DOCSLIB.ORG

Architecture for Integrating Desktop and Web 2.0 Data Management

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Architecture for Integrating Desktop and Web 2.0 Data Management ICWE 2008 Workshops, 7th Int. Workshop on Web-Oriented Software Technologies – IWWOST 2008 Architecture for Integrating Desktop and Web 2.0 Data Management Stefania Leone, Michael Grossniklaus, Moira C. Norrie Institute for Information Systems ETH Zurich CH-8092 Zurich, Switzerland leone, grossniklaus, norrie @inf.ethz.ch { } Abstract work activities. Thus, friendships might be managed by Facebook, while professional networks and contact infor- A new form of personal information fragmentation is mation may be managed by sites such as LinkedIn or Xing. arising due to the rapid growth in Web 2.0 applications and Clearly, this development in terms of how the Web their use for the management of data typically associated is used for personal information management (PIM), also with desktop applications. We propose a data management raises several technical challenges with regard to data man- architecture that allows data to be shared between desktop agement. While the Web is an ideal platform for collabo- and Web 2.0 applications. The architecture supports a sep- ration and participation, Web applications generally cannot aration of concerns between the management of personal compete with desktop applications in terms of complexity data and its publication on the Web to social networks. and integration into the local working environment. Fur- ther, while a few approaches have been proposed to enable users to work with Web 2.0 applications offline, currently 1 Introduction desktop applications still cope better with this requirement. Therefore, it is not to be expected that Web 2.0 applica- Web 2.0 is the term often used to describe the Web’s evo- tions will replace desktop applications entirely, but rather lution from a hypertext publishing system [2] into a plat- that the two kinds of applications will be used for differ- form of participation and collaboration [18]. In Web 2.0, ent tasks and modes of working. However, they may share content is not only delivered to users, but users actively data which means that, ideally, there should be some way of participate by augmenting and creating content. As a con- seamlessly managing data across desktop applications and sequence, content is no longer created locally and then Web 2.0 applications. published to the Web, but rather managed entirely online. The distribution of information across desktop applica- In essence, Web 2.0, together with Rich Internet Applica- tions and Web 2.0 applications introduces further forms of tions (RIA), are taking over some of the functionality of information fragmentation already considered to be one of traditional desktop applications. the main issues of PIM with respect to desktop applications. In particular, several Web 