is Transportation a » » » » “MesInfos: Self Data Cities” — What if cities took a central role in

returning citizens’ personal data to them? P WHAT IS THE BEST WAY TO SHARE SHARE TO WAY BEST THE IS WHAT DATA 5 SELF DATA? PERSONAL MODELS GOVERNANCE and explored we on MesInfos, During our work gained experience with a specific typeof data it While cloud. model: the personal sharing that no believe we advantages, many does offer rendering capable of uniquely single model is are at There their data. over individuals masters perso- including models, shelf" the "off five least - modi which can be hybridized, all of nal clouds, one-size-fits-all a isn’t there that Given etc. fied, support the po- solution that can unilaterally public the local the role of Self Data, of tential guide will be to the movement, leader of entity, one or another personal towards collaborators model. data sharing governance describe here are models we The governance of differing orders of The magnitude. first two standpoint from a technical different very are which is not to cloud), personal transfer, (direct depends everything — are neutral that they say etc. their use, who drives are used, they on how third party trusted — models The other three data trust and civic data co-operative, platform, in that can operate are organizing principles — detailed providing By two. first the with tandem - gover these models of each of of explanations public inspire metropolitan to seek we nance, - struggle between proponents of privacy protec privacy of proponents between struggle gain on the and economic one hand, tion on the other. "who is allowed the question of to The answer who has i.e., — do things with personal data" to personal value from deriving of the privilege point our was It absolutely. important, is — data to departure research: how of the MesInfos for utility derive personally to individuals enable - neces "who" question But the from their data. —"to sarily entails reflection about thepurpose purpo- is in the realm of it because — what end" se that the risks and abuses reside. exclusive? mutually strategies So are these two which goggles, "tech the remove Or can we pri- between trade-off suggest a binary falsely that author Ben Green and innovation" vacy A The Smart Enough City? describes in his book, medium is what Self Data points toward: happy of control that puts individuals in a framework time al- and at the same their personal data, emerge in value-creating uses to new for lows so- and civil collective individual, response to cial challenges. SHARING PERSONAL PERSONAL SHARING GOVERNANCE DATA: MODELS research programmes, studies, "The publications, the agendas evincing interest tank and think But protecting personal . . . . legion are smart city these of much the poor relation very data is still problems that worst, at Individuals remain, efforts. 1.0. smart city were in as they just — solving need and participative promoters of for some At best, are treated like they cities at least, contributive data is essential to whose mobile smartphones urban affairs.” of the proper conduct (in French; CNIL - LINC ville. Plateforme d’une La in English) summary, project and conferences attended have we often All too to ques- finding answers to devoted workshops do get we share to people "How their tions like "Which le- better, the slightly or, data with us?" data sharing approaches will gal and technical privacy?" people’s also protect heard ques- we have — rarely far too — Rarely - "Why share personal data with the in tions like, We what end?" To them? dividuals who generate data as if it were treating personal been have or out in secret, be parceled to booty stolen during the never-ending protect a hostage to (September 2018 to 2019) with these three cities these three 2019) with 2018 to (September as We our defining by began partners in the field. in themed authority regional each of the role - empower with citizen formulated experiments Métropole in Nantes The themes ment in mind. food my impact of and limit the "understand were car- home’s my and reduce "calculate choices", the production to "contribute and footprint", bon neighborhood/city". energies in my renewable of manage "better the themes were Rochelle, In La improving to "contribute and budget" mobility my And for region". the transportation my in offering social my "oversee were themes the Lyon, Greater "understand and obligations" rights and services rights and entitlements". (social welfare) my ap- a different be exploring would Each territory use each its own and so to Data, Self proach to the agenda to according cases and challenges, that would The choices pursue. each was going to po- roles, actors’ — implementation project inform could they because be crucial, would — sitioning and unique data sharing models. new lead to - nizations to set up their own data transmission data transmission their own set up to nizations channels; new foster cities can data innovation, driving 2) By a) promo- by personal data governance of forms enable that projects and models piloting and ting trust, of via frameworks their data reuse to citizens ac and public private of variety a getting and b) around the same civil society and members of tors experiment to them the space table and offering together. in its capacity intermediary, relational As a key 3) as first pointof contact for all things citizen re- authorities are in the ideal po- the regional lated, role active a more symmetrical, establish sition to ur- enriching are presently Citizens individuals. to their own rather than with their data, ban services co-design, and mediation digital utilizing By lives. imagine Self Data to with citizens work can they cases use create and them, to speak that scenarios but needs, citizens’ to correspond that not only as challenges facing the wider region the also to a whole. that muni- not escape the conclusion could We in ma- play role to a special have cipal actors Our discussions with the king Self Data a reality. a MesInfos (already Lyon Greater French cities of and La Nantes of the City partner), pilot study Rochelle confirmed whatwe This hadconcluded. our launching the Self Data Cities project led to 1) As a data collector, it can lead by example, and example, it can lead by As a data collector, 1) it holds return the data to set up sharing protocols to This adds legitimacy them. to about its citizens the same approach, take others to ask a call to providers. startingservice digital its own with means has both the necessary government Local orga- regional convince to and the action force The local public actor must play the role of Self the role of must play actor The local public mo- new a of and facilitator mediator driver, Data metropolitan A personal data governance. del of make to is unparalleled in its capacity authority reasons: three for Self Data a reality Self Data is based on the idea of an innovation an innovation idea of is based on the Self Data or on a on disruption, focused that is not solely Self Data offer. new "revolutionary" startup with a their cities. bet on the future of to asks adopters from any emerge will inevitably services new True, more But program. Self Data ambitious regional radical- involves this direction taking importantly, at personal data, look we the way transforming ly multi-purpose, distributed, and creating a more holders, data gets that ecosystem value-enabling researchers and entre- social enterprises, citizens, in involved and general interest) preneurs (public to than local authorities Who better the dynamic. paradigm this into stakeholders regional guide shift? new role for regional authorities" as "mediator and and "mediator as authorities" regional role for new level. at the territorial change systemic of driver" “MesInfos: Self Data Cities” — What if cities took a central role in

returning citizens’ personal data to them? P - - Protector of Protector the transfer Individual ives consent eplicit Data holders Third party or party Third holder Data Data sharing Data tor-based approach might be more appropriate, might be more appropriate, approach tor-based perspec the from potential, reuse data that and somewhat. be limited might the reusers, of tive - "me individuals are is that Another drawback is though consent Even consent-givers. rely" the individuals can’t see explicit, and informed reuse their data they nor can "moving", data is fragmented: the process Also, themselves. minimum, actors, two to must be given consent the personal unlike Moreover, each service. for Everyone’s Everyone’s responsibilities are clearly defined, legal a mitigated it represents all, above and, and re-users. both holders for risk individuals allow not really it does yet And really to data, their of overview 360° a get to are not going to services it: third-party master sign and APIs holders’ different 1000 to connect sec a that means This contracts! different 1000 - tly between data controllers with the explicit, explicit, with the data controllers between tly services for individuals, of consent revocable can participate in public or so they provision - For exa or research projects. projects interest "Ene- the Enedis created provider energy mple, who have Customers project. dis Data Connect" that services smart offered are meter Linky a in- Enedis’ to with their consent, will connect, use and help them derive system formation This model has data. from their consumption therefore and actors, fewer a great advantage: implementation. as regards less complexity be signed between can potentially contract A specify to the data holder and the reuse service the of data protection,usage of levels processes, data (volume, retrieve infrastructure to bearer’s - potential could Some services etc.). regularity, to not allowed and hence "blacklisted" be ly security for system the data holder’s to connect example. for reasons, organizations using this Although there are few des- the model we — protocol transfer kind of the minds of in exist cribe here doesn’t really that the likelihood — the digital outside actors high, quite is probably it will inspire uptake and is coding, with" "mess it does not because with the current digital economy. consistent 2) Direct transfer 2) Direct prin- key on a grounded is transfer Direct direc place takes Data sharing ciple: consent. Exemples nal data, for example by allowing algorithms to to algorithms allowing by example for data, nal the data clouds without thousands of run over data means personal This clouds. leaving those and big data analytics power used to be could the individual of the control still remain under cloud sha- personal In addition, concern. they individual from sharing (data capabilities ring improving. are etc.) data pooling, individual, to them and their users and clients, plus there are there are plus clients, and users and their them up keep to connectors channels and transmission are another tool they For individuals, . . date. to who develop the ones — reusers For master. to projects cloud personal — services third-party trustworthy create to investment: extra require - with data-hol work learn to to have they services, and therefore data controllers, ding organizations’ align their effortsdata whose actors other with from theirs. differ may management approaches the ope- to technically adapt to also have They personal cloud platform every of rating system crea- to are used Most developers encounter. they opera- (GAFA) well-established for ting services to Android, or Google’s iOS Apple’s — ting systems or within the massive, — biggest name the two This is a Facebook. like ecosystems self-contained technology the when make to adjustment difficult users. few very is just emerging and has data sha- where personal In the digital economy, (personal organizers, services ring with third-party their to is integral etc.) transportpublic apps, the advantages of consider here we functioning, such environments data-sharing dedicated using in place Data crossing takes as personal clouds. a trusted carried out by a personal digital space, the though for Even as host. provider third party - fo is largely cloud sector the personal moment, - personal cloud = an indi "a cused on individuals: they looking at how research is underway vidual", use from perso- collective derive can be used to ...... 1 Data 1 Data sharing sharing Mr. Martin's Mr. Martin's Mr. personal server personal server Mrs. Dupont's Mrs. Dupont's personal server personal server 2 processing 2 processing algorithm algorithm STORAGE STORAGE Data Data holders holders Services Services réutilisateurs réutilisateurs Individual Individual personal cloud personal cloud At home At home At Central server Central server Central data Martin's Mr. data Martin's Mr. Mrs. DuPont's Mrs. DuPont's data data +... +... or or to their development. Even though there are many though there are many Even their development. to data holders perso- for using them, advantages to between another intermediary yet nal clouds are personal cloud Personal clouds are still very new. Low adoption Low new. very are still clouds Personal is a barrier individuals and data holders alike by The personal cloud is like a digital home: a space a digital home: a space is like The personal cloud their data from can aggregate where individuals one not server, personal their on sources different having The advantage of an organization. run by to designed services any that is server personal a their data will run on value from help them derive - as on-board com known a process — that server With a the server. the data don’t leave — puting and the data, to come the services personal cloud, can be developed Such services the data stays put. which are datasets, based on synthetic anyone by but not actual (in detail). (in form), representative yet and home, their digital leave to No data needs that and apps services individuals can still enjoy mobilize and triangulate their data that find they complete Individuals have "Store". on their cloud’s on their which is stored their data, over control is also (self-hosting or locally virtually machine, a possibility). 1) The TECHNICALLY SPEAKING, TWO VERY VERY SPEAKING, TWO TECHNICALLY CLOUD THE PERSONAL MODELS: DIFFERENT TRANSFER DIRECT VS. actors to act, and equip them with the tools they they tools them with the and equip act, to actors among them. select to need “MesInfos: Self Data Cities” — What if cities took a central role in

returning citizens’ personal data to them? P - tive tive can be re-identified to the individual: collective? possible in a really data anonymity is but data, other members’ cannot see Members collec other the of names the knows everyone procedures voting roster); the (via members tive - joint decision-ma also be open (debate, may is under no obligation a cooperative Also, king). virtuous data usage will be that (a guarantee to grant its members right to has the cooperative a data for resell their personal permission to and there are numerous examples cents), few handed with their being as heavy collectives of as organizations operating under employees governance. mode of classic any re- - and their derivatives - Data co-operatives models that make the few one of however, main, data and uses of collective foster it possible to these data. of where individuals remain masters Exemples - Data sharing Data of Collective individuals Reusers Public and private data holders data private Public and Platform from which to from Platform retrieve,store third with personal data and re-share services owned parties and develop the co-op members. by Coop shared decision making Coop shared vote) person 1 1 selected by the selected by coop members Even though data collectives open up new ho- open up new data collectives though Even are they rizons by confined in data governance, their own set of limitations: first andforemost time members must dedicate the amount of by the collective, (the bigger matters governance to Although this becomes). the more complicated the critical mass that burden can be restrictive, also members must large numbers of by created be weighty enough to flesh out a quality digi- that of in the absence In addition, tal service. critical there mass, is the - significantly heighte the collec by shared pooled data that risk ned - "there - col notion of “any Lionel Maurel: Antonio Casilli and Paola Tubaro, and Paola Casilli Antonio 4) The data co-operative The data 4) jointly to a group individuals formed What if they how decided then and data, their manage collec them, share and them use to wanted tively? This is the route of the (still rare) data of This is the route tively? principle that 1 in- Based on the co-operative. de- jointly members co-op data vote, dividual=1 search en- apps, (chat and services tools velop grant them control that eventually etc.) gines, might The collective Z. to A their data from over via them share to together decide also simply public to contribute to example for a platform, creation. knowledge how of control individuals regain In this model, (sharing) others by used is data personal their of make will themselves they uses the of and - exis might adopt They creation). them (services (email services free-standing ting open source, their own. or develop etc.) or chat services, - supportiveThis model is particularly col of In data pooling. that require initiatives lective valuable more made be can data personal fact, resear- to According when not used in isolation. chers is nothing more collective than personal data". data". than personal is nothing more collective National France’s of add the words we this, To Centre for ScientificResearch Associate Scien- tific Director decision a collective data must include lective and severally that incontestably making power its members”. resides in the hands of The keyword in the trusted third party platform platform third party in the trusted The keyword close very all, after model is, the — "trust" is concept the current paradigm it, so without — Google’s to plays operator platform The not change! would and also centralizes guarantor transfer the role of and the data rests the tool over Control storage. - provi as organization, the of hands in the more it services the and manager of the platform der of such as services the way is similar to This offers. Amazon and Netflix use platforms (but minus a services products and their own promote PIMS) to their of view a global Individuals still maintain . . . - provi are often these platforms Nowadays, data. be to Data reuse tends large institutions. ded by data personal and services on integrated focused al- postal platform DigiPoste France’s sharing (eg: and data the documents organize to users lows needed to build a real estate application file and an agency). share it to Exemples Data holders Central server Central data Martin's Mr. data +Mrs. DuPont's + ... Platform storage Platform Individual Data sharing Data Access Individual Central platform Central + platform integrated services Individual rants consent rants Reuser and Reuser data other holder services A key facet of this model is basically that it is the basically this model is of facet key A vault: a portal a digital of platform/ version 2.0 and orga- users can retrieve where personal space data from multiple sources, documents and nize services of advantage take also and them share - from third parties inte been or ones that have is a personal So how the platform. into grated data On a personal cloud, Storage. cloud different? - and data proces on a server, is centralized storage third parties than elsewhere is performed sing by - is an exa Record Shared Medical France’s locally. although platform, third party" "trusted a mple of document rather than it supports mostly today data and aggregation, is used chieflyby usersto rather than share data with health professionals services. via dedicated reuse them 3) The “third party platform” party “third The 3) - Exemples THREE MODELS THAT ARE TECHNICALLY ARE TECHNICALLY THREE MODELS THAT WHOSE GOVERNANCE SIMILAR, BUT THIRD THE TRUSTED DIFFERS: APPROACH AND TRUST CIVIC DATA PLATFORM, PARTY COOPERATIVE. DATA cloud, the data flows to the services, which means means which services, the to flows data the cloud, wit stored and data are duplicated that personal A separate entity can, however, play the role of the role of play however, can, entity separate A the and individuals between party third trusted and re- organizations (data holders other two guarantors". "transfer them as of think We users). data of and authenticity ensure the security They individuals dashboard for a sharing and provide their and manage oversee (and organizations) to portability to data rights and obligations related (and thus consent/sharing), data erasure, modifi- etc. cation, - the prolifera to This contributes service. hin each privacy personal and makes data, personal tion of vulnerable. mechanically “MesInfos: Self Data Cities” — What if cities took a central role in

returning citizens’ personal data to them? P far more sense to treat them as smaller, agile treat them as smaller, sense to far more In trust”. governing one overarching, units than - data hol work, data trust to a civic for case, any hold. they share the data to agree to ders have in- Data, Self with the spirit of And in keeping merely than more as treated be must dividuals must be granted they — contribute the data they to framework within the governance real power define future uses. Exemples sions, etc. — — according sions, etc. to the conditions defined a step also represents This model the group. by do on their own data Public Open Data. beyond market, services the emerging facilitate not really good, the public serve to ones designed especially data may data with personal but crossing public uses. new entirely the creation of to contribute done being work the of majority the in Today, on emphasis is placed little around this model, In fact, individuals. the role of personal data and role in re- a peripheral only personal data play data manage- development, gional data platform data trusts. civic ment and the wider domain of But some trust builders are starting an take to the platforms, party third to Similar it. in interest “Who is the third individuals is, crucial question for offered when Google Toronto, In exactly?” party, imme- proposal the trust, data a civic up set to “Will Google be as, raised questions such diately a seat at the given choose the trustees the one to Some table when it to definingcomes the rules?” one — up with alternatives are starting come to with Toronto of the National Library entrust is to Sean by As noted oversight. of the responsibility Civic many build to easy as just is “It McDonald, so build one, as it is to example, for Trusts, Data use case to them according organize could a city are Trusts need. public or group representative or abi- data’s and given replicate, to easy structurally it makes re-use, support to non-competitive lity API data Trust platform Trust Third party services party Third data Enriched services and data Enriched services and Individual PUBLIC AND DATA PRIVATE HOLDERS The data can be physically stored and accessed and accessed stored The data can be physically or can be left our diagram), (see via a platform “trusted the and the trust becomes are, where they data and secure private who oversees guarantor” causes to contribute to example for — transfer discus- policy public interest, the public that serve According to the Open Data Institute, a civic data a civic the Open Data Institute, to According independent structure that allows legal “a trust is third party”. a trusted data by management of pri- actors, public can comprise body The trustee go- Its society. civil of members and actors vate but those rules rules can be multiple, vernance the use of on the trust’s consensus must facilitate by it to entrusted data non-personal and personal individuals and data holders. 5) The civic data trust data The civic 5) “MesInfos: Self Data Cities” — What if cities took a central role in

returning citizens’ personal data to them? P model. . . . The risk of a buyout by one of the the of one by a buyout of The risk . . . model. - Face or Google, Apple, like Leviathans web’s fantasy”. as sheer not be dismissed should book users and build the ne- So what will reassure - tech open source Are the use of trust? cessary data taking one’s of possibility nologies and the elsewhere if the service is bought back suffi- - consi us to Maurel invites cient guarantees? be can relationship the that possibility the der , avirtuousa Coopcycle along the lines of one co-ops messenger bike of European federation consider to need current thinking is that we “my and the soli- the digital Commons converging models that are part develop to economy darity limit but also aim to sphere, the economic of asprofitability an endgame from start, very the efforts other actors’ and market and reinvest interest”. the public serving into they can be enacted. According to the above, for for the above, to According can be enacted. they trus- a as classed be could Facebook example, so could and — provider platform third party ted of launch with its recent evidenced as Microsoft, the data storage of consideration Careful BALI. - If a data co-ope paramount. is equally aspect anyone where data in a country stores rative data the over control individual it, can access the same These are essentially a hit. will take in the digital platform issues that pertain any to on who oversees depends Everything economy. Then rules. which to and according the model, you, should another question arises: what role and Tools in the model? play actor, the public And sponsor? tender Public provider? services res- place put in who ensures the framework is No choice involved? stakeholder every pects will be take you course and whatever “wrong”, the emerging given in some way, experimental Self Data. the domain of nature of - consi landscape to Then there is the economic say who is to third party, is by If governance der. them force will not eventually that investors and hand over other service, any act like to in personal data? Lionel Maurel (Calimaq, users’ Tim Ber- question after very this French) asked that his startup announced Inrupt had ners-Lee capital giants venture from funding secured (and with success “If Solid meets Glasswing. do what guarantee hoping it does), to here’s change its suddenly that Inrupt won’t have we in the hands of a single (public or private) or private) single (public a hands of in the several by or is it controlled organization, a group (shared governance), organizations alone? or the individual individuals, of who is the mo- use(s): The question of governance Do the data del destined for? - indivi favor framework and governance to groups, uses (for dual uses or collective etc.)? good, the common to contribute » » data governance positioning the models of By and equip hope to we axes, along these two among them. making the choice guide actors platform, third party trusted The personal cloud, individual present mostly all transfer and direct The personal cloud puts the use possibilities. the per- of and control a digital home, of keys indivi- in the hands of sonal data it contains, the platform duals; the for third party platform, and seat; driver’s the in is organization provider the data-holding organizations in data transfer, Both data sharing decisions. over power have data trust and the civic the data co-operative but radi- use, collective for vast potential have em- gives first the control: of loci different cally whereas the individuals, to the data pire over seat a marginalized at best, them, offers second making table. at the decision Despite the utility of having clear definitions, the way remain cautious of to you advise we CT A T A D

TST AL 360° T AD A TST CIIC DATA LAS OOLE) SIDE CO M DATA A T 360° A COOPEATIE COOP MID The question of control: who is holding the who is holding control: of The question per- what kinds of over reins? Does the power it rest use to and how collect to sonal data Shared governance 1 individual = 1 vote. A co-op platform for user data aggregation and collective A co-op platform for user data aggregation and collective decision making regarding data use(s) (Public / Private / Civil entity) A trusted third party ensures the proper use of the data shared with it (personal data, public data, company data, etc.) » The choice of one model over another rests on the on rests another over model one of choice The questions: key two to answers » NB: This diagram presents a seemingly definitive categorization of these models. It is based on an analysis of the present situation. definitive categorization of these models. It is based on an analysis of the present NB: This diagram presents a seemingly are evolving). as is their ongoing permeability (e.g., the collective uses for personal clouds The use of more than one model is possible, Use—Who is the model for? Are the governance framework and model designed for individual usages or collective (groups of individuals, general interest, etc.) ones? SE AT FO) Digital home 1 server = 1 individual) Portal. Consent. Allows individuals to store and administer data from a variety of sources and use applications designed to run on this individual private server. A personal cloud can be self hosted. Portal/Personal Area developed by an organization that enables data and document retrieval, storage, sharing and the use of integrated services or services developed by third-parties. Data exchange happens between data controllers directly, with the explicit consent of the individual, for the purposes of service provision and/or to support a cause in the public interest, participate in a research project, etc.

A T T A CT to do the opposite, and provide citizens with indi- with citizens and provide do the opposite, to let people want to may Some services. vidualized res- them entirely and make — data their control ponsible and for some — their may finddata that and suggest citizens, for heavy the burden is too third party. trusted go through a that they INPT DIIPOS CONNE ENEDIS D CLOD DIECT TANSFE PESONAL ENS France CO 360° 360° Onecub 360° TSTED TID Connect FairSmart PAT PLATFOM DDA individuals? S IC MODELS OF DATA OENANCE FO IC SE CASES DATA OENANCE FO IC IC MODELS OF O) of an organization that use? Does the Who is holding the DDA DDAS CONTOL the hands of several reins? Who controls the uses for personal data and the terms of (public or private)? In individual or group of organizations (shared governance)? Or does power lie in the hands it lie in the hands of an AAT AATS - All five of these personal data sharing strengths have models and weaknesses. ac public Local want may Some Self set up a to Data project whose purpose mas- create is to collective sively perso- uses for while nal data, wish may others tors embarking tors on Self Data will make to have One choices. model is not ne- more cessarily virtuous than - eve — another rything depends needs the on and constraints the actors of it. who oversee MAKING A CHOICE: WHY CHOOSE CHOOSE WHY CHOICE: A MAKING OVER GOVERNANCE OF ONE MODEL ANOTHER? “PERSONAL DATA AND CITIES” — AN OVERVIEW OF INITIATIVES AROUND 02 THE WORLD “Personal data and cities” — An overview of initiatives

around the world P in Europe, the hubs in Cameroon, Japan, Brazil, Brazil, Japan, hubs in Cameroon, the in Europe, - and will cer active particularly are and Korea in these territories. initiatives launch tainly PROTECTING CITIZENS’ PRIVACY CITIZENS’ PROTECTING indivi- protect to taken measures Examples of in our the most prevalent were privacy duals’ data priva- In the Self Data dynamic, research. - when establi are prerequisites security and cy - ma and storage, recovery, shing personal data nagement channels.. about cities asking themselves The number of pos- personal data they the citizen-generated managed that data are how especially — sess and used — is significant, and growing. Issues transparency of the lack to abound relative protecting about which data are being held, da- of and the proliferation privacy, citizens’ places. in public ta-capturing systems share ways to for strategies devising Before some inhabitants, personal data with a city’s raised questions about the have actors public capture data and use to infrastructure needed where sensors are more In cities it ethically. ini- and where Smart City and more numerous, think it is essential to off, taken have tiatives pro- to and how work these devices about how cities have number of A privacy. people’s tect up and running across the across running and up hubs MyData lized, Self Data concept. We put the approaches put the approaches We concept. Self Data lized, 4 categories: into privacy; 1) individual decision making; citizen 2) using generation data 3) metropolitan sensors; citizen Data. Self “pure” 4) - seve — are exclusive these categories None of found We all four. belong to could ral projects of possibility the considering cities are that few of in the governance citizens including actually or deal with privacy The majority personal data. do not discuss we with Open Data (a subject this study). of as it is outside the scope here, in- build new cities are trying to though Even establish a none are looking to frastructures, - speci require which would Self Data dynamic, measurestofic address both data sharing from transparency. and overall individuals holders to the ini- of is that the majority note One thing to - Wes in are being conducted found we tiatives largely drew we review, this For countries. tern from reports major and articlespublished by American institutions and European and North Open Data Institute, including the tanks think data sharing and But personal etc. CNIL, Nesta, there are almost Mydata/Self Data is pervasive: twenty mostly can be found and although they globe,

, datasets are enriched , Transport for London and Waze, and London for Transport uses its customers’ and uses its customers’ Uber Movement lity. There is the example of Vodafone, who is who Vodafone, of is the example There lity. enrich to Barcelona of city with the working its Open Data Portal; the data sharing - agree ment between data. anonymized drivers’ - Self Data is emerging as a complemen Today, data re- the existing to alternative or even tary in the de- including people by — system covery them turns it sharing, data about made cisions their data. of masters into cities and personal data pro- this In compiling categorize it useful to found we overview, ject it contributes how of each approach in terms unrea- yet and as the overarching, achieving to which gave rise to WiFi connectivity across the WiFi connectivity rise to which gave ser- Waze the enrichment of underground plus vices using TfL crowdsourced data; and across Uber with a collab in San Francisco, the pond, the rescue improve to intends and RapidSOS services. emergency the city’s to data provided the has taken on the other hand, City, York New - injunction against certain com legal of route rental data from real estate obtain panies to for and Airbnb, example, traffic data generated There are also Uber andLyft. taxi companies by or Uber Movement Strava Metro like platforms - mobi to that grant cities (but not only) access On Strava Metro data. lity personal account, via their users swathes of by while - (in a number of da- a number of - city: Perso a of “The platform partial English translation) which out analyses analyses abound; we will not expand further on we invite the you topic to However, here. consult reportthe CHILD’s the smart of city” as the cornerstone nal data but also the involved, the stakes lines not only of “the datafication reconciling pathways towards civil liberties”. of the protection and the city sharing” data “personal words when the Today, re- do they rarely very cities, of emerge in context that frameworks or to Self Data autonomy to fer Ins- data exchange. of put individuals in control variety a between place takes “sharing” the tead, The Open Data Ins- actors. and private public of titute in London has identified and private the between transactions ta-sharing public sectors, and classified them according to pur- objective role and actor public criteria: two - collabo user, as act can entity public The sued. andto seek financier or regulator, customer, rator, im- competition, promote innovation, stimulate data, over and accountability transparency prove support support research and political planning, - or assume regulato making, operational decision cities between data of The exchange functions. ry of either in the form increasing, is and companies obligation a legal of in the form or collaborations companies. towards - cities coopera of examples There are many mobi- in the domain of actors ting with private French; After several months researching the Self Data Ci- months researching the Self Data several After world, around the happening initiatives ties-style we understand that our definition what Self Data some And advanced. yet, fairly is and does is still the see to begun have cities and local authorities empowerment citizen of at the crossroads — value that giving ci- — development and technological their data represents. over control tizens Digital for the Cities Coalition For example, the cities launched by a joint initiative — Rights with York, and New Barcelona Amsterdam, of the support of UN-Habitat, and EUROCITIES, the of number a with conjunction in worked — UCLG promote, help them protect, to cities worldwide digital rights. visitors’ and residents’ and monitor an increasingly become data has clearly Personal of both in terms cities, for essential resource - improve services citywide operations and public those provide directly citizens Sometimes ment. are typically actors and regional but public data, was practically The Smart City the data holders. including its implications as a topic, unavoidable individual personal data management and use, for technologies new and the introduction of privacy, critiques and Smart City sphere. the public into CITIES AND CITIES PERSONAL WAYS WHAT DATA: CITIZENS? AHEAD FOR WORLD AROUND THE AROUND OF INITIATIVES INITIATIVES OF AN OVERVIEW AN OVERVIEW AND CITIES” — “PERSONAL DATA DATA “PERSONAL “Personal data and cities” — An overview of initiatives

around the world P - research pro- research MesInfos - informa the via with share data to wish they the data which will transmit system, tion bank that under conditions those organizations to - An experi in advance. upon agreed been have DAC 2018 by in September ment was launched Consortium Inc., in partnership with Needs Hitachi. have also already been identified in the And Ja- andagriculture. health, fieldoftourism, global partners, FIng’s one of Data, NTT pan’s a launching be soon will in tandem with partnersject from the banking, retail sectors. and insurance, res- agency the government in Finland, Over in the Finnish promoting safety ponsible for a MyData pilot begun has system transport Trafi its personal of the transformation catalyze to is an im- The agency data management system. gathering resources portant driving data holder, and driving professionals licenses from drivers aim was The pilot’s across Finland and Sweden. im- these data subjects offer to enable them to significant and control, and access data proved Until reuse data. them to for real ability the ly, model was based on obtai- the agency’s now, consent ning to subjects’ the offlow theirdata Based and organizations. companies between use a on focused pilot the principles, MyData on case involving 200 testers. Trafideveloped a en- to personal platform API and Wallet MyData and manage, share, to drivers able professional their driving right and professional use of make . Let us Let . - exa is to One way in urban areas. development or respond improve can vegetation mine how toolkit via its phyto-sensor air quality to sen- between a clear distinction make therefore to little have that people in cities sor initiatives digital advertising (eg: screens over no control views) audience transportin public track that have not only where Individuals and initiatives also are but collect, they data the over control op- by example for participantsactive in its use, their of interests the serve to it share to ting broadly. good more the public and communities DATA IMPLEMENTING SELF call 100% presents what we Our last category in- in that here, Self Data experiments, “pure” their data and do retrieve dividuals personally Such initia- choose with them. they whatever and are a muni- and far between, are few tives of with the number when compared cipal rarity sensing. or citizen on privacy focus that projects that the Self at the national level It is mostly promise, the most is showing Data approach of variety emerging is a versions with different its Data Banks (or Japan is developing contexts. secure the databases for — Banks) Information - perso of and sharing management, collection, with individuals or companies nal data held by Indi- subject. the data of consent the explicit choose the companies viduals will be able to project — a representative a representative — Making Sense project purposes, while their potential for personal use personal use for while their potential purposes, example limited (one developed fully is rarely Ci- ). Capteurs Citoyens initiative is the French emancipation citizen for are tools sensors tizen tools technical to access grant citizens they — in doing and their city “measure” can use to they pol- awareness of a policy-oriented acquire so, are But they example. for lution or radioactivity, of sources and also free useful also extremely be able to not otherwise data that cities would pri- in taken measurements especially access, tools should not become Sensors spaces. vate — their citizens manipulate that cities use to opportunities in- to concrete offer should they operations inhabitants in metropolitan tegrate generating for management and act as tools shared knowledge. The that sensing experiment a citizen of example their data how over control inhabitants gives offering by track, right the on is — used is participants help citizen to learn workshops and in Belgium levels radioactivity measure to this). on more for below (see Netherlands the Sense is in the called Citizen Another initiative and de- questions, It contextualizes, vein. same - environmen democratized for avenues velops practices. sensing citizen through action tal - comple three serve is used to Data detection obser- measuring pollution, purposes: mentary sustainable promoting and fauna, and flora ving ), Syd- ), ). and Madrid (DecideMadrid Say), Your Sydney USING DEDICATED SENSORS TO TO SENSORS USING DEDICATED CITIZEN DATA GENERATE - equip — sensing initiatives citizen number of A control data sensors that they with ping citizens with the tools citizens providing emerged, have — im- use to can and share data the city capture to what approach is closer to This its offerings. prove produce in that citizens Self Data, consider we data that they can the choose to However, share. a city’s serve to solely generated data are often they sign a petition, or data sharing via dashboards via dashboards or data sharing sign a petition, they dashboard ) designed the BCNOW example for (see use. collective for are cropping platforms democracy Participatory (decidiTorino Turin, like in places up all over, ney ( ties between stronger of the forging time, Over the lines along — and Self Data tech” “civic such citizens if Imagine likely. is highly — Decidim of - speci push for pool their data to choose to could near living residents (eg: taken be to measures fic Collectives pooling their health data)? a factory - collabo to use a platform be able to also would pu- that serve Self Data services develop ratively for app reduction a CO2 like objectives, policy blic assertpublish a call to or to their right members, to actors personal data with public share their to plans in their region... mobility improve - - di source open Decidim INCLUDING CITIZENS IN DECISION DECISION CITIZENS IN INCLUDING MAKING and ques- back a step takes category Our second personal data governance approaches to tions how in metropolitan decision might include citizens across a number of place take This might making. privacy that participants’ and provided mediums, can be essential bridges these tools is respected, a metropolitan area and its inhabitants. between that give developed been have platforms Several of leaving them in control while voice a citizens their data. although still an — this category of Emblematic the — example isolated supportsgital platform participation citizen that It is being city. any the walls of beyond extends tested in 35 cities, including Barcelona, Roubaix, The Decidim plat and Waterloo. Mexico, Helsinki, as as well private use by available for — form social councils, organizations such as city public neighbo- unions, NGOs, universities, enterprises, allows users — to - co-ops confi rhood collectives, launch to “spaces” gure participation areas or processes, conduct hold assemblies, initiatives, these and enrich all of . . or handle consultations. meetings, via support face-to-face for offerings and reports, follow-up votes, proposals, surveys, - an inte of all within the parameters . . comments. au- control module enabling individuals to grated should anonymity thentication data transmission, There are many other examples of such initiatives. such initiatives. of other examples There are many has a Metropolitan Data Char- Métropole Nantes and - Barce Amsterdam, Montreal, ter; and Boston, regarding stance an explicit taken also lona have Self Data. of a cornerstone privacy, We also note that many of these cities have wide- cities have these of that many also note We and years, recent Open Data in of ned the frontiers data sharing city that facilitate platforms created open of Is the terrain third parties. and reuse by consider to begin to right place data sharing the its After data privacy? citizens’ of the protection Open Data campaign in 2015, the City of the Internet Guidelines for its produced of York New designed to recommendations a series of Things, Echoing that privacy. citizens’ help others protect Principles Privacy a Seattle produced approach, data departments integrate help city to toolkit guide- and other Open Data-related transparency city’s the after issued was publication The lines. sensors in of network a massive installation of drones was met with of and deployment the city - there is the exa Finally, serious backlash in 2013. whose Digital Privacy California, San José, mple of 2018) is actively Group (launched in May Working a month. once meeting taken steps in this direction, to varying degrees. degrees. varying to in this direction, steps taken “Personal data and cities” — An overview of initiatives

around the world P - pro Data Cities Self stance on personal data and its use by and for in- and for its use by personal data and on stance city by as demonstrated is still unique, dividuals course of and and Grenoble, Rennes in initiatives the within practice into put with the cities of in conjunction led have we jects Lyon. Greater and Rochelle, La Métropole, Nantes Trust Store platform, and Toronto Toronto and platform, Store Data My , a private and se - and private a Folder, Citizen Digital is a personal data aggregation and aggregation Digime is a personal data cure digital repository where personal documents where personal cure digital repository From a single point they all citizens. for are stored and data all their personal information can access The ci- portal. web from the municipality’s directly project, with its Digital Register Amsterdam, ties of its and Trento Data the Civic of consideration and London’s are each venturing into the Self Data ecosystem; in the a spotlight on their projects will shine we outlined The French approach, follow. to sections individuals places this report, of chapters in later groundbreaking Our heartthe at data. their of At the city level, we draw your attention to projects projects to attention your draw we level, the city At Milan’s like Another good example of a Self Data initiative is initiative Data Self a of example good Another in health sector positioned in the a project Digime, Iceland. managed to The company management platform. in partnershipset up an experiment with the go- were vernment and Testers its Ministry of Health. in the stored personal health data retrieve able to data retrieval, Beyond system. information state’s of the development encourage to Digime seeks the uses of new that foster applications dedicated streamline sharing with treatment, track data (to etc.). and health professionals, caregivers qualification datato demonstrate their eligibility for specific jobs and streamline procedures asso- with their work. ciated Amsterdam, citizen sensing for a elsinki, the cradle of Self Data. responsible smart city London, creating newer, more #SelfData SPOTLIGHT: A trustworthy collective structures #citizensensing #privacy #CivicDataTrust CITY-BY-CITY creating new Toronto, from Smart City to trusted city? hent connections between PROJECTS : PRESENTATION OF #CivicDataTrust the city and its inhabitants. reater Lyon > DECODE provides tools that put PERSONAL DATA #SelfData #Privacy bolstering support for individuals in control of whether social welfare INITIATIVES they keep their personal data #SelfData private or share it for the public PROJECT CATEGORIES: Trento, using smartphones as Each of the following examples sheds light democratic tools good. on what we consider to be a major metro- #SelfData : cities give citizens back their personal #SelfData politan initiative. Rather than being stan- data so they can use it in ways that serve their inte- renoble, making the move > Making Sense, empowers Eu- dalone projects, however, each is woven towards energy cooperatives into the fabric of a (typically European) rests and the common good. ropean citizens through personal #SelfData arcelona, citizens at the heart of the city. initiative that involves several cities. Those digital manufacturing, co-desi- #ParticipatoryDemocracy #citizensensing #privacy initiatives — including DECODE, Making #ParticipatoryDemocracy : cities invite citizens to gning and deploying of environ- Sense, Solid/Inrupt , Sharing Cities, Euroci- ennes, shifting from digital #SOLID #DECODE actively participate in policy decision making via dedi- workspaces to personal clouds for mental sensors. ties, etc — are building the bridges that lead education data to even more widespread sharing, commu- cated platforms. nication, and collaboration. #SelfData > Sharing Cities, works toward #citizensensing : citizen-controlled sensors en- building democratized smart ci- able them to help the city by contributing to a body of ties. shared knowledge. > SOLID, a new paradigm for a #CivicDataTrust : cities identify trusted third parties decentralized Web. who can oversee and ensure the ethical use of perso- nal data.

#Privacy : cities identify trusted third parties who can oversee and ensure the ethical use of personal data. “Personal data and cities” — An overview of initiatives

around the world P (Barcelona ) Plaça Del Sol (Barcelona (Amsterdam) map- UrbanAirQ (Amsterdam) Making Sense Making The Making Sense project (2015-17) - Com the European by was co-funded ways explore to Its aims were mission. and uti- appropriate could that citizens them allowing tools open source lize transmit loca- and analyze, capture, to and in doing environmental data, lized pres- participate in solving today’s so, issues. sing environmental efforts divided between were Project the Smart Kit and Citizen developing install to initiative galvanizing citizens’ those two Over and use the sensors. communities other European years, simi- a in initiatives explored cities and lar vein: streets, ped out pollution in the city’s measured Gamma Sense (Amsterdam) radiation, chartedpollution, neighborhood noise and Smart (Barcelona) Fab Kids Lab raised families’ (Amsterdam) Kids Lab do, awareness about what sensors can (Kosovo) in Prishtina Air Polution and involved youth the city’s get sought to pollution. air of issue the resolving in Tada Tada , an open registry of all of an open registry , The Sensor Register Upstream of concrete experiments, the the experiments, concrete of Upstream - profes published by and written — Manifesto — in 2017 region Amsterdam the sionals from - and govern companies, organizations, invites ment authorities to read and affirm a setof 6 responsible cities’ to related ethical principles data. use of in its ensure transparency to drive Amsterdam’s Data its City operations is further underlined by of vast array A only) open data portal. (Dutch on the anyone available to been datasets have platform since 2015, with categories ranging traf- buildings and plots, to spaces from public health theof quality fic, care, environment, life, some of and However, subsidies, more. permits, on the portal the data stored generated were various organizations, sensors that belong to by and their diverse formats makes reading diffi- cult. address to seeking is city, the in installed IoTs surveillance these over control of lack citizens’ - Unfor transparency. more create and devices, hindered by their progress has been tunately, about information obtain precise to an inability questions about the to Answers the devices. data they which kinds of and locations, sensors’ within what are cur- be found are to harvest, siloed departmentsvarious orga- inside rently nizations and businesses. - Gebiedonline (Neighborhood AMSTERDAM, CITIZEN SENSING SENSING CITIZEN AMSTERDAM, CITY SMART RESPONSIBLE A FOR number a launched has Amsterdam of city The DECODE Two projects. personal data-related of since agenda part been city’s the have pilots of 2020. December until continue and will 2017, which allows pilot, One is the Digital Register data personal retrieve to the city residents of and use them on in municipal databases stored Attribute the of its use to thanks terms, their own - mecha (ABC) authentication Based Credentials The pilot nism. circumvent to Online) uses the same system when credentials Facebook provide to the need local social networks. to access seeking launch to helped the city DECODE In addition, vacation rental owners’ on focusing an initiative requires law recent A Airbnb). personal data (eg: furnish data about the rental pe- landlords to must not ex which their property/ies, riods for ceed 30 days per year. Until now, homeowners homeowners Until now, year. 30 days per ceed information amount of a massive supply had to to Thecomplete their citywanted profiles. this opting to and by be more ethical, to process mechanism, Based Credentials Attribute use an by shared be could data of amount minimal a consent. explicit to share them. Now, the question is: how how the question is: Now, share them. to that is groun- economy a digital create to and controlled, data generated, ded on and that also takes shared collectively, account? into individual privacy it is — per se platform is not a DECODE the emer- foster designed to a project in- allowing open technologies of gence and share their data control dividuals to were Four set pilots fit. see they however Ams- and Barcelona up in the cities of test to 2019, and 2017 between terdam during the developed technologies new the focus: themes were Three project. open de- Things (IoT), of the Internet economy. the collaborative and mocracy, and were trust and privacy The issues of the solutions being imple- to are central mented. and - Ci Project (DEcentralised The DECODE Data Ecosystems) tizen-owned January — project is a 3-year DECODE the funded by — 2019 December to 2017 under the aus- European Commission pices of Horizon Its 2020. objective is to the way to practical alternatives develop especially today, the Internet use people The goal is use personal data. they how value inherent the social demonstrate to their per- control to citizens in allowing ways different sonal data and illustrate - diffe sensors that measure install and control to noise including air and — pollution of rent levels and homes. their neighborhoods in — also pays particular the pri- to attention The city and this means protecting citizens, its of vacy The Digital Democracy their personal data. between place which took pilot, Data Commons the im- enabled April 2019, 2018 and October module on the city’s a DECODE plementation of par- to citizens allowed which platform, Decidim projects in platform-related anonymously ticipate their data. a minimal amount of for in exchange - Barcelona Barcelona Making Sense , which , CityOS , which has two pilots which has two project, DECODE Platform, which brings a range of city data city range of which brings a Platform, Barcelona has been a pioneer Smart City city city Smart a pioneer has been City Barcelona 22 into organized 122 projects It has 2011. since in was elected Ada Colau When Mayor programs. the began city to 2015, move in a different direc BARCELONA, CITIZENS AT THE AT CITIZENS BARCELONA, THE CITY OF HEART emerged have projects of variety a then, Since might play actors public on the roles that focus large-scale Two in personal data management. the attention: the city’s attracted have projects European tion, and make citizens a central part its me- a central of citizens and make tion, concerns Ethical development. project tropolitan interest growing city’s the for impetus the were - and interope Data Commons, in open standards, rability. earlier the and city; the in underway sen- citizen on focused which (2015-2017) project va- a high places The city sing implementation. citizens which offers lue on the sensing approach, and city the about data create to opportunity the are notable: projects Two it is used. how control sensor which established an open source Sentilo, and data collection platform; and data analysis. for open platform another deployed their built city the , partAs DECODE of Now including data gathered by in one place, together Data Governance Science the Citizen Finally, citizens. opportunity the inhabitants gives (DECODE) pilot “Personal data and cities” — An overview of initiatives

around the world P TORONTO: FROM SMART CITY TO TO CITY SMART FROM TORONTO: CITY? TRUSTED in partnership- with Goo Toronto, of The City gle-affiliated SideWalkLab, recently launched wa in its Quayside - called Smart City a project on topics There are a range of district. terfront public mobility, including agenda, the project’s and development, sustainable housing, space, This digital last innovation. theme has fivekey and accessible coherent developing objectives: data stan- creating new digital infrastructures, and data, identifying responsible uses for dards, that be- digital services set of launching a core nefit the city elicited however, has, project The Smart City highlighting despite all, First of some criticism. inhabi- the city’s inclusiveness, its desire for due to excluded been have that they tants feel and little communication. information of a lack about personal raised also been have Concerns city Which data will the and use: data storage necessary be would It what? for and . . using. be between differentiate somehow to the city for urban data personal data and the anonymized the issue, clarify To use. to is likely the city - dee — visual language designed SideWalkLab med highly insufficient—by some and posted dotted the data capture devices explain signs to could around the neighborhood so that citizens har- which data they are used for, what they see to house to (PODs) tions and tools for decentralized web web decentralized for tools tions and are based on that app development is The goal principles. Data Linked it uses — WWW a new create not to and protocols standards WC3 existing (HTTP, REST, HTML, etc.). URLs Today, documents, readable toward us point data point to them to but Solid wants si- http addresses to using By as well. addition with the datapoint each tuate of three identifiers(object: link source, tar- link subject: type, link predicate: the relationships between get) a sea of can available make and create we data no longer only would Web The swell. ques- to answers of us instances offer compile be possible to it would — tions (data) “protein” the to thanks our own, a With the support Inrupt, of it. feed we users Berners-Lee, startup by founded - perso their own create will be able to stores data online nal their data. over and maintain control - could become become could Solid platform SOLID : Linked Data : Linked SOLID creators the one of Tim Berners-Lee, (re) to wants Web, Wide World the of decentralize the Web. His idea business models existing countless puts and exploiting based on harvesting What question. personal data into users’ the ones were happen if people would hence and data, personal their storing ex any to inaccessible them rendering businesses, (government, entity ternal web’s The their consent? without etc.) - Face Apple, Google, (eg: hitters heavy the so-called Microsoft, Amazon, book, no ad- little to see likely GAFAM group) but — adopting this system vantage to and local emerging business concerns authorities) city entities (like public gauntlet up the take well very could is Ghent Berners-Lee. by down thrown a case in point. The cities looking to a springboard for reshape their personal data policies. giving individuals by Solid empowers Its de- their data. over them control - conven sign is grounded on a set of tions), that will also enable tions), them to fill out forms stored information the personal to (thanks faster on their profile) and contribute to citywide de- participationvia an online velopment platform. Ser- Ghent Library exist: already features Three request childcare and Ghent Sports Service, vices, service. initiative its Hallo.gent launched Ghent 2018, In online their own with citizens provide aiming to will The system websites. domains and personal ser- municipal any for citizens register be able to data (proving the necessary only and retrieve vice personal their entitlement) from the individual’s ever without the municipality Mijn Gent portal, additional personal in- or store collect to needing These 100% unique personal websites formation. Tim designed by the PODs are similar in design to can websites The partas SOLID. of Berners-Lee applications, applications complete and generate their per- how control to individuals which allow and shared with local au- sonal data is accessed thorities. (Flemish language) project wants to wants to Mijn Gent (Flemish language) project The city of Ghent was inspired by Tim Berners-Lee Berners-Lee Tim Ghent was inspired by of The city as a tool the Internet preserve to and his intention their effortsTheir by are bolstered democracy. for the from Verborgh Ruben Prof. with collaboration Ghent. of the University Multimedialab at Belgium has a complex system of their trust in their of governance; the majority place people managing their to local authorities when it comes authentica- data trustworthy providing and data authorities must City and services. tion protocols with other in close collaboration work therefore An as with citizens. as well government of levels important part is designing more ethical this of - Bart Ros systems. management data personal seau, Ghent’s Chief Data has Officer, stated that act as regulators, entities may data governance As personal data. of validators and creators, users, only) language (Flemish People of partits City of its empower Ghent wants to of the city strategy, technologies to giving them access by citizens and control. own they The can a to usecitizens give single profile page they (consult interactions manage their administrative sign children up for their appointment schedule, aid applica- of the status track sports activities, GHENT, CREATING NEW CREATING GHENT, THE CITY BETWEEN CONNECTIONS INHABITANTS AND ITS ,” were delivered. were ,” Citizen Citizen Sensing Toolkit Several concrete outcomes, including the outcomes, concrete Several “ “Personal data and cities” — An overview of initiatives

around the world P TRENTO: USING SMARTPHONES AS AS USING SMARTPHONES TRENTO: TOOLS DEMOCRATIC a began Lab Mobile Territorial Italia’s Telecom in collaboration in 2012, Self Data initiative - La a researcher at SKIL Vescovi, with Michele Innovation); Knowledge and (Semantic boratory the Bruno Kessler Foundation; and Telefonica around the centralized Efforts been have I+D. enabling users a tool , Data Store My creation of The and share their personal data. control to a create aims to (MTL) Lab Territorial Mobile Ita- Trento, lab at the heart real world of “living” One of its specific aimsly. isto harness mobile and make track capabilities to phone detection beha- and lifestyle spending families’ sense of indicating mood and stress plus markers viors, patterns. and sha- the control for Data Store is a tool My from mobile personal data collected ring of The sampling apps. via experience phones and participants63 with 15 tested over was project weeks; each received an Android smartphone that ag- software mini-detection with equipped from the mobile phone data detected gregates The data is account. Data Store My on the user’s future exploitation. for stored securely there Firstly, sources. from three The data come mo- from the extracted automatically are those call logs and SMS messages and bile devices’ - Sharing Cities Sharing The Sharing Cities program began in began in program Cities The Sharing 100 European brings together It 2016. Bor London, including communities, Mi- and Warsaw, Burgas, Lisbon, deaux, ground to create a shared testing lan, for smart ci- and a shared methodology into citizens integrates that ties design the process. to is objectives Cities’ Sharing of One which create Urban Sharing Platforms, a from data to manage users enable will analytics, (sensors, sources wide range of principles common of set a using etc.) - Lon leverages It and open technologies. (DataS- analytics data in expertise don’s with application in work Milan’s tore), with and (APIs) interfaces programming and Lisbon’s experience data use, public and data gateways sensor data analyzing this goal. to achieve , in partnership , The first - Pro Action & Resources (Waste UK WRAP with a data trust model of the impact tracked gram), abi- stakeholders’ improving by waste on food in waste measure food and to monitor to lity chains. supply in partnership pilot was conducted The second with WILDLABS Tech Hub. The collaborators spent the first three monthsof 2019 exploring to be used trust model could whether a data - the efforts develo the numerous scaffold of re-users working and data users, vendors, pers, the trade around wildlife illegal tackle the to world. each cases, use two explored pilot third The the in applying the data trust model explicitly and dealt with mobility, One the city. of context avai- maximize could using a data trust how more attractive, and promote data lable parking The other transport. less polluting means of looked at ways to improve energy efficiency in one of the city’s blocks of social housing flats, a and control monitor installing sensors to by heating system. collective modernized tion pilots since 2016. 2016. since tion pilots ners-Lee ners-Lee and artificial intelligence expert Nigel data open value of the showcase to Shadbolt, data using of ways innovative for and advocate It level. at the global change inspire positive to independent organi- non-partisan, is a non-profit, as be presented feasibly data trust could A zation. use a sign that data and their measure, a safety re- holders and organizations between transfers Using securely. be handled will them quiring opportunities, economic new create them would - commu empower and greatly help with research, nities. The definition given by theODI, however, - inde structure that allows legal “a to is limited third a trusted data by pendent management of party.” Sean on the research of The ODI relies heavily who definesMcDonald, a data trust as ecosystem having five dimensions: a a bene- creator/owner, aficiary, trusted third an party, asset, and a goal. party third trusted a to asset an gives owner An to ensure that it fulfills a useful functionfor the data McDonald, to according However, beneficiary. own their carry they — trusts are not a panacea tax foster to including their potential risks, set of divert data may that actors the possibility fraud, responsi- waive ends or even commercial serve to The data trust governance data privacy. for bility - and legisla model cannot do without a political supporting system tive it. - data trust implementa The ODI has set up three LONDON: CREATING NEWER, MORE NEWER, CREATING LONDON: COLLECTIVE TRUSTWORTHY STRUCTURES the Cities is also a member of London of The City exploring and has been for Digital Rights, Coalition In 2010, now. years several municipal data use for data and which stores it launched the Datastore, use in a to anyone for accessible it easily makes joined the Sha- the city In 2016, ways. of variety - develop the which promotes program, Cities ring Smartment of in engagement Cities and citizen Along with the Open Data Ins- their development. a clarifying what towards are working they titute, into might be integrated it data trust is and how terrain the it making — project Cities Sharing the trust exploration. future data for Insti- Development Overseas The London-based - Tim Ber in 2012 by (ODI) was co-founded tute — was put into question. Are they really suited to to suited really Are they question. put into was — can and further, in the debate, mediator the role of trustworthy?be Strictly really size this of project a ideal an is not really project Toronto the speaking, but it is extremely Self Data at work, of example partnerships the potential of terms in instructive can and and the role(s) that in place, can put a city in the process. citizens by should be taken - Lab’s legitimacy — it is backed by Google, the epi- Google, by it is backed — legitimacy Lab’s all ethically-questionable data use after of tome After launching the initiative and sparking the and sparking launching the initiative After SideWalk on data management, resulting debate Mistrust of Google has led residents and city and city Google has led residents Mistrust of the giant in the question the role of to actors be data really Would data governance. project’s Toronto The with Google at the helm? “shared” and sug- it, doubted Commerce Area Chamber of manager Trust Data Civic that the role of gested its brand is because library, the city to be given and it has expertise with ar- “neutral,” it is trusted, information and policy, management data chiving, management issues. In 2018, SideWalkLab suggested establishing a suggested SideWalkLab In 2018, system a data management — Civic Data Trust - data mana independent third-party that provides ano- maintenance, including collection, gement, complement To and sharing oversight. nymization, Assessments (RDIA, Data Impact Responsible this, will be triggered and analysis) in-depth review or use of collection the for a proposal whenever including details on the urban data is presented, any data sources, its required objective, proposal’s communities, or individuals on impact potential analysis. plus a risk-benefit vest, vest, which data will be identified, and whether with associated can be individually individuals those data. “Personal data and cities” — An overview of initiatives

around the world P - - penses), challenges users to lower their energy energy their lower challenges users to penses), analyses comparative generates consumption, data ex and facilitates with other users data, augment the Its activities will eventually port. territorial for maps needed energy of contents energy planning, help to define and compare for database a as serve profiles, energy baseline and address energy identify help to research, etc. poverty, being led by is another initiative Captothèque sensing and Its citizen Grenoble. of the city participation a set of inhabitants gives scheme smartphone, applications, (micro-sensors, tools air can collect so they etc.) website, dedicated Out in the field in Grenoble, a is — Turbine.coop Péniche La as Scop La known formerly — collaborative co-create can people where space so- and a Infolab, digital data mediation a tools, It is a pace accelerator. project cial innovation charge of and users can take where citizens - data challenges and collabo their digital and that contribute digital solutions invent ratively to transitions. In 2015, La Turbine.coop held workshops Energy MesInfos Fing co-hosted and projects along with its participation in several personal data, over individual control exploring Vivacité) including the MétroEnergies (formerly ma- now platform, MétroEnergies The project. tai- generates Grenoble, of the City naged by visualizations depicting individual energy lored ex and associated consumption data (energy THE CITY OF NANTES, GREATER GREATER NANTES, OF THE CITY FRENCH ROCHELLE: AND LA LYON, SELF OF THE FOREFRONT AT CITIES DATA effortsData, Self implement to Frances’ to separately spread have Fing, spearheaded by have We years. the past few cities over several cities French three with directly working been and Greater Rochelle La Métropole, Nantes — of implementation and design the on — Lyon The results Cities experiments. Data their Self The ci- chapter. in the following are presented and Grenoble are also engaged Rennes ties of present which we in data sharing initiatives, here. Grenoble Grenoble-Alpes Métropole is in the process of of process Grenoble-Alpes Métropole is in the per- and shares it manages how reconsidering March Fing in at conference During a data. sonal project Smartand digital City city’s the 2019, of core outlined the Deslattes manager Laurent which investigation: internal the city’s areas of data do we hold? How are we using and them, ci- place Where do we use them? can we how What are the provisions in this process? tizens citizens, and for data use by that will optimize their privacy? and respect , funded by EIT EIT by funded , CaPe and manage their data [ie: MyData] as well as MyData] as well their data [ie: and manage and used.” collected it is how influence Via the “Virium Helsinki Helsinki Forum,” has begun to reflect on waysto effectively imple- has The city Data model. ment the MyData/Self - perso of the sources mapping begun already for concepts and developing nal data it holds reuse and retrieve enable individuals to ways to report at that shows collection data The them. city Helsinki 800 approximately the of 209 least personal data. contain systems computer a My- become to working is currently The city demonstrations It is developing Data operator. manage it might be possible to how illustrate to me- via connected consumption energy citizens’ ter data; while its project mobility making towards working is Digital, portabledata partiesthird that so create can individuals. useful to that are services their personal data,” especially by encouraging encouraging by especially data,” their personal The research programs. launch pilot others to My- the for Helsinki in annually meets community Data conference. The Finnish headquarters- is charged with organi zing the annual conference in to Helsinki, create visibility discussion and increase the for a space Each hub is built activities. concrete local hubs’ of ; the MyData Declaration to according their - mis sion is to form a definelocal acommunity, com- im- project on collectively work and goal, mon the MyData Fing is responsible for plementation. working the French community hub and France on the topic. cities of in the rapidly hubs are growing Local - Zu London, Geneva, Brussels, Barcelona, Atlanta, and rich, Sydney; and Brazil, nationally in Austria, Cameroon, Denmark, Greece, Hungary, Japan, the - Swe Kingdom, United the Scotland, Netherlands, Valley. and Silicon Slovenia, den, local public for resource is a precious The network sphere of MyData’s reasons. of number a for actors influence is gradually expanding (particularly at capitalizing on the efforts by the European level) whose Ci- such as Eurocities’, networks existing of - Pu its activities. of a driver Data theme is tizen Data Principles iits Citizen blished in March 2019, responsibility the have “governments that state to access can have and must ensure that citizens HELSINKI: THE CRADLE OF MYDATA CRADLE OF THE HELSINKI: Finland (especially Helsinki) has been the cradle as MyData synonymously known — Self Data of when the MyData Global network 2010, since — 1, July On member. founding a is Fing created. was the presidency over took when the country 2019, men- makes their agenda the European Union, of - the develop accelerate to their intention tion of during data economy a human-centered ment of their presidency. the 6 months of We are not featuring Helsinki here to highlight Rather, personal data. approach to another city’s what is now to attention your draw to seek we em- wishing to city any for an indispensable tool implementation: membership in on Self Data bark is (whose epicenter the MyData Global network in Its Helsinki). members are making a concerted data economy the personal effort recalibrate to In October individuals. of in favor more equitably 2018, the network was officiallyformalized as a nonprofit. a wide range of brings together MyData Global - com private academics, activists, entrepreneurs, - cen Its aim is to organizations. and public panies, tralize emerging reflections and increase enrich so, and in doing their impact at the local level, The and experience. capabilities, perspectives, impro- individuals by “empower to seeks network regarding self-determination ving their right to Other sources of personal data were shared on shared on data were personal of Other sources dedicated and many platform, the MyData Store to that enabled citizens developed apps were partnership a strategic For example, reuse them. Trento’s chain enabled distribution with the Coop data and their consumption retrieve residents to data) with their mobility reuse it (in combination manage their apps designed to on third-party shopping routines. from scans of Bluetooth devices and GPS/WiFi, and GPS/WiFi, devices Bluetooth of from scans in- status and device events, activity multimedia with are equipped the devices Secondly, formation. and air quality detect that periodically sensors humidity, data (temperature, meteorological basic Final- Store. the to transmitted then is which etc.), quality, sleep stress, mood, some data on daily ly, - expe an using collected are expenses daily and The fin- via mobile app. conducted riential survey dings revealed that close to 50% of participants what awareness of greater gained a said that they and what their are used, they how personal data is, be. might potential “Personal data and cities” — An overview of initiatives

around the world P Project RUDI Project (RUDI) Interface Data Urban Rennes The support with the initiated the of project, Rennes of and the city European Union with its Metropolitan (in conjunction - will launch in Sep Data Service), Public an urban It will develop 2019. of tember and to access facilitate to data interface data it contains, the understanding of the in innovation stimulate to principally data “social as a kind of Operating region. social enterprises, citizens, for network” a de- as it will operate and businesses, new for ground proving and velopment access advantage of that take services - vo data furnished and to these data to the In inhabitants. the city’s by luntarily are at the citizens Self Data, true spirit of should they — heart the undertaking of personalized access be able to eventually manage flows, data anonymized also and share their data with to their consent and third parties or entities), (services that reuse their services to gain access data. -

The The City of Nantes, La Rochelle, Lyon Greater and With its MyToutatice project, an extension of ENT ENT of extension an project, MyToutatice With its students’ make to intends the academy Toutatice, MyToutatice read. easier to much school records - in collabora designed platform cloud is personal that can “digital binder” a — tion with CozyCloud data that and teachers’ learners’ store and collect - or tea their schooling end of the will endure until are pauses along the if there even ching career, their and exploit control users to It allows way. - their pri of respectful while being personal data, high school stu- involving An experiment vacy. soon. is expected dents and teachers tive: launch experiments that to develop their develop that to experiments launch tive: implementation Data Self what of understanding of the City Rochelle, La their regions. implies for Data Self launching are Lyon Greater and Nantes, the on sustainable mobility, focusing experiments respectively. transition and social welfare, energy This is the first time that local actors public have the Self Data as leaders of positioned themselves details their actions. chapter The next revolution! Self of pioneers become cities have French Three with Fing closely working been have They Data. an ambitious objec and its partners achieve to On a different tack, the Academy of Rennes has Rennes of Academy the tack, On a different on implementing Self Data prin- focused been is The reasoning ciples in the education sector. paths are fragmented teachers’ and this: students’ platforms educational multiple of the use through Pearltrees, Moodle, such as pronote, software (eg: PMB, and POD; news reports shown in class; di- gital textbooks, encyclopedias and dictionaries; digital BRNE; bank resource the national France’s education portal eduthèque; the national - extra curricular education pathway platform France’s Folios; online curriculum platform homework Labomep; websites like Homework done; peda- maga- digital Toutapad; as such platforms gogical lear- and teaching Satchel Madmagz; creator zine ning tools; online digital certification program PIX; mapmaking platform Cartoun; libra- (school, and workspaces etc.) VIA, M@gistère, AALN, change mention when they not to etc.), home, ries, aca- complete and full a which renders — schools generate. impossible to virtually record demic Rennes, France Rennes, quality data that will enrich the city’s existing existing city’s will enrich the data that quality approach Data Science Their Citizen indicators. and Barcelona by developed those to is similar - is consi the city Today, example. for Amsterdam, its regional into Self Data logic dering integrating so that individuals can strategy, data warehouse themselves. and share their personal data control SELF DATA DIY — CREATE A LOCALIZED, RELEVANT SELF DATA INITIATIVE FOR YOUR REGION: THE EXAMPLES OF THE CITY OF NANTES, LA ROCHELLE 03 AND GREATER LYON. Self Data DIY — create a localized, relevant Self Data initiative for your region: the

examples of the City of Nantes, La Rochelle and Greater Lyon. P - (especially (especially , so you are prepared you so , ... reduce my home’s carbon footprint and footprint carbon home’s my reduce ... consumption. energy manage my ...contribute to clean energy production in clean energy ...contribute to neighborhood or city; my ...understand and take charge of my food food ...understand my charge of and take and their impacts; choices » » » » - wel social improve Self Data to - Lyon Greater help me... and to fare, » Self Data FAQ Data the Self consult There questions. participants’ your answer to Pilot Summary Self Data is also the and all the examples) which is full of 4, Chapter over produced have we other (English) content is available under a Everything years. the past 7 ena- license, 3.0 attribution Commons Creative as long wish, you as reuse the info to you bling us as the source. cite you as and La Grand Lyon Métropole, In Nantes conduc the seminars we of each Rochelle, the get a clearer picture of us to helped ted stage in the at every be overcome challenges to process. project Self Data in support the of - Métropole Nantes help me... and to transition, energy » you have drawn up the “guest list” for future future for list” “guest drawn up the have you can open the debate you when workshops, interviews, conduct audience, a wider to meetings....have you you have a list of specific challenges for to; respond Self Data to participants pursue the desire to will have consider and further, Data Self of topic the data and data uses; participants tie Self Data must be able to concerns; local their specific with together participants must come away with a solid participants away must come - Data and its poten Self understanding of tial; » » » » » » You will find a methodology and a setof best seminar in your prepare you help to practices also wish to may You booklet. this 1 of appendix » » » or are working with data — especially personal personal especially — data with or are working support will in associates you These key data. Self your map out you months as the coming Self know them will not of Many Data strategy. Data; it is a complex You subject. will have to and them, invite an orientation day, organize further to then use the opportunity sharpen Data seminar must That Self focus. area of your objectives: several achieve » - (French only). The topic tied together se- tied together The topic (French only). to set up a regional “carbon calculator” that that calculator” “carbon set up a regional to footprint carbon residents’ incorporate could their and under consent their explicit data with control. gravitated initially Lyon Greater though Even the given education as its theme, towards - holds and its poten data the city amount of explore to instead opted but they tial uses, on solida- focus the city’s given social welfare, rity had around its city other questions the veral grasp to ability citizens and its administration in fact, had, The city their rights. and exercise a di- from the terrain explore to begun already using France by example for gital perspective, parents and between as the interface Connect childcare services. public litt a was situation the Nantes, of city the for As le different. The people we worked with were with were worked we The people le different. department systems neither information em- - innova the city’s for work nor did they ployees came from its business they — tion department including the DGTEESU (Directorate divisions, and Environment, Transition, Energy General for theme was The social welfare Urban Services). a great fit, aswere itsfocal areas: energy and food. a core identify time to Then it’s theme? your Got the field, who either know local actors group of - UNDERSTANDING THE THE UNDERSTANDING ASSOCIATED STAKES DATA, WITH SELF AND AN CHOOSING PROJECT APPROPRIATE The first stepto launch Self Data isto rallyyour data colleagues, year: the coming for accomplices business representatives, civil society holders, them to will need You etc. universities, clusters, majo- a that scenario experimental an build help them will adhere to. of rity nor will area, every cover will not be able to You single sec from every actors unite to manage you that theme and topic a find to need will you so tor, the future: which minds into your Project sticks. internal motivate to themes are the most likely municipal your Which of actors? and external activities would most benefit from taking aSelf the example, for Rochelle, Data approach? In La as their theme settled on sustainable mobility city a mo- is already the city First, reasons. several for and environment its energy Second, pioneer. bility Then, mobility. pursue to keen was ADEME agency Fabrique accelerator with the mobility a meeting a creating considering who were Mobilités, des prompted Data, on Self based account” “mobility wanted Rochelle La finally, And forces. of joining a phase 0 : become aware of Self Data and aware of phase 0 : become be appropriate would choose a challenge that needs; their city’s to personal the of perimeter the define : 1 phase be shared; data that could use cases and their asso- phase 2 : create models; governance ciated phase 3 : finalize a road mapto implement the in scenarios experimental more one or year. coming » » » » What about your city joining other Self Data Ci- joining other city your What about experiment, on a Self Data embarking ties? Before you will help steps preliminary a few following your in dynamic the necessary create not only more clearly will also be able to you — region during encounter will you what of some foresee these each of through went We implementation. phases with all three cities; the results and me- help to are intended kit contains thodologies this do the same. you - wor we 2019, 2018 and July September Between help them : cities to with three ked » » » » GREATER LYON. GREATER ROCHELLE AND ROCHELLE OF NANTES, LA NANTES, LA OF OF THE CITY THE OF CITY THE EXAMPLES FOR YOUR REGION: YOUR FOR DATA INITIATIVE INITIATIVE DATA RELEVANT SELF SELF RELEVANT A LOCALIZED, LOCALIZED, A DIY — CREATE — CREATE DIY SELF DATA DATA SELF Self Data DIY — create a localized, relevant Self Data initiative for your region: the

examples of the City of Nantes, La Rochelle and Greater Lyon. P itself overcomes at least one of your inhabi- your one of at least itself overcomes 3 and 4 describe Appendices challenges. tants’ and organize to use can you methodology the workshops. host these Lyon, Greater Métropole, with Nantes Our work — cases use a dozen yielded Rochelle La and details about the data which includes each of target audiences and features plus their utilized, and the governance as a use scenario as well — In support be used to models that might them. present a brief synopsis we pages, the following each. of POTENTIAL USE POTENTIAL AND CASES MODELS OF RELEVANT GOVERNANCE the data on a data- visualizing Gathering and can you where position a in you puts also sheet and use services, uses, imagine new to begin the data. cases for is to process the project The third stage of cases and their rele- use dream up those new civic models (personal cloud, vant governance metropolitan portability, right to citizen’s trust, you and — work a lot of It’s etc.). data platform, worth of workshops’ of a couple have will only time to dedicate to the task. During the service up with at least a dozen will come you first based on the then choose a few and concepts, datasheets, which you then flesh out into use imagina- your let is not the time to This cases. architecture, technology, by tion be constrained those will be All of or data sharing concerns. during workshop, dealt with during the second approach an overall will develop you which each for and governance implementation to yourself familiarize to will need You use case. (see exist options that “on-the-shelf” the with hy- an alternative, create this kit), 1 of Chapter model that can supportbridized a use case that - these are perso of Two-thirds transition. energy (age, data profile include These character. in nal etc.), composition, household address, name, - data (subscrip consumption data, geolocation (spe- data preferences energy), food, fuel, tions, cific itineraries,food, etc.), and household cha- data that are the type of are racteristics.These which solar determining useful when equally or to entitled to, is someone panel subsidies buy things to a list of make to enable people products seasonal local, offer from sellers who (budget, and preferences that suit their needs etc.). tastes, an with up come to not is datablitz a of aim The wish to you the personal data list of exhaustive part of underway, Once share with individuals. care- will be to process experimentation your - informa document the data in each holder’ fully are These workshops (IS) anyway. tion system about horizons your expand to an opportunity be shared with people or might what could — challenges existing of from the perspective disposal. your at systems not the information types new discover might be surprised to You on not were that holders data new and data of previously. radar your data that perhaps did not come immediately to to immediately come not did perhaps that data un- and other sectors data from especially mind, that own your than headings topic der different Self Data of within the context sense still make implementation. From your workshop findings, you can create a the results so that containing shared spreadsheet partici workshop the - but especially — anyone created have We it. to contribute can can — pants - (French lan mapping tool an online spreadsheet visualizations sheet” “data generates that guage) It can be further en- purposes. educational for a questionnaire is completed. riched after data type (per- topic, by your search can filter You Each data sheet or keyword. sonal/non-personal), the holder(s) the data, title, presents information mo- of types 60 over are There platform. the and the to data relevant and 100 types of data, bility - this to data for Which are the most relevant on personal data, focus your pic? (maintain open and repositories data at look also but which might be useful). data facili- already Who holds these data? Do they download)? API; direct (via access tate What are some use- reuse ways to ful these or combine data? » » » Step two of the Self Data adventure: identify identify adventure: Data Self the of two Step - eventual personal data that will the relevant This happens du- be shared with individuals. ly “data hunting a or “datablitz” call a ring what we de- have you Based on the challenges workshop.” questions must subsets of three address, cided to be answered: » » » 2 details the Appendix methodology. datablitz are These workshops oppor- useful extremely and explore tunities to identify systematically personal for sources DEFINING THE DATA THE DEFINING DATA PERIMETER ...manage my mobility budget; ...manage mobility my op- rethinking the mobility ...contribute to in the region; tions on offer the pleasure: reduce with utility ….combine and comings daily my of carbon footprint cultural knowledge. and enrich my goings, ...calculate and reduce my mobility carbon mobility ...calculate my and reduce footprint; ...easily take part in the city’s public sports, sports, public part take ...easily in the city’s and social activities; cultural, and per- to, talk to the right people ...identify tasks. necessary form ...understand my entitlements, streamline my my streamline ...understand entitlements, my responsibilities; tasks and » » » » » » » » » » » » sustai- more better, Self Data for - La Rochelle help me... and to nable mobility, » » Self Data DIY — create a localized, relevant Self Data initiative for your region: the

examples of the City of Nantes, La Rochelle and Greater Lyon. P utors Support staff . . . sonal cloud” and “third party service” functions are functions service” party “third and cloud” sonal is social services data with sharing of The siloed. trust Users’ that exchange. as is securing required measures is capital, data security in the service’s best would service this type of this reason, and for han- that already actor a public by be developed administra- (the City exchange dles this type of etc.). Services, Family tion, e personal cloud office aation Mediation Data recovery assistance recovery Data Mediation amily ervices processing algorithm elcos Data sharing y ocial y tatus anks this third party service is actually intended to enable to intended actually is service third party this so users can assess their benefits visualization, data indivi- built for is shared, visualization The status. a major who play the social workers duals and for and then the evaluation, data for role in gathering case sheet, summary status the generate it to using progress report, and a list of the tasks beneficiary’s - “per if the cannot operate The service and priorities. charities du oeur programs ocal support ocal eg estaurants eg Creation and Creation of folloup report status Energy companies rance, rance, ocial ecurity rganizations ness case file) ness case over-indebted eg anue de eg ocial workers du edecins onde, amily ervices, etc. GOVERNANCE MODEL: THE PERSONAL CLOUD THE PERSONAL MODEL: GOVERNANCE be- services social for is destined largely This tool neficiarieswho are already seeing a socialworker. alignswell withSocial the Benefits“My Dashboard” personal ascloud theconfiguration, personal cloud and supportsinteroperability data source multiple where users “home” in a digital individual storage data. their personal and administer store are able to but its operation, to prerequisite This is a necessary CONCEPT AND USE CASE AND CONCEPT 1 MA

GREATER LYON GREATER SELF DATA AND SELF DATA BENEFITS BENEFITS SOCIALE - SOCIALE MY SOCIAL SOCIAL MY SITUATION SITUATION SOCIAL WELFARE - WELFARE SOCIAL DASHBOARD Self Data DIY — create a localized, relevant Self Data initiative for your region: the

examples of the City of Nantes, La Rochelle and Greater Lyon. P

...... ity apps sponsored ights attribution criteria andlords provided by the same trusted third party orga- party third trusted the same by provided need. all users would be likely would nization, service energy energy providers providers ousehold ectors companies, etc. of the individual of office Employment E EE E office euired public euired data aation Data shared with specific holders with the informed and explicit consent consent and explicit the informed with with specific holders Data shared anual entry of further data changes to my situation, etc. situation, to my changes data further of anual entry holders data various the among coherence of verification amily llowance SAED SOCIAL FILE ocial ecurity e temporary password) or permanently. In line with In permanently. or password) temporary the individual model, Medical Records the Shared - (or other data holders share data with can only reuse and cannot etc.) workers, social ganizations, them given via the third-party However, services. Direct ways BenefitsMy will be using individuals’ pur- A unnecessary. reuse seems third party data, and bundled with the platform pose built service, - anks Data sharing Data I give my informed consent informed my I give sharing the secure to personal data my of yment yment benefits nemplo My personal data is shared with me personal data is shared My upport workers arming services retirement ocial workers du edecins onde, amily ervices, etc. Online mediation by a by Online mediation based on profile worker social odas GOVERNANCE MODEL: THE TRUSTED THIRD PARTY PLATFORM PARTY THIRD TRUSTED THE MODEL: GOVERNANCE to securely transmit data must be able to form with a (eg: whether temporarily social workers, “My “My Direct isBenefits” anapplication thatwould Social Folder” “Shared France’s into be integrated aggregate to individuals allows which platform, sharing. manage and space secure a in data their third a trusted by must be provided The service The plat services). Allowance Family (eg: party CONCEPT AND USE CASE AND CONCEPT 2

GREATER LYON GREATER SELF DATA AND AND SELF DATA BENEFITS MY DIRECT DIRECT MY MES AIDES MES AIDES SOCIAL WELFARE - WELFARE SOCIAL DIRECTES - DIRECTES Self Data DIY — create a localized, relevant Self Data initiative for your region: the

examples of the City of Nantes, La Rochelle and Greater Lyon. P ...... rganization museum eg office) ticketing ublic transport facilitate families’ access to cultural offerings cultural offerings to access families’ facilitate for outings, for preparations and streamline a possibility. is also — example ultural program and pricing niversity euired open data Prove a right Prove Taxation Office Taxation anual data local my entry local my grocer, etc. market, SOTIA LON Sharing my personal data Sharing my Employment services Employment was made to share less external data with Sortiawith data external less share to made was preferences their enter the users to ask and Lyon vacuum in a can operate The service and interests. or it can their rights, of users inform and simply - share some data with a ticke users to also allow their eligibility prove to example, for ting agent, share the without having to rates discounted for Creating a pro- of their entirety data. confidential may so they — childminders for interface fessional oi Data sharing ity Consent to Consent sharing my sharing my and consent and consent hildminders follow-up via follow-up personal data (authentication (authentication with Sortia Lyon with Sortia Lyon France Connect). France The direct transfer model applies if Sortia Lyon can Sortiaif applies model transfer direct The Lyon data sources. of number with a restricted operate and are public sources their that most of Given national social services a part France’s of already use could Sortia Lyon FranceConnect, platform user authentication streamline its those ties to - Trans “Direct The process. follow-up and consent a the creation of foster not really model does fer” so the choice perennial 360° data overview, truly GOVERNANCE MODEL: DIRECT DATA TRANSFER DATA MODEL: DIRECT GOVERNANCE CONCEPT AND USE CASE AND CONCEPT 3 LYON SORTIA SORTIA GREATER LYON GREATER SELF DATA AND AND SELF DATA SOCIAL WELFARE - WELFARE SOCIAL Self Data DIY — create a localized, relevant Self Data initiative for your region: the

examples of the City of Nantes, La Rochelle and Greater Lyon. P . . . Waze 1 associate 1 vote 1 1 associate ther associates ther local collectives, ect. operators, transport a collective to join an SCIC are numerous: to to numerous: are SCIC an join to a collective transportation public offers,change harmonize challenges, (via way positive in a habits citizens’ free — change encourage to system or a bonus or otherwise act example), for storage, bicycle health. public of in the interests anks elcos ssociates y obility udget obility y beneficiaries individuals SCIC Cooperative Association of Collective Interest) Collective of Association SCIC Cooperative oogle etc. calendar, . . . y obility udget udget obility y creators etc. employees, Quantified apps elf come this obstacle, the solution for My Mobility Mobility My for the solution obstacle, this come - a coopera — an SCIC create be to Budget could and orga- — interest collective association of tive be greater there would That way, a collective. nize critical the service, develop to means with which and the service reached be more easily mass could the of member any by used be could developed group making things like for especially collective, The reasons for purchases. (and thus discounted) Personal data sharing/consent to share my data with the platform with data my to share Personal data sharing/consent Weather information utomakers the service Data reuired by reuired Data y obility udget udget obility y group comparisons, tutoconso purchases, challenges, etc. information, ublic transport operators ir uality uality ir abs, etc. lume The main problem with using a data cooperative a data cooperative problem with using The main to develop this kind of service is how difficult it can be to get people involved; there has to be a to individuals on the partstrong interest many of because this, a structure like building commence governance. to be devoted the time that must of members the critical mass among And achieving service digital high quality a produce to required - over To might be tricky. anonymity and preserve GOVERNANCE MODEL: DATA COOPERATIVE MODEL: DATA GOVERNANCE CONCEPT AND USE CASE AND CONCEPT 1 - MY - MY MON ROCHELLE MOBILITY - LA - LA MOBILITY BUDGET BUDGET BUDGET SUSTAINABLE SUSTAINABLE SELF DATA AND SELF DATA MOBILITÉ MOBILITÉ MOBILITY MOBILITY Self Data DIY — create a localized, relevant Self Data initiative for your region: the

examples of the City of Nantes, La Rochelle and Greater Lyon. P ...... Waze arbon reference deme data and 2) data sharing from personal cloud to lo- to personal cloud sharing from and 2) data example. for organizations, cal public anks epersonal cloud vailable public transport elcos euired open data I share my personal data on my personal cloud. personal data on my my I share processing nsurers individual personal cloud oach processing Quantified Self Quantified apps taneously.To fully articulate the collective nature nature articulate the collective fully taneously.To enable colleagues, designed to — the service of coordinate to and families roommates students, challenges common to responses collaborative modify such as to requests, collective and make orga- the majority, schedules in line with public 1) data will require — and so on rideshares, nize personal clouds, users’ Coach sharing among CO2 processing sharing individual personal cloud processing utomakers incentive rganization, eg rganization, public actor, etc. - etc. public actor, emonstrate need emonstrate individual personal cloud and rights eg ta eg and rights university, employer, employer, university, ublic transport operators “CO2 “CO2 Coach” might be the first in a wide ge- data used to the personal lot of range A services. of clouds personal on people’s the service nerate mobility-re- other types of by can also be reused public tools, comparison (insurance services lated to have not Users would etc.). transport surveys, importing of data multiple their the task perform simul- projects participatetimes to in several GOVERNANCE MODEL: PERSONAL CLOUD MODEL: PERSONAL GOVERNANCE CONCEPT AND USE CASE AND CONCEPT 2 CO2 ROCHELLE COACH MOBILITY - LA - LA MOBILITY SUSTAINABLE SUSTAINABLE SELF DATA AND AND SELF DATA Self Data DIY — create a localized, relevant Self Data initiative for your region: the

examples of the City of Nantes, La Rochelle and Greater Lyon. P . . . authority delegates overnance Civil society ther third- ther services party Public service developer area developer Public transport Trusteessteards Data transmitted via Data transmitted ocal public ocal transportation delegates Employer offered to individuals to access the services de- the services access to individuals to offered and area) developer the (via reusers by veloped cam- collection data Trust’s the to contribute de- campaign).For transportpaigns (eg: survey in this model is that there the interest velopers, individuals who group of large is a relatively and the provision be using their services would datasets, private) (and eventually rich public of personal datasets. albeit fictitious data obility platform Open data business data etc business data Open data transport. data.gouv.fr alendar Author of a call of Author sharing data for olice Shared obilities Shared - all for data data for - all data sharingcitizen portability campaigns space platform - visualization and for debate oogle maps Waze governance rules, and a shared architecture with architecture shared a and rules, governance the community those with whom actors: mobility delegates) Transport links (Public has contractual who are impacted actors territorial but also any lo- hospitals, changes (universities, mobility by at society civil plus businesses) shopkeepers, cal We jury). or citizens’ enterprise large (via social and perso- data transfer that direct hypothesize be the means options would nal cloud sharing Author of a call for data sharing data for a call of Author algorithm processing 2 pen ata Direct transfer Direct roup of individual citizens of roup Personal data sharing by direct transfer (by informed and explicit individual consent) or via my personal cloud personal via my or individual consent) and explicit informed (by transfer direct Personal data sharing by e ersonal cloud O ublic transport bus delegate Sharing “Shared Mobilities” is not really a service, it’s more it’s a service, is not really Mobilities” “Shared data calls for to dedicated space a communal of - por citizen and facilitation) (and sharing sharing It is debate. for plus a space campaigns, tability the public management model: a public by backed that efforts is the guarantor are conducted actor - com and has the mobility in the general interest Authority). transit (Public ensure this to petence establish shared data must nevertheless Trust The GOVERNANCE MODEL: CIVIC DATA TRUST DATA MODEL: CIVIC GOVERNANCE CONCEPT AND USE CASE AND CONCEPT 3

ROCHELLE

MOBILITY - LA - LA MOBILITY SUSTAINABLE SUSTAINABLE SELF DATA AND AND SELF DATA MOBILITY - SHARED - SHARED MOBILITÉS MOBILITÉS PARTAGÉES PARTAGÉES Self Data DIY — create a localized, relevant Self Data initiative for your region: the

examples of the City of Nantes, La Rochelle and Greater Lyon. P . . . Waze service’s service’s specifications and either established with charter signed a contract or a common third which uses outlining framework A them. also been data has parties citizens’ of make can not use the personal data can the city created: In data. aggregated only on the platform, stored short go, uses as far as collective the long term, could via the platform conducted “campaigns” transit a public to “Contribute (eg: be effective data”). your with survey anks ity eg survey eg ity cultural for access programs etc. improvement, . . . elcos ity-developed, ity-developed, bundled application Aggregated data ity-developed, ity-developed, bundled application Data sharing oogle etc. calendar, eisure activities, eisure of points tourist interest e Data Open latform furnished latform the it b visualization access and consent management) Quantified Self Quantified apps - 4 che “Par install to individual decides When an ser- third-party several is one of which — mins” the on stored data personal the uses that vices the a list of generates service the — platform city - provi must share with service data the individual at data use is revocable personal to Consent ders. effortan and has execute, to easy is and time, any esta- carefully to individuals allow made to been certifies city The share. to wish they data the blish the validated have third parties they trusted after Data sharing utomakers other services other services ar chemins ublic transport operators “Par 4 Chemins” (Roundabout) is a third party ser- party is a third (Roundabout) 4 Chemins” “Par the city. by provided on the platform built vice their retrieve to citizens enables platform The city them securely. store data and It also has : pre-bundled services; developed, city 1) a set of city the by certified services third-party of list a 2) area); developers (APIs, granted. chart3) a management consents of CONCEPT AND USE CASE AND CONCEPT 4

PAR 4 PAR ROCHELLE

MOBILITY - LA - LA MOBILITY SUSTAINABLE SUSTAINABLE SELF DATA AND AND SELF DATA CHEMINS - CHEMINS ROUNDABOUT Self Data DIY — create a localized, relevant Self Data initiative for your region: the

examples of the City of Nantes, La Rochelle and Greater Lyon. P CCAS Tenant Tenant Energy Energy Landlords companies Collective overnance associations . . . for example, strengthen the power of tenants’ tenants’ of the power strengthen example, for grasp of a better giving them by associations an appro- Finally, consumption. their energy social public model should also promote priate en- combat to such as those that seek policies, poverty. ergy latform Energy ata Energy anks Anonymization results of alendar emy personal cloud aation Office processing algorithm I share my personal data via my personal cloud via my personal data my I share - the com that includes joint syndicate) enterprise, - asso (tenants stakeholders relevant and munity an ensure to be would aim Its etc.). CCAS, ciations, and build a framework data of open and fair use roles. the lines between trust without blurring of should also the service of potential The collective users for platform a offers it be overlooked: not It would, connections. and make obtain advice to y mart y ome Linking for local energy production local energy for Linking andlord roup of citizens of roup deme carbon reference data . . . ower companies euired open data euired My My Smart Home is a personal cloud third perso- party nature, their individualized Despite service. collective for great potential also show nal clouds distorting without openness greater foster To use. establishing a their data, over control individuals’ by be steered It would is an option. Trust Data Civic governance mixed using a community collective a public local group, interest public structure (eg: GOVERNANCE MODEL: PERSONAL CLOUD MODEL: PERSONAL GOVERNANCE CONCEPT AND USE CASE AND CONCEPT 1 - NANTES HOME MÉTROPOLE TRANSITION THE ENERGY THE ENERGY SELF DATA AND AND SELF DATA MY SMART SMART MY Self Data DIY — create a localized, relevant Self Data initiative for your region: the

examples of the City of Nantes, La Rochelle and Greater Lyon. P ...... ity of antes of ity bservatory ood antines scolaires with the future Sustainable Food Observatory Food Observatory future Sustainable with the create to Data Self use to city the enable would de- thereby level, at the territorial knowledge riving the maximum benefit from per- citizens’ - ven local encouraging step(s): Next sonal data. charter. groups and sign a common form dors to pen ood acts oyalty card card oyalty numbers eg etc. stocard euired open data data sharing data Aggregate user Aggregate uncheon voucher group voucher uncheon anual entry of anual entry my data other my local grocery, etc local market, anks LA TOE ETE Data sharing the number of data holders required to provide provide to required holders data of the number or if the ser- include banks, increase to the service data individual health incorporate to decides vice “Personal the a transition to etc.), allergies, (food be recommended. probably model would Cloud” with be integrated could case use of type This (PAT, Territoriale d’Alimentation Projet the city’s be could the service and Project) Food Territorial Working citizenry. with its together constructed e upermarkets to o arntership Eg oo ood oo Eg Partnerships with the supermarkets, Go To Good To and goods platform "You suppliers, etc: need X product? . . . it here!" Find my personal data my with la Toque Verte with la Toque Consent to Consent sharing The Toque Verte is a very good example of the of example good very is a Verte Toque The can Nantes of The City model. transfer” “direct a small num- if only even service launch the and such as supermarkets — data holders ber of the share to agree — groups voucher luncheon do not need They clients. hold with their data they the ser- the data for of a 360° overview provide to a model based of so the simplicity work, to vice on Should explicit individual would suffice. likely GOVERNANCE MODEL: DIRECT DATA TRANSFER DATA MODEL: DIRECT GOVERNANCE CONCEPT AND USE CASE AND CONCEPT 2

- NANTES MÉTROPOLE TRANSITION THE ENERGY THE ENERGY

VERTE - VERTE SELF DATA AND AND SELF DATA LA TOQUE TOQUE LA THE GREEN THE GREEN CHEF’S HAT CHEF’S Self Data DIY — create a localized, relevant Self Data initiative for your region: the

examples of the City of Nantes, La Rochelle and Greater Lyon. P 3) a platform: Zeus Techno has an API, which API, an has Techno Zeus platform: a 3) data with other share their lets individuals Techno’s Zeus on based services third-party sta- such as a recharge wish, if they offering rental, vehicle vehicle, an electric tion for etc. . . . » » my private data to data private my Request to transfer to transfer Request Zeus Techno/consent Techno/consent Zeus onnected digital devices services party third ther Consent e Sharing anks otary Energy a) simulate their self-consumption po- their self-consumption a) simulate and data their of basis the on tential and an offer; Techno” “Zeus make consumption, manage their energy b) - and resale data (gene self-production and equipment); Techno Zeus by rated production eus techno eus during install by echno eus by Data generated Data systems installed systems 2) a service that allows individuals to to individuals that allows 2) a service • • » aation office » Data with sharing Zeus Techno platform Techno Zeus Open Data ower companies Energy retrofitting subsidies, nE eighborhood characteristics etc. weather, . . . 1) An energy provider: they install solar pa- they provider: An energy 1) a and offer the network, to users connect nels, subscription plan; » GOVERNANCE MODEL: TRUSTED THIRD PARTY PLATFORM THIRD PARTY TRUSTED MODEL: GOVERNANCE “Zeus Techno” is Techno” “Zeus » CONCEPT AND USE CASE AND CONCEPT 3 ZEUS - NANTES MÉTROPOLE TRANSITION THE ENERGY THE ENERGY TECHNO SELF DATA AND AND SELF DATA Self Data DIY — create a localized, relevant Self Data initiative for your region: the

examples of the City of Nantes, La Rochelle and Greater Lyon. P ocal Energy ocal bservatory antes king care of the electricity network. Calling on Calling network. electricity the of care king would such as FabLabs actors other regional as hardware such construct to it possible make be expected would City The mini-wind turbines. with other projects the initiative integrate to Trust). We In Sun solar cadaster (ex: Sharing of Sharing of agregate data coop member . . . Cooperative e o-op members anks otary Coordination managed by City managed by Coordination e ix e ersonal ersonal clouds aation office - understan analysis: and cost a proper needs to according is appropriate mix energy ding which to members’ profile dataplus gainingneighbo- their and priorities household of picture a fuller the as such characteristics, environmental rhoods’ the manage to needed also is Processing weather. rely ought to WeMix (Smart Grid). network energy critical mass Achieving and open software. on free ta- those to a salary pay it possible to will make - Open data Private data sharing via direct transfer or persona cloud or transfer via direct data sharing Private n Trust Sun e Energy provider reuired for simulation for reuired . . . eighborhood characteristics etc. weather, Energy retrofitting subsidies, nE GOVERNANCE MODEL: DATA CO-OPERATIVE MODEL: DATA GOVERNANCE is central Data processing tion and maintenance. - manages an en that a data cooperative is Mix We co-op When combined, cooperative. sharing ergy local of a critical mass data establishes member build clean collectively them to enabling citizens, - It shares commonali production facilities. energy co-op. an energy and co-op ties with a production upon (and share) decide The members collectively produc infrastructure construction, of the costs CONCEPT AND USE CASE AND CONCEPT 4 - NANTES WEMIX MÉTROPOLE TRANSITION THE ENERGY THE ENERGY SELF DATA AND AND SELF DATA the dashboard to generate an up to the minute case »» Potential testers may be different from those using of your (potential) experiment partners converge What follows are not the final roadmaps the cities SELF DATA AND SOCIAL WELFARE - IN PRACTICE: OUTLINE status summary sheet for the tester. the “My Social Benefits Dashboard.” You may wish to with the Self Data Cities objectives and with the adopted — after the last workshop, a succession of GREATER LYON conduct a separate recruitment process based on AN EXPERIMENTAL interests of the communities you will be serving. iterations both internally and with potential pro- »» Strong emphasis is placed on prompting testers and the findings from the research mentioned above. SCENARIO FOR YOUR For example, you could ask them: “What would ject partners allowed each of them to recalibrate social workers to remember the app, visit the per- you like to learn/achieve/prove via a [theme] Self their objectives, deadlines, timelines, and bud- 1. The “Mon Parcours Social - My Social sonal cloud, and utilize the tool #mediators #MDM »» “Sortia Lyon” could also be developed as a dashboard (Maisons de la Métropole). that gives an overview of the user’s social welfare REGION Data Cities experiment?” “What do you need for gets. Preparing to launch an experiment before Benefits Dashboard” Experiment profile and a list of cultural activities available in this experiment to be approved/your participa- its official announcement takes time, especially Lyon according to their preferences, including the You now have a clearer idea of the kinds of data tion to be approved?” (eg: a clear legal framework for public actors who are constrained by electoral Process summary: preferential rates they are entitled to. They could you can share with people and some concepts that spells out exactly where the data will go, and schedules, so be patient — and keep you eyes pee- 2. The “Sortia Lyon” Experiment »» 50 volunteers retrieve their social welfare/benefits click on an event they like, visit the relevant page, for uses that might emerge from sharing them. when, and how); or “What do we want to avoid at led, because these three cities are nowhere near status data from a personal cloud provided by Grea- and either buy the ticket by furnishing the necessary You have also started to think about governance all costs?” eg: an experiment launch date in three finished with Self Data! ter Lyon. They are all seeking to rejoin the workforce, Aims: proof of their reduced rate entitlement directly from models you might implement, and after the itera- years, disinterested testers, etc. their personal cloud, or buy a ticket at the reduced and each is receiving the RSA (Revenu de Solidari- »» Simplify testers’ access to discounted rates for cultu- tive workshops with your local collaborators, you rate and generate a PDF/data printout that they té Active, a return to work welfare benefit) and so ral outings offered by the city. know which ones you think you should direct your Then it will be time to get together and define would greatly benefit from an overall picture of must present to gain admission to the event. efforts towards. Ideally, you would have used the the experiment as it might exist, including its pro- what is a rapidly and continually evolving situation »» Better grasp the stigmatizing effect of presenting workshops to begin discussing the means you will jected timeline, personal data sources and types, -> Develop the necessary connectors between the reduced rate vouchers and invent ways to avoid it. use to put your experiment in motion. testers, actors, use cases/their development testers’ personal clouds and any data holders — So- cial Services, the city, perhaps the Tax Office, etc. — Process summary: willing to share a copy of testers’ data with them. The time has come to ask yourself a few questions In La Rochelle for example, we worked on two sce- The “Sortia Lyon” service is derived from the “My So- before the next workshop, when everyone will narios: “Shared Mobility” and “My Mobility Coach.” »» Each personal cloud has an app “store” containing cial Benefits Dashboard,” and it uses the same data. It come together to consider one or more experi- Nantes Métropole went with “La Toque Verte,” and a city-developed app called “Ma Situation Sociale can operate as a standalone service based on testers’ mental scenarios. In your view, what are the main envisioned a scenario grouping two use cases (My (My Social Benefits Dashboard),” from where they calendar/budget preferences, or it can work in tandem can get an overall picture of their benefits status, si- objectives you wish to achieve with your Self Data Smart Home and Zeus Techno) together, which with the Dashboard. When the two are deployed to- mulate benefits applications and pre-fill application Cities experiment? Who do you want to test your they dubbed “Hestia & Zeus.” In Greater Lyon, the gether, three additional concerns/recommendations forms with the “Mes Aides (My Benefits)” service (via arise: concepts, and how many testers would you need? chosen scenario was “My Social Journey,” uniting questionnaire), and prepare a completed application Which use cases do you really want to try out? two use cases: “My Direct Benefits” and the “Sortia file for submission to the appropriate department »» During the experiment prep phase: an exploratory Lyon.” (by generating a “batch file” PDF combined with the sociological study will enable you to clarify users’ By establishing these three starting points (objec- data stored in their personal cloud). They share the needs in greater detail. What are the stakes surroun- tives, testers, use cases) in advance, you won’t start In the following pages you will find a summary file with their social worker, who has a restricted ding the social stigma attached to rate reductions? the workshop empty handed. However, you will of each of these scenarios. The methodology that view of the dashboard (“TS interface”). This enables What are the barriers to asking for and obtaining want to further validate your objectives with the enabled them to emerge can be found in Appen- the social worker to get a better grasp of the tester’s them? Who are the target audiences? status, and provide any extra information needed for other workshop participants so that the interests dix 5. and Thalès data to be transferred toTraces. -> Development of data holder connectors to the -> Public empowerment — the hope that offering SELF DATA AND SUSTAINABLE SELF DATA AND THE ENERGY Process summary: personal clouds. dashboard type services, renovation assistance, etc. MOBILITY - LA ROCHELLE »» Testers collectively agree to share their data TRANSITION - NANTES MÉTROPOLE will sufficiently enrich existing services rather than »» 100 testers form the 2020/2021 cohort for the Fa- for research etc. during meetings, debates »» An application developed by a CDA provider is needing to develop a service from scratch. mily Zero Gaspi (Zero Waste) Challenge (face-to-face (using a co-op structure: one person = one vote) available on the cloud’s app “store” that generates coaching, etc.). They are equipped with an applica- -> There is no way to obtain significant findings with a visualization of their carbon footprint and mobi- »» The testers will be able to reuse their personal data 1 - The “Mobilités Partagées - Shared 1. The “Hestia & Zeus” Experiment tion that retrieves their personal food data from at only 50 testers, so the goal is to study individuals’ lity cost/consumption data, offers them persona- in different ways. Step 1 “HESTIA:” generates a data Mobilities” Experiment least three data-holding partners (supermarkets) so motivation for sharing their data. lized advice about how to reduce both (it remains visualization and a series of targeted eco-challenges Aims : they can monitor and reduce the carbon footprint to be seen whether it is financially feasible to de- that result in more personalized advice about ener- created by their food consumption and increase Aims: velop this feature), allows them to share their CO2 gy efficiency measures once achieved. Step 2 “ZEUS:” »» Estimate if access to and reuse of their regular their awareness about food waste and the impact of »» Validate the intuition that shared personal data can results score with the CDA’s carbon aggregator. consumption data and cross-referencing it with predicts the ROI from energy retrofitting work by 2 - The “Mon Coach Mobilité - My Mobility their purchases. practically contribute to city management, common -> A specific app to be developed. Testers to be others allows individuals to reduce their consump- owners who have already completed the work and Coach” Experiment knowledge gathering, etc. overseen and supported (by a dedicated researcher) tion or encourages them to commence energy retro- visualizes the savings to be made by owners with »» A recruitment campaign is underway, conducted by for the duration of the experiment. fitting of their homes. similar profiles to raise awareness about the advan- Nantes Métropole to recruit experiment volunteers. »» Experiment with the factors affecting the individual Aims: tages of retrofitting over time. They must be customers of at least two of the three choice to share personal data to serve the common »» Understand how digital support provisions like Self data holders who have agreed to share data during good. »» Test the Self Data hypothesis: “sharing my data gives Data can be developed to effectively deploy targe- the experiment (ie: they must have a loyalty card). me more control over them.” ted, tailor-made citizen challenges (eg: a “positive -> Development of data sharing connectors. »» Explore the potential of data co-operatives. energy family” challenge), and by association, make 2. The “Toque Verte - Green Chef’s Hat” »» Determine whether it is possible for testers to ob- it possible to reach a wider audience. Experiment »» The testers will then be able to use their personal tain a useful/practical measurement of their carbon data to visualize their food’s carbon footprint; find footprint/mobility budget based on the data shared Process summary: Process summary: Aims: alternatives for certain purchases; contribute to the with them. creation of common knowledge; compare them- »» 50 testers (Greater Lyon (CDA) employees or postal »» 100 testers form the 2020/2021 cohort of Positive »» Help people better understand the carbon footprint »» Observe behavioral changes (and in parallel, ascer- selves with others; and share their experiences. workers; both are categories of civil servants) are Energy Families: half of the panel has already had they create from their food consumption, and give tain whether the use case can be developed further). -> App development — calculation of the carbon given access to “Traces,” an open source app (built their home retrofitted, the other half has not and them a simple and concrete overview of the impact footprint crossed with Open Food Facts data + Ade- by the Fabrique des Mobilités de l’Ademe), which are still living in non-energy efficient homes. A se- that their purchases make. me Base Carbone®. enables them to retrieve their personal geolocation Process summary: cond panel of 1000 testers, who are not necessarily data and view a dashboard summarizing their jour- homeowners, is recruited, but will receive less face- »» Offer individuals the opportunity to choose alterna- »» 50 CDA employee or postal worker testers are each ney data (statistics visualization, CO2 footprint cal- to-face support. tives that are more respectful of the environment. allocated a personal cloud enabling them to ma- culation, etc.) from which they can share these data. » Contribute to the creation of common knowledge — nage their data. »» Members of both panels are allocated a secure » allow people to share some of their (anonymized, »» At least two other types of data are shared personal space allowing them to retrieve their »» Their Yelo data (public transport, public bi- on Traces: CDA Yélo app data (public trans- data from partner holders (Enedis, GRDF, EDF, pseudonymized) data with France’s Sustainable cycles, and self-service cars, etc.) and poten- port, public bicycles, and self-service cars, etc.) Engie, etc.) and to add data concerning the cha- Food Observatory. tially their Thalès (parking use) and SNCF and, if possible, Thalès (parking space data). racteristics of their housing and the dates for/ (train tickets) data are shared with them. -> Connectors are developed to allow testers’ CDA invoicing details from their renovation work. “SHALL WE BEGIN?” — PROTIPS FROM EXPERT 04 SELF DATA ACTORS sonal and user data-holding organizations Nantes Métropole, Greater Lyon, and La Rochelle set up transmission channels to share these are Self Data pioneers. Each has managed to foster data only with the individuals concerned; the emergence of a dynamic in their metropolitan areas by putting together a group of motivated »» uses for these data: tools developed to allow

actors and ambassadors, having a precise idea of testers to derive value from their data (store 1 2 “On s’y met ?” - Les the data that are available and several use cases them securely, manage them, share them, that put these data to concrete use, moving towar- cross them with other datasets, and reuse them). ds appropriate governance models, and creating A SELF DATA A SELF DATA solid experimentation scenarios that pave the EXPERIMENT: 10 EXPERIMENT: way forward. The meetings attended by all three Bear in mind that, for the purposes of this kit, the QUESTIONS TO ASK 10 LEVERS TO protips d’acteurs experts du Self Data. cities were crucial to their ability to structure the following tips refer to fully fledged Self Data ex- projects and iterate potential opportunities and periments and not to pilots. The objective of an ACTIVATE “SHALL WE BEGIN?” solutions that adopting and implementing such experiment is to learn, even if it means making policies might entail. Data sharing is one of many mistakes, while the goal of a pilot is to demons- — PROTIPS FROM areas where Self Data Cities may need to coo- trate the viability of a concept. A Self Data expe- EXPERT SELF DATA perate, as certain data holders are common to riment is thus a conjoining of three types of ex- 01 02 different cities and also different themes. Coor- periment: ACTORS dinating would facilitate experiment implemen- tation across the board. If you are embarking on a »» a sociological study; 3 4 Self Data Cities experiment, we hope that you will »» an experiment in driving change in large or- share your strategies and intentions with collec- ganizations; tives and coalitions of like-minded others! A SELF DATA A SELF DATA »» an experiment in innovation policy imple- mentation (launching new tools). EXPERIMENT: EXPERIMENT: 10 7 PITFALLS TO CARDINAL RULES A Self Data experiment has three essential ingre- To guide your efforts, we have put together a dients: list of pointers to help you conduct what may be AVOID TO RESPECT construed as a slightly crazy experiment with Self »» testers: individuals who will control their Data. data during the experiment, learn from the practice, and possibly be the subjects of ob- servation by researchers; P »» personal data “returned” by data holders: per- 03 04 WHAT ARE THE OBJECTIVES OF WHO ARE THE TESTERS? HOW WILL WHAT SHOULD TESTERS BE ABLE WHO PAYS FOR WHAT? WHAT ARE THE FIELD TESTING THE EXPERIMENT? WHAT DO WE WE RECRUIT THEM? TO DO WITH THEIR DATA? INDICATORS? WHAT DO WE WANT TO 1 WANT TO TEST? LEARN?

It is important to identify your main objective: ha- This question is bound to create tension. Who You will not immediately have the answer to this Experimenting with Self Data is expensive: you This is the question that every large organization ving your fingers in too many pies will inevitably should you recruit as testers: should they be early question, which is normal. It brings back the old will be paying project managers, technical service will ask you, especially if you have applied for na- become problematic. Formulating and not straying adopters, or at least people who are already inte- Self Data dilemma between which comes first, data providers, designers, tester panel supervisors, etc. tional or European funding. Although you are here A SELF DATA from the experiment’s primary objective is es- rested in learning to manage their data? Or maybe or services? It’s like choosing between the chicken Once you have drawn up your budget, you will to learn, you can establish some indicators — not of sential to achieving its goal (to demonstrate the people who aren’t comfortable with digital techno- and the egg. Should you share the data first, and need to create a financial partnership orientation success, but of change and evolution. For example, EXPERIMENT: 10 value inherent in Self Data). However, despite the logy and could benefit from being introduced to it? then see which uses emerge before you decide file that details the cost of participating in the expe- if your goal is to restore trust between individuals backbone it provides during the experiment’s pre- Choices will need to be made. which data are the most appropriate? As part of the riment . . . and then find these partners. For them, and organizations, measuring trust would become QUESTIONS TO ASK liminary phases, you must reconsider it once you MesInfos pilot project, that is what we did — the you may wish to create a tiered partnership struc- an explicit part of the research process. have compiled your final roster of contributing goal was not to operate under any preconceived ture. You will also need associate project partners actors. The variety of domains you will traverse notions about the value of the data or its potential (eg: social enterprises, competitiveness clusters, 01during the experimental process will add many03 se- 05uses. But the risk of focusing our efforts on data07- etc.), because their expertise is essential. Finan09- condary objectives to the pot (for example, “scaling sets that had little to do with each other was great. cial partners are often data holding organizations. Self Data”), which must remain subordinate to your In the case of a Self Data Cities project, you should they may become partners for two reasons: either primary aim. do things the other way around: you should know, they intend to share their data during the experi- before starting your experiment, which use cases ment (and in this case, their financial commitment are going to emerge — while, at the same time, would have to be considerable, as they will require maintaining a certain degree of flexibility — and a considerable amount of support), or they wish to WHICH DATA WILL BE SHARED WHICH LOCAL ACTORS DO YOU therefore which data should be shared. learn how to share personal data over the medium WHICH TIMELINE TO FOLLOW? WITH THE TESTERS? WHO WISH TO ENLIST? HOW DO YOU and long term. AND WHAT IS THE “REAL” CURRENTLY HOLDS THESE DATA? PLAN TO WORK TOGETHER WITH TIMELINE? THEM? WHO DEVELOPS WHAT? WHO MANAGES THE PROJECT? HOW? A Self Data experiment without data holders is like Between data holders, social enterprises, SMEs, HOW? The major phases of your experiment process, at a fondue without cheese — it makes no sense. You competitive clusters, and researchers, you will each level, should be thoroughly mapped out: set will have to surround yourself with holders from bring together a wide range of stakeholders whose the date when the entire cohort of testers will have the start and work alongside them to set up the needs and strategies might actually conflict. Re- Any definition of a “Self Data Experiment” would The project should be staffed by at least one (at the tools in hand, for example, and the date when sharing channels. You will need to find internal member to define how this consortium will work, be incomplete without mentioning third-party, least!) one full-time FTE, depending on the size of data holders will be expected to have activated the ambassadors at each who will champion the drive perhaps by drawing up an official agreement (rules data reuse services, which enable users to derive the experiment. The local public entity leading the final shared data file, etc. A Self Data experiment is internally to validate the strategy and bring about of communication, entry into the consortium, de- value from their data. “Third-party service” can experiment can delegate project management to complex — there are many actors, and they do not its implementation. cision making, etc.) that acts as a charter that these also mean “data aggregation platform” (eg: perso- another service provider, but that person cannot always make progress at the same pace. You will 02 04actors commit to following — and also a charter nal cloud, third-party platform, data trust, etc.). The replace the city employees who act as Self Data10 need several Plan Bs and an extremely robust deci- that explicitly defines the research scope/user fee- local public entities who pioneer Self Data initia- ambassadors, as they will be the ones convincing sion making protocol, so that when a pillar of your dback protocol. tives do not need to personally develop their own08 data holders to join. You might also wish to break project timeline map collapses, you can decide platforms and services.They can rely on the local the project down into several moving parts — legal, what to do as rapidly as possible. 06ecosystem, existing services, or even conduct open technical, recruitment, tester management, and re- public tenders, etc. search, for example — that run simultaneously. GET CITIZEN/CIVIL SOCIETY DRAFT AND RATIFY A CHARTER PREPARE THE EXPERIMENT’S IMAGINING DESIRABLE FUTURES IS USE PEOPLE’S PERSONAL ORGANIZATIONS AND CONSUMER FOR YOUR EXPERIMENT “ELEVATOR PITCH” FUN AND GRATIFYING — CAPITALIZE COMMITMENT AS LEVERAGE 2 GROUPS ON BOARD ON THAT

The topic of personal data is now well known A charter is a tool that establishes trust and creates Having an easily understandable, basic description Imagine a “Siri” that knows your favorite pizza (but As mentioned above, Self Data values appeal to enough to have sparked the interest of civil society transparency in your project communications. It is of the project will go a long way towards avoiding doesn’t sell the info to Pizza Hut); a GPS that could collaborators and project actors as individuals, as and consumer organizations to be interested in it, also a valuable internal tool that conveys both the misunderstandings, and also might prevent misre- tell you not only how to reach a destination, but citizens, as family and community members, and A SELF DATA and even a desire to tackle its challenges. The par- project’s vision and its limitations over the coming presentations of the project from appearing in the also which destination would be the most relevant; so on. Propagating Self Data values is motivational, ticipation of these groups is integral to the success months. It will enable you to state openly where numerous press articles that will undoubtedly be or a fridge that reprimands your teens when they and fosters close ties among its proponents. This EXPERIMENT: of your project — how else do you expect to put in- the project’s priorities are as regards more conten- written. It is a particularly indispensable tool given drink too much soda . . . Any use is possible in the is an incredibly useful lever: it will help you not dividuals at the center of their data management tious issues (for example the “data monetization” the number of actors involved and the innovative world of Self Data, and because no data is shared only overcome the many obstacles that the project 10 LEVERS TO without making them part of the process? game) and being able to refer to it will free the ex- and transformative aspects of Self Data. You can without being under the control of the individual, is bound to encounter, but also spread the word periment from any time-consuming controversies bolster your pitch (or “the line of your argument”) concerns about tracking or surveillance can be and sustain the vision of Self Data over the longer ACTIVATE that might erupt. The charter also represents the with a few personal data reuse cases that clarify the set aside when dreaming up new uses. This allows term. This alchemy is something you must culti- 01 03very first collective output generated by the project 05subject matter and make whoever you are speaking07 your collective to embark on a quest for more09 in- vate through general assemblies and events where GET THE CNIL ON BOARD actors, and the drafting and ratification process of- to want to know more. In a similar vein, be sure to novative and unpredictable approaches. Imagining different actors can meet and exchange. These may If that list of questions worries you, fers you the perfect opportunity to test the group’s maintain a regularly updated FAQ so you have your new services — be they useful or “useless” — and give way, later on, to more informal gatherings. The never fear — Self Data experiments dynamics and its decision making process. It will most solid arguments and answers to hand — it will projecting yourself into a future where they are more they can get on with things without you, the also come with one overarching make your partner’s positions quite plain, and so help you avoid being taken by surprise. possible and real can be very fun. Creating imagi- better the project will be! benefit: everyone wins. Despite the enable you to identify solutions and compromises naries creates energy, enthusiasm, and cohesion Because Self Data embodies “the spirit” of the profound changes that implemen- upstream of operational commitments. within the group. ting Self Data entails, every actor in- GDPR (and the 1978 Data Protection Act), the CNIL volved — citizens, regions, data hol- — mainly via its Innovation and Foresight Labora- ders, digital service providers — is a tory (LINC) — has been an integral part of Fing’s BEING “OPEN” OPENS GET THE INTERNATIONAL MYDATA player in the game, and each stands MesInfos pilot study and various Self Data experi- FORM CLOSE TIES WITH YOUR DOORS BREAK DOWN SILOS WITHIN NETWORK BEHIND YOU to gain something of value. We would ments (including during the planning stages) from PARTNER’S LEGAL SERVICES ORGANIZATIONS even go so far as to say that Self Data the start. Getting the CNIL’s stamp of approval is intrinsically positive and demo- (which means having the right to use its logo in cratic. Stakeholders, regardless of your supporting documentation, if you are able to At the risk of sounding rhetorical, the philosophy their role, position, function or sta- 02establish a partnership), even informally, will be behind open source software is perfectly in line The network will be delighted to hear about your tus, will (almost) always interpret necessary for you to inspire confidence in your Absolutely zero data will be shared without the with the values that underpin Self Data. Many even Personal data within organizations is transversal decision to launch a concrete initiative (remem- “human-centered” as putting them- stakeholders. It will be a decisive factor for future sanction of your partners’ legal departments. It is see open source as a prerequisite for establishing in nature. So it will naturally transform your Self ber: MyData = Self Data) and will promote your ef- selves at the center. This is an enti- data holding partners. Fing’s main advantage is essential that you gain their approval early on, as transparency in personal data processing. It can Data experiment into an inter-departmental trai- forts among network members — these global ex- cing prospect, and it should win you that we are independent from our partners, which soon as you have settled on your experiment sce- also lead to fruitful cooperation between projects, ning ground for each of your project partners. The perts and international organizations have much many allies. means we occupy a space of “neutrality” during nario. broadening the support and impact of your ex- value generated by this type of interchange is tan- experience and insight to offer you. discussions. This greatly facilitates dialogue with periment. The open (and potentially free) aspect gible, and has the merit of being more easily reco- representatives from our partners’ various depart- greatly simplifies the adoption and use of software gnizable than the virtues afforded by Self Data. The ments as we form hypotheses and table risky so- 06solutions and tools for the project, especially com- practicality it requires is useful, and can serve10 as lutions within the wider context of an experiment04 pared to proprietary solutions that could require08 a lever for you to convince your partners to make that is both audacious and also limited (in time, in confidentiality agreements, contracts, etc. themselves more available for the experiment. participants). HACKATHONS: DON’T DO THEM (?) ANTICIPATE SLOW PERIODS IN START RECRUITING ONCE THE HAVE A PLAN B FOR EVERY MAJOR GIVE YOURSELF LEEWAY IN YOUR TESTER ACTIVITY TESTING ENVIRONMENT IS READY . STAGE OF THE PROJECT SCHEDULE 3 . . AND NOT BEFORE

This rallying cry is a recipe for how to best serve Mid-August (in Europe), the week between Christ- Avoid making your tester panel wait! If you do, your As noted previously, a Self Data experiment turns To be on time, you must plan for your time to be your purposes in the most pragmatic way possible. mas and New Year’s Day, months when national panel will certainly be let down in some way, and into a succession of experiments: in change ma- wasted (this is a proverb we have coined at Fing). Hackathons and app development competitions holidays come one after the other, back to school this will accentuate any desire they have to disen- nagement inside large organizations; in launching You will never be able to plan everything down to A SELF DATA cannot generate proof of concept (reliable, easy to time, school holidays. . . At certain times of the year, gage from the proceedings — all of which means new software; in gathering results for a sociological the last moment. Nevertheless, beyond applying use, intuitive, etc.). You can use them to spread the it is nearly impossible to anticipate how available that you run the risk of conducting the core experi- study. Even though each produces new knowledge, experience and realism to the task of estimating ti- EXPERIMENT : 7 word about new opportunities and to inform pro- your testers will be, especially since that availabi- ment with a drastically reduced number of testers. none will achieve precisely the results you antici- melines, meeting deadlines is a matter of commu- ject development, and they can help you push ideas lity also depends on the use case: on Christmas day, pate, which destabilizes proceedings downstream. nication: a seemingly tight deadline is a useful tool PITFALLS TO AVOID a step further, create buzz around a topic, recruit a smartphone game will have its highest audience, This pitfall is, unfortunately, very tricky to avoid: To ensure that the last experiment in the chain to make some of them take greater responsibility new team members. But the question remains: will and a research questionnaire its lowest response recruitment is a lengthy process, and one that of- takes place under the appropriate conditions, you for their input. any of that help you achieve your goals? rate. If the subject is complex, experienced tester ten involves partners (who also have their sche- will need to ground it on a solid foundation — some Here are some of what we now think 01 02community facilitators will likely be aware of these 04dules and priorities); the data are always “nearly06 practical outcome that is perhaps not pioneering.07 Beyond these general considerations, the three fa- of as “bad good ideas” that can ap- For example, if the primary goal of your Self Data constraints. ready;” the solution is always touted as being ready Aiming for a less ambitious but proven solution cets of a Self Data experiment are all conducive to pear during your experiment. These experiment is to promote the concept and even- “this time” . . . all the while, the experiment’s hard will temporarily bridge gaps in your timeline and creating delays.The most fraught with risk is pro- are the things we wish we had known tually embed Self Data values in the digital services deadline is inexorably approaching . . . and we have enable you begin the next phase of the experiment bably the data sharing aspect. Every organization when we started the MesInfos pilot of tomorrow, then a hackathon is an interesting EXPECT TESTERS TO LOSE not even begun to list the external factors that will at the scheduled time. has to carry out an internal, cross-departmental study and experiments. tool. On the other hand, if the objective of your ex- INTEREST weigh in! The reasonable solution? See numbers 5 process voluntarily (personal data is a legally sen- periment is to observe how individuals use a Self and 6 on this list. sitive subject) — and it will rarely be their operatio- Data service, then you will need to avail yoursel- nal priority. You must find your strongest collabo- ves of a service that is already reliable enough — rators within each organization as early on as you because it has been developed more fully — to be When it comes to experiments that go on for mon- JUGGLING DREAMS AND REALITY can. Do not hesitate to consult Fing’s work on data used autonomously by individual citizens. ths, the majority of the testers recruited at the be- portability for support, especially our “practical ginning almost inevitably give up at some point guide to data portability,” which outlines the pro- during the experiment. In any case, that’s what cess in detail. the statistics say. Retention and drop-out rates are well-documented features that must be taken into A Self Data experiment is an opportunity to envi- account when planning the technical side of socio- sage what might be possible when conditions are logical research and should be factored into any favorable. Creating this imaginary is crucial to 03goals for numbers of recruits. You must also consi- clearly identifying and consolidating your vision. der recurrence of use vs. experiment duration: if But these concepts are impossible to achieve wit- your use case is intended to allow individuals to hin the experiment’s time frame, and with existing move houses more easily, or to change a service means. You must learn to juggle enthusiasm and provider, remember that very few of them will ac- expectations for particular outcomes with clarity tually move house, and that switching providers regarding the experiment’s real perimeter of pos- might only happen one time during the entire life 05sibilities. It’s up to you to find the balance that will cycle of the experiment. allow your experiment to succeed. ACHIEVE BALANCE TREAT NEWCOMERS WITH CARE, YOU DOUBT THE MAGIC OF DATA, . . . BUT THOU SHALT ALSO DOCUMENT REGULARLY, BETWEEN DISPERSION AND WILL YOU WILL DARE TO DREAM. YOU WILL 4 CONCENTRATION, YOU WILL

Is choosing a theme before launching a Self Data Take care of your communities: partners, reusers, Shared personal data should foster the emergence An experiment Self Data must evince a conside- Thoroughly documenting (and communicating dynamic a barrier or a lever to its development? and testers will form the bedrock of your expe- of innovative uses. But you will have to avoid the rable degree of ambition. After all, it’s a very new about) each step in your experiment, and capita- The main advantage of not having a fixed theme riment, throughout the months (and sometimes trap of underestimating the gap between what you concept, you have to keep dreaming to embody it. lizing on your learnings, will show others the way. A SELF DATA pre-launch is that you can consider bringing a more years) to come. You will need to patiently answer can feasibly do with data, and magical thinking And do not dream alone: imagine simple but enter- Create common knowledge! Self Data has become expansive range of data holding organizations and the same questions, address the same concerns, about “what we could do.” Some specific properties taining uses with the testers and partners. You will more popular recently, you are not the only one to EXPERIMENT: 10 partners on board. The experiment will thus be and continue to move forward without taking “one of data (type, frequency, latency, etc.) can block cer- be dedicating a lot of brain power to understanding consider launching an initiative: cooperate, share more focused on individual data management, and step forward, two steps back.” Anyone can thwart tain uses (such as data crossing, for example). Some Self Data, and lots of time testing it and implemen- your experiences, create synergies. In addition to CARDINAL RULES less on embodying “Self Data and X” (the energy the experiment at some point if they are not suffi- uses imagined in workshops may be impossible to ting it: make that time fun. carefully documenting your progress and status, transition, mobility, etc.). The disadvantage of this ciently informed, especially outlier stakeholders implement using the data available. Crossing data- do not forget to create a log detailing exactly the TO RESPECT type of approach: dispersing your efforts. Tester who are following the project from afar or come sets may remain a fantasy. Do not underestimate types of data you are using (fictitious datasets, data 01and data densities are sometimes not coherent.03 Fo- on board later in the process. Consider delegating 05the time it takes to obtain data, nor the difficulty07 of 09repository sources/geolocation data, etc.), inclu- cusing on an explicit theme enables you to garner responsibility, training accomplices, and recruiting mobilizing reusers. ding the means through which they were shared the participation of the right actors very quickly, to Self Data champions and ambassadors as part of ASSEMBLE A VARIETY OF DATA — you will be laying the groundwork needed for sit them around the table from the get go. Above all, your efforts to establish a more horizontal space HOLDERS, YOU WILL reusers to exploit the data successfully. a stated theme enables you to make Self Data more for debate. concrete for the user by associating a temporarily fluid technical solution to a real problem. Stating a theme creates space for something new to emerge PUT TOGETHER A DREAM TEAM, — it is your territory for learning — which also has One thing you must decide immediately: can a data YOU WILL the benefit of increasing your competitiveness and holder also lead the experiment? Local public ac- AVOID MISUNDERSTANDINGS, THOU SHALT NOT LIE. . . sharpening the visibility of your efforts relative to YOU WILL tors, decidedly so, in our view. Localized public en- other cities on similar Self Data paths. tities can bring together actors with diverse and of- ten competing interests. (Fing has also been able to You will need a team whose members, together, achieve this.) Putting a private organization in the possess a wide variety of skills. You will also need a driver’s seat can lead to problems enlisting allies. Self Data is a complex concept. We have fond me- dedicated coordinator working full time, of course, Some will not be able to join a “private” initiative KEEP THE FAITH IN SELF DATA, mories of one partner who thought that the Self Once you have put together your final experiment or even two — and they should be working for an or- (eg: led by a company whose stated mission is pu- YOU WILL Data experiment would grant them access to all scenario, it will seem ideal. You will have made08 the ganization that can communicate effectively with blic service), some will refuse to join forces with the testers’ personal data, and a reuser who told effort to please everyone, you will have hybridized every stakeholder. These entities may be employed their competitors, etc. Your experiment should in- us they couldn’t begin developing services be- several scenarios into one. Beware. If it’s too good by the city, work for a DSI or in the field. Here may clude at least two to three data holders who agree cause they had no data to work with . . . Avoiding to be true, you risk disappointing partners and tes- be the perfect opportunity to recruit a third party to share the private data they hold with testers. But misunderstandings will save you precious time. ters. Avoid half-decisions: make explicit choices to lead the experiment! You will also need a “guru:” if you have only one holder who has a lot of data to Using Self Data to transform the digital economy This is why you have a FAQ: to answer testers’ and (about the target audience, the services developed, 10a highly placed person who can project the Self share (for example a city), the experiment can still directs means directing your efforts toward a very partners’ questions upstream. Literacy around Self the means with which you will enable their co-de- Data message loud and clear. You also need a killer work if the foundations of the experiment are solid. desirable and worthy future outcome. Keep that04 in Data applies to everyone, even to the most senior 06sign, etc.). Your experiment will simply be better. tech supervisor, motivated researchers, expert de- mind as you grapple with the many obstacles that data experts. signers, a facilitator to oversee the test cohorts, and 02can stand in the way of your practical pursuits. another for the innovation clusters, etc. APPENDICES READY-MADE # METHODOLOGIES Appendices Ready-made methodologies P stick their responses (on sticky notes) on a notes) sticky their responses (on stick ideas group common making sure to wall, together. take 15 minutes to allow them to exchange exchange to them allow to minutes 15 take pair; ideas with another give everyone two minutes to list the risks to minutes two everyone give and opportunitiesSelf with associated Data; » » » » to volunteer one ask up, sum everything To play and another to advocate, the devil’s play can use the lunch They the Self Data defender. opportu and - risks identified the group to break for communities, (for category by nities together citizens). individual for businesses, » Put participants into pairs, and then : and participants pairs, Put into » Lunch (1h) : Break Lunch (1h) : Break a volunteers the two give continue, you Before sum up the risks and opportunities to chance each category. for and of course the first chapterof this booklet. present the calendar time to is also the Now the next of and the dates events upcoming of workshops. 10min - Exercise 2: “In pairs, describe what describe “In pairs, 2: Exercise - 10min you means using any Self Data represents a a poem, mime, drawing, wish: a diagram, etc.” keywords, cloud of your catch some time to you gives This exercise and lets participants discuss what they breath, This en- amongst themselves. just heard have - clear and that eve been have you sures that See Self Data. of the concept has grasped ryone participants up with. your what come Smokescreen – analysis SWOT A 30min: Self Data to objections and knee-jerk Self Data seminar means that participants A and Self Data, will be questioning the notion of ne- won’t you questions that asking countless and that there will for, answers have cessarily can get The debate also be some controversy. “advocate” posing as the sole avoid To heated! spread the responsibility and to self-data, for everyone will involve exercise a SWOT around, in imagining Self Data success. is FAQ a potent resource. resource. a potent 30min - Self Data Cities: implementing Self Self Data - 30min Data on a citywide scale After defining it Self is Data, timeto the clarify ap- a regional cities and why major issues for can use our slides You proach can be fruitful. with Self Data, examples/use cases, the value to to value the cases, examples/use Data, Self with the international stakeholders, by be obtained por- data to the right and the GDPR outlook, typical few a answer to Get ready etc. tability, ownership, data monetization, questions about Data Self The more. and models, revenue “What Open question - 1 Exercise - 15min personal data think you value do kind of holds?” the data resale issue by can circumvent You asking the after organizing a small exercise: their them write have participants the above, = one idea). note (one note a sticky on answers build to minutes few a then takes The facilitator grouping and notes the reading by wall map a op- is an This the answers. to them according per- sees actor each how reveal to portunity notions preconceived sonal data and correct them. monetize individuals about how game; or maybe or game; “5 min 20 data” 20 min “5 1h - Presentation of the Self Data concept; Q Q the Self Data concept; of Presentation - 1h + A will which slides, your prepare to Use our content associated stakes the outline the general context, - session; presen (2.5 h): Plenary Morning Self of the basics self-teaching ting and Data and Icebreaker Welcome - 5min the them play Let try the easier “data in your wallet” game, which game, wallet” your in “data the easier try your in “Look participants asking of to consists wallet, find a card thatyou believe implies per- Examine up.” and hold it in some way, sonal data choose a partici - brandished, the cards being “What you do personal data kind of ask and pant, Other participants help implies?” this card think times or three the operation two Repeat answer. store a grocery cards (ex: choosing different by data consumption to lead will card loyalty chain the number quantities purchased, (product names, while a credit etc.) household, in the people of dates, purchasing data (places, card will point to the details as quickly to Drill down etc. amounts, much how reveal to a great way can: it’s you as on- than rather offline, generate we data personal line.. The participants come away with a solid un- with The participants away come potential. Self Data and its derstanding of The participants- tie Self Data to are able to concerns. local specific with their gether The participants pursue to the desire have and consider Self Data further, of the topic data and data uses. We have a list of specific challengesfor Self respond to; Data to future for list” “guest drawn up the have We to can open the debate you when workshops, have interviews, conduct wider audience, a meetings.... 30 with lunch break 10am-4pm, one full day, » » » » » » » SELF DATA SEMINAR: DATA SELF METHODOLOGY : Objectives » » » » » Participants : » : Time required » the seminar template here Download 1 THE SEMINAR Appendices Ready-made methodologies P IV/ Plenary session - 30min - session IV/ Plenary to be devoted will the day half-hour of The last reminding each group, by delivered summaries and holding a events, participants upcoming of round table discussion to figure out who was in the next and should join missing that day partici- ask work: the network Make workshop. about, think they the people contact pants to pre- have you email them a template and give that effect. pared to III/ Associate the Self Data possibilities to to the Self Data possibilities Associate III/ 30min - in the region the data available the reveal to and try each use case, Then take you “The ideas participants, Tell data behind it. - on perso draw to need just had will necessarily which data?” — nal data the on spreadsheet mini the fill to time it’s Now templates; without going into too much detail, some data that identify be able to will all you Do share with individuals. to sense make would also look — data on personal solely not focus sure if Not etc. data, open at data repositories, you’re — it all the same Note a dataset exists? the possibilities within Self understand here to will use right you content produce not to Data, away. region who are already working on these issues. on these issues. working who are already region cases that could discuss the use they that, After each issue. address emerge to our document de- consulting by yourself Prepare par- and ask data use, of domains tailing the 7 “What of kinds question: following the ticipants address use to you and use cases could services this issue?” For example: individuals to allow data to “share Contribution: transportation surveys;” complete mobi- citizens, for easier life “make Management: lity-wise;” the of the carbon footprint “evaluate Awareness: it;” and reduce region, citizens “help action: & taking making Decision budgets.” manage their mobility there not are you furtherthis; go than to need No to come up with youspecific use are cases, there ideas for the maximum number of generate to If some address the issues. that could services personal data, to the use cases are not related of in come well very may they . . . down them note handy! II/ Link issues and the potential ways Self ways Self issues and the potential II/ Link 30min - Data might address them their theme noting down by The groups begin and the issues associated sheet, A1-sized on the and projects ideas for and then iterates with it, their in resources as on draw can they people the many months to come. come. to months many “What participants question: the following Ask mobility/transport (eg) kinds of challenges would If region? your address in to like personally you these problems using an action express possible, be might ideas mobility, is theme the (When verb.” transport public use seniors “help to like things young drivers and “encourage lear- go shopping;” carpooling.” opt for ners to to jot down one solo, Participants take 5 minutes, challenge per sticky note; then each participant maps them and the facilitator presents their ideas, theme. out on the wall by can then put the participants groups, into You challenge/issue. on a different each working hyper- use the template stages, For the following - Remem this appendix. of at the beginning linked ber to modify it to fityour theme, and print out paper. A1-sized on copies several Elucidate Elucidate the issues and challenges specific the theme (eg: to according each region to so- consumption, sustainable energy mobility, etc.); cial welfare, initiatives; regional Discuss existing - (poten of in terms Self Data, all this to Link tial) use cases and data. » » » This part is essential. The themes that emerge can This part is essential. will they but forward, go you as refined be always for experiment the and workshops your inform I/ Issues/Challenges (plenary) - 30min - I/ Issues/Challenges (plenary) » » more smoo- pass part this make the day of To is- of list small a make event the before thly, theme that are likely the day’s to sues related each region. from actors local public concern to the themes to These challenges must correspond for and their strategies will address their projects “faci- mobility,” “increase soft For example: 2020. “calculate passenger transport,” intermodal litate transportation of the carbon footprint in options etc. our region,” Objectives: » Afternoon (2.5h): Looking forward forward Looking (2.5h): Afternoon themed “Challenges/Data/Uses” — groups) (small workshops Appendices Ready-made methodologies P a fictitious name for the service a fictitious name » II/ Preliminary list of uses (15min) list of II/ Preliminary this last part of bridge the is to The objective uses and po- with possible data types/sources this in will be exploring (you services tential go too to so no need that follow, the workshops vision). a this is about creating — far “Imagine a use for one): Instructions (choose enable us would service the data/What kind of it do?” What would this challenge? address to participants giving one-line avoid Ask to should They fun! have them to Tell answers. up with : come » Do not hesitate to tie in possible data repo- to Do not hesitate Open Data. of sources and sitories Do not hesitate to get online and see what what get online and see to Do not hesitate data might be available in personal kind of example for providers, service from profiles » » » uses are not Potential NB : Focus on the data. list is to what counts — important at this stage holders that emerge the data and the potential The in context. when the challenge is placed notes and notes sticky the up picks facilitator and types the details regarding the down to The best way contain. data they of sources and sources data the relevant of track keep template the use groups the have to is types the on each of placed will have you that below tables. 1) Begin with 5 minutes of individual reflection: reflection: individual of minutes 5 with Begin 1) jot down to note each participant uses a sticky (holder)? Where and possibly — What (name)? and They share How their (access)?. ideas with the group. re- know already do we information What 2) history”) “education this challenge? (eg: to lates help would that information find I can Where — me address this challenge? res- What further to 3) I need do information pond to this challenge? How can I locate that I obtain it? could How info? » feel should be included in future workshops. included in future should be feel Stage 3 (1h45): Identifying relevant relevant Stage 3 (1h45): Identifying data list (1h30) Data I. the main themselves Each group should ask “What will be needed information question: be them to Ask this challenge?” to respond to as specific as possible: “Wecan startby listing actual but information, of categories general (ex: be better data would ideas about concrete - sport informa lesson fee “private like an item tion” is too broad; but data relating “length of lessons paid/number of commitment/number lessons remaining” of taken/number lessons of is better). Break (15min) Break participants tell they that when the break, Before a challenge pick to have will they back come table = 1 challenge at that table (1 and sit down place to break the of advantage Take group). 1 = a template sheet for the groups to fill out on each table (see the figure in Stage 3);you can spot on on the templates either prepare new beforehand out them print or notes, sticky giant on A1-sized paper. Stage 1 (20min): Introduction Stage 1 Thanks to the first seminar, you have hopefully - expe in the involved people of circle the widened concept the explain must you So process. riment of Self Data again, to briefly, bring everyone up refresh to everyone This will also allow speed. to their memory. prior of Summary Stage 2 (40min): and furtherworkshop development here: slate will not be starting out with a blank You a range have you earlier seminar, the thanks to during this on iterate issues and challenges to of year’s summarizing the coming After workshop. present the to minutes a few take points, focal key semi- the previous in discussed challenges 4 3 to session in a plenary to will return you which nar, the reformulate is the time to Now after. shortly actors. issues with the relevant you per challenge maximum if minutes Spend ten se- first the of summary a created you If four. have can present one slide you then takeaways, minar’s about notes includes that challenge/issue per use case and the early and data, actors relevant The slides will enable participants more to ideas. the op- you and offer discussion, join in the readily their relevant about newcomers ask to portunity that initiatives and ideas about existing contacts methodology methodology “Wanted Data List” “Wanted 30-40 plus one 15min break 3h, » » DATABLITZ (DATA HUNTING) HUNTING) (DATA DATABLITZ METHODOLOGY WORKSHOP: Objectives: Based on the produced as part of a crossover between Fing’s Fing’s between as partproduced crossover a of will workshop this projects, Infolabs and MesInfos be useful or would data that wish list of a produce associa- some kind of has that participants think course, of will, There with a particulartion topic. data. on personal always be some focus data that has not even will reveal you Sometimes two actually are There yet. computerized been identify you the data either scenarios: possible already exist (you know where to find them), or yet. do not but they exist, them to love would you some do can holders data workshop, the Before as data in have what they at and look “homework” on the chosen theme. systems their information CIOs and IS professionals invite is the time to Now workshop! the them to and invite a coffee, for Participants: » Time: » 2 THE DATABLITZ Appendices Ready-made methodologies P Self Data Cities (energy, mobility, education) mobility, Cities (energy, Self Data health energy » » » Our most “prospective” visualizations: Our most “prospective” » » » the data visualization from the MesInfos pilot visualization from the MesInfos the data (2016-2018) - experi our MesInfos visualization from data ment (2013/2014) a one-line pitch/tagline that encapsulates that encapsulates pitch/tagline a one-line concept the service features. 3 key » » » » > Visualizations based on data present in organi- Visualizations > systems: zational information » » To generate value from the workshop proceedings, proceedings, value from the workshop generate To and if possible a spreadsheet, scan the results into the results. visualizing read map to an easy make Here are some examples. The participants return to the plenary seating ar- The participants the plenary return to per group one spokesperson rangement and now takes a turn summing up their findings. Descri- far too take data would of single piece bing every on 3 focus will therefore The spokespersons long. original more (the data interesting of types 4 to have and the uses they the better) or surprising, them. envisioned for Summing up (15min) » » Appendices Ready-made methodologies P - Stage 2: Services and Data (10min) - - and Data (10min) Stage 2: Services Plenary created you visualization present the data You and Get it up on a screen, the Datablitz. after vi- (as a complied you data the list of distribute etc.). as a data map, as a simple list, sualization, (at least print out enough copies to Remember one per table). the for created visualization a of An example “data cards.” with printable workshop, vices per challenge, with the facilitator’s help. the facilitator’s with challenge, per vices go fast and it should short, is fairly This stage number the maximum generate to want you — time wit in a limited simple ideas possible of Sorting will them. of one each questioning hout after. come “What form would that service take? (app, (app, take? “What that service would form etc.)” social network, object, site, “Can you formulate these service ideas like ideas like these service formulate you “Can but . . . X do that would ‘It is a service this: for/ use also could we that and Z, and Y, also A.” like Generate service concepts - 30 min. - concepts service Generate “We have identified your in citizens by challenges experienced several significant regions; now, what concrete services can individuals enable would that imagine you with these challenges? contend to » » » » » or one for individually think may Participants = (1 post-it notes then use sticky minutes, two The fa- share ideas with the group. an idea) to - tem ideas” “service A4 the completes cilitator ... 4 ser- 3, 2, 1, imagine Each group can plate. » » “service the of copy A4-sized one Materials: table per ideas template” Have the groups begin by entail? it does What sub-challenges challenge: iterating on the tackle? we the challenge should of What aspect inherent in this challenge? What is the problem etc.) support, (education, participants questions: the following Ask » Reminder of the challenges and movement movement the challenges and of Reminder 10 mi- - groups (1 challenge = 1 group) into nutes. Quick Quick presentation of Self Data; - informa tion on the objectives of the that have the challenges reminders of workshop; emerged. card ins- “data” Each participant draws a after visualization produced the pired by “Imagine says, The facilitator the Datablitz. or do something with this can use you that in collaboration or yourself by either data, do with to like you would What with others. then present think, 3min to have You it? words.” in a few use idea your » » » Stage 1: Challenges to services (40min) services Challenges to Stage 1: group work - Introduction and Ice-breaker - Plenary Plenary - and Ice-breaker Introduction (20min) » » » go around the table to This is an opportunity are fami- and trade ideas about the data that participant the If participants. Datablitz to liar ask use the data, to with a way up cannot come the thoughts that they explain simply them to the data might and how with the data associate with other data. be combined potentially Service ideas template Service template: detail Service template: Francesca Persona 30-40 with one break 3.5h, » » » » » - sont téléchar à l’atelier nécessaires templates Les certains) à en modifier : aurez geables ici (vous » » » Participants: » Time: » Foster the emergence of a dozen service service a dozen of the emergence Foster and outline them, a few, select concepts, their usage scenarios. create on personal data to must rely These services or groups of individuals for value generate completed have to will need You individuals. (see beforehand workshop “DataBlitz” the prepared have methodology) and to previous visualizations or at least created either data can share easily. you lists that pro- privacy about security, now worry Do not on ge- is focused workshop The etc. tection, be will workshop coming The uses. nerating sharing frameworks. to dedicated » » » This methodology was developed in partnershipin developed was methodology This . with the BAM Collective Objectives: » » » previously, a data list not compiled have you NB: If not be will you visualization, a data or created probably will You workshop. this conduct to able de- as many imagine digital services, be able to but the point sign studio methodologies do today, Self construct to is workshops I” “Imagine these of the interval out space to free Feel Data services. give to workshop and this the Datablitz between visualiza- the produce to need you the time you that might not have with data tion and enrich it recorded. been IMAGINE I WORKSHOP I WORKSHOP IMAGINE “SERVICE (AKA METHODOLOGY WORKSHOP”) DESIGN 3 USE CASES Appendices Ready-made methodologies P “Back to the data: to do all this, what data what do all this, the data: to to “Back Which information need? will the service manually, enter to have will the persona automatically, collected which data will be and when?” . . . etc. tions, explain how the service is used and used is service the how explain tions, concerns: the persona’s it addresses how one does How it? use persona the will how mo- (via which medium: service the access What stages etc.)? online platform, bile app, ser- the using when through go user a does vice?” » Step 5: Summing up/Services Pitch Pitch 5: Summing up/Services Step Plenary (10min) - as work their of results the shares group Each briefly as possible: name ofpitch, service, the for data required of 2/3 items some features, steps name and 2/3 key persona function, it to use the service to follow to the persona needs properly. » “You should now fill in the people have you last(if detail - template Service page of the ask may you group, your with artistic abilities in that users ‘screens’ the design some of them to see). would status; relationship to the theme, etc.) the theme, to status; relationship How do they relate to the theme? How do it? experience they - com would motivations) (or Which needs use this service? pel them to - are of you the service What obstacles will overcome? to them need fering principal flaws? What are the service’s “Which this for situations are problematic Explain the challenges that persona today? is dealing with at the moment persona your the service).” of (within the context participants is for this step The purpose of use that will service for contexts discern to the to relevant are and persona the benefit these situa- “In each of concerns. persona’s » » » » » » » » » » III/ Use a persona to describe the use case/ describe the III/ Use a persona to (40min) scenario service ser- your using persona your of the story “Plot can tell You timeline. scenario on the usage vice see he does (what steps 4-5 in journey user the help Use these questions to etc.). on his screen, you: » »

“persona template: Francesca” template: “persona Who are they? (age; civil and professional Do we agree with the principles the service the service with the principles agree Do we value it will create think do we — on is based satis- Are we it? the individuals who use for fied with thefeatures itoffers? Is something missing? clearly work to continue we on the above, agree If we what are If not, as described. on the service Which features? most relevant the service’s with agree does it target? Do we audience(s) described? the target audiences » » » II/ Deepen the persona profile (20min) the II/ Deepen the persona (or of Describe the characteristics chosen: have you personas) » 1) What does the service do? service What does the 1) » » selection 2) Persona participants 1 select will stage, this of end the At cards available, or 2 personas (from the persona will en- the personas or from their imaginations). the how picture of a concrete create able them to under which cir- whom, by used, might be service what benefit. to cumstances, use the can You theme. suit the day’s to adapted will have you that Break (15 min) Break group - (1.25h) use cases Create Stage 4: group/select I/ Participantschoose a service a persona (15min) the participants are motivated think you If another table/ to switch them to invite enough, short presentation of A group. join a different “We follows. imagined service group’s the former are you either remain where to now you invite - a diffe table where join a different or to seated, least one particiAt - was imagined. rent concept pre- to table, pant must remain at their original the sit, to decide you Wherever sent the concept. script the phase will be to the next of objective must be able not only you meaning that service, but also some in detail, its features describe to for it.” use cases/scenarios concrete specific, a (this is changed has composition the group If the same groups if re-summari- time thing: keep switch but isn’t feasible, concepts zing the service participants things around if possible) and allow at with the services themselves familiarize to table. their new To organize your thoughts, use the first two pages two first the use thoughts, your organize To detail. template: the service of a pitch, will require, data the service the kinds of - (app/platform/ob mode delivery the service etc.), ject, the target audience, to users. the benefits it will afford » » » » » Have Have the groups begin : to and develop define them to Ask concept. refine their service » Back in their groups, participants choose an idea in their groups, Back se- them to Remind on. work to all agree can they personal the use of that will require an option lect data. » » » » Stage 3: Services definition and- develop group - ment (40min) . . . and so, and for the rest of the workshop, we are we the workshop, the rest of and for and so, . . . work, to reality; with ideas your compare to going be to individuals have use by destined for services workshop, Datablitz the to Thanks data. by driven we have identified and documented aof number [NAME OF “personal the the data from these data, landscape.” THEME] data YOUR - interes of with a lot up come probably have “You achievable are probably Some ideas. ting service be- more time take some will probably and now, .” . . day of the light see they fore Appendices Ready-made methodologies P

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- Eve scenario: Money” Money, “Money, The their starts monetize ryone want to to 10min: presentation of the Self Data Cities the Self of 10min: presentation objectives and workshop project 5min “Imagined services:” spend a few mi- at the created presenting the use cases nutes a will be delivering You workshop. previous have must you but each, of brief summary each service for sheet a detailed summary workshop. in the later out for printed 5min “Why the exercise, foresight This is a tricky continue:” current situation cannot it asks participants their because project to mo- governance and imagine minds forward, but today, exist dels that don’t necessarily begin you So so desired. if the actors could it why explaining by process the foresight by . . . is important today discuss models to might happen tomorrow. what revealing scenarios: disaster Examples of • » » » Stage 1: Setting the Scene (1h) - Plenary - (1h) the Scene Setting Stage 1: » » N service imagined we workshop, the previous “At will paint We challenges. the meet to concepts each one (name + tagline + picture of a brief you these use can associate you so that main features) models.” cases with one or more governance » 30-40 3h. » » Objectives: Objectives: and the services to a more global approach Take assigning a mo- by imagined use cases previously each one. to data governance del of options. with the existing familiar 1) Become 2) Consider the “back operations office” the use model a governance and create will involve, case it. scaffold to at least one sure the model overcomes 3) Make obstacle. Participants: » Time: » here. workshop template and cards the Download THE IMAGINE II METHODOLOGY II METHODOLOGY THE IMAGINE OF “WHICH MODEL (AKA USE?”) WHICH FOR GOVERNANCE 4 MODELS GOVERNANCE GOVERNANCE Appendices Ready-made methodologies P After thinking about the obstacles and des- After - over able to cribing a model that has been the study to minutes a few take them, come making that mo- pathways opening towards what levers What milestones, del a reality. emerge to that model for be needed would today? Facilitators choose from a list of ready-made ready-made choose from a list of Facilitators obstacles that best fit the alternative model on can rely You participants designed. have visualizations available in the template: the data aspirations; destruction of data centers; generalized monopoly; rebellion. Do not he- others. create to sitate » » Stage 4: Summing up (20min) - Plenary - Stage 4: Summing up (20min) the and case use their summarizes group Each including the obstacle it model that emerged, making it a reality. to and the steps overcomes, Stage 3: Putting the Model to the Test — — Test the to the Model Putting Stage 3: - (30min) it be Implemented? Can How group “How “How does this obstacle This affect your model?” participants allows dis- to exercise pure foresight imagine the their model, for safeguards legal cern some and consider create, it may controversies them. initial responses to » » . . . Waze anks ity eg survey eg ity cultural for access programs etc. improvement, . . . elcos ity-developed, ity-developed, bundled application Aggregated data ity-developed, ity-developed, bundled application Data sharing oogle etc. calendar, eisure activities, eisure of points tourist interest e Data Open latform furnished latform the it b visualization access and consent management) Quantified Self Quantified apps Data sharing utomakers other services other services ar chemins ublic transport operators If you have the time, consider describing what the consider the time, have you If actor’s from the regional model is transforming “are perspective: we making an actor obsolete?”; etc. skills,” brings new “This actor this model relevant to our use case? What does use case? our to relevant this model together put time to take can then You it offer?’ to (This is the time a hybrid.” even model, a new the shelf’ ‘off the explaining sheets the distribute models that exist. You can find visualizationsof 1.) each in Chapter it is whom to the data is stored, “Describe where it as a can represent You in what ways. shared, by partdiagram in the dedicated the template of as pre- Qualify page. on the next using the icons are. actors key who the model’s as possible cisely like schema, with a complete up should come You ‘Roundabout’ called this one describing a service model platform third party’ ‘trusted that uses the data sharing with individuals. manage to template template “Use the template to answer this question ‘Why is this question answer to “Use the template here. You You can use the firsttwo pagesof the “Abstract reflection“Abstract on a particular model makes ‘What does it yourself ask to have you no sense: Use it to you. helps This is where the use case do?’ purpose, the model’s understanding of your guide are not just explaining you so . . . etc. who it serves, it can how are illustrating you some structure, support region your uses that the inhabitants in will find useful.” “You have a service (ex: Toque Verte) and a data go- Verte) Toque (ex: a service have “You - Concen the personal cloud). model (eg: vernance idea the governance: on the model of today trate it a desirable make to it, modify to it, improve is to your in emerge see to like would you model that manage to enable individuals you help to region their data effectively.” Each group is allocated a use case. Before this Before use case. a Each group is allocated yourself for determined have will you workshop, each for appropriate most the seem models which data co-operatives, data imply uses for (collective etc.). trusts, One group = 1 model + 1 use case. = 1 model + 1 One group - Gover Alternative Building an Stage 2: groups - (1h10) Model nance Appendices Ready-made methodologies P - . . .data (who . are the . 2 to 5 holders the ex do without? cannot periment absolutely API Which share? they would data Which use?) do they geographical many, how (who, .testers . . modes, recruitment/facilitation perimeter, user feedback) will be and uses (Which services .services . . - experi the during tested and implemented NB: use the hypothetical use cases — ment - and gover data transfer and models of and — learned about previously you nance enrich- Z, to A from development eg: how, group will work on an experiment scenario that scenario on an experiment work group will startinghas a different point. each have “N testers Lyon: Greater of In the case can They the city. by provided a personal cloud cloud from the personal service “X” download Greater the by developed been has which store, Lyon.” an experimentation have Each group should Also efforts. their scaffold to template scenario the of sheets printing out the summary consider emerged. use cases that have ask will be to building exercise scenario “Your . . to. questions related and answer 1) What would you like to learn and/or to like you What would 1) Data via a Self and/or demonstrate create on [theme] in [City]? experiment the go ahead give to need you What do 2) legally that? (ex: like an experiment for detailing where, document substantiated and when the data will be shared) how, at all costs? avoid want to you What do 3) starts in 3 that only an experiment (ex: - tes enough recruit able to not being years, etc.). ters, Then, compare your list of axioms to the parti the to axioms of list - your compare Then, goal The exercise. using the following cipants’ of- (po the interests converge to find waysis to partners those with tential) experiment in the and the inhabitants. the community of questions: these three Answer (use prepares their answers silently Everyone per 1 color 3 colors, notes: sticky color different that the facili- then shares them so - question) them on a wall. can group tator - Experimental Scena Stage 3: Producing Group rios (1h30) - Each groups. three to two form then can You My Mobility Budget; Shared Mobilities; Shared Budget; Mobility My Coach. CO2 about fifty testers who are employed or Enedis; Office, the Post the city, by test the validity of the Self Data as a of validity the test personal data; controlling means of Self Data of the universality explore digital mediation); — testers (beyond have testers test uses cases related to mo- to uses cases related test testers have bility: involve: meet two objectives: objectives: two meet • • • • » » » » » Stage 2: What We Want to Learn/What Want Stage 2: What We Plenary - (30 minutes) Avoid to Want We to will have you the workshop, for prepare To axioms some developing time some spend months of several After each experiment. for in experiments and discussing the iterating that each the objectives and beyond, workshops and the conditions achieve to seeks experiment their guarantee to that must be established Get some help clear. be fairly ought to success - your these axioms iterate to from colleagues the workshop. self before the participants. them to introducing Start by Rochelle in La “The experiment For example, . . must . » data holders who agree to share data with to data holders who agree concern, the individuals they reuse those data; who will be able to testers data their reuse to testers enable to tools etc.). services, third-party (platforms, » » » “This workshop enables you to precisely define testers, number of experiments: of types different requirements, data solutions, technical timelines, cla- as a means of It will also serve etc. budgets, experiment potential any of rifying the stance Under which you? join to ready partners: are they conditions?” Stage 1: Introduction (20 min) - Plenary - (20 min) Introduction Stage 1: the during produced what was of little overview A same the on everyone get will workshops past Challenges, Self Data, of the concepts Cover page. Models. and Governance Use Cases Data, this present attached to stakes Be clear about the to stakeholders moment for it is a key workshop: inspire to carried out previously use all the work scenarios experiment two one or their creation of futures towards move to city that enable their and also feasible. that are desirable, fundamental has three Self Data experiment “A components: requisite » » » Describe Self Data & “theme” use cases that “theme” & Describe Self Data experimentation. via can be developed - experi (potential) of interests the Converge ment partners the community of with those inhabitants. and the city’s scenarios. Understand Self Data experimental actors, (budget, Understand the parameters to and the timelines relative etc.) partners, these experiments. 30 2.5h » » » » » » Objectives: Objectives: » » » » Participants: » Time: » here. workshop template and cards the Download EXPERIMENTAL SCENARIO SCENARIO EXPERIMENTAL (AKA METHODOLOGY IN DATA SELF “IMPLEMENTING CITY”) YOUR 5 SCENARIOS EXPERIMENTAL EXPERIMENTAL Appendices Ready-made methodologies P - ment of existing services, competitions, etc.?) competitions, services, existing ment of - resear holders? the data are (Who .actors . . chers? funders?) in mind that (keeping .and timeline/budget . . across place take will likely the experiment re- composition, fronts: round table different and services facilitation/research, cruitment, from inspiration take can You development). ‘MesInfos booklet the Pilot’ to help you flesh out your ideas.”. periment started! Each group shares its experimental scenario in scenario experimental its group shares Each will be work of a lot the workshop, After plenary. and re- produced the material extract to needed You will formulate need it into specific scenarios. - external and internally an produce to be able to here). an example shareable document (see ly with the agreement any This will be the basis for The possible partners the scenarios. on one of then presented document can be amended and “Partnership a of (perhaps in the form publicly the ex can get you then and . . . File”) Orientation - min) (10 Feedback Collective Stage 4: Plenary “WHAT IF CITIES TOOK A CENTRAL ROLE IN RETURNING CITIZENS’ PERSONAL DATA TO THEM?”

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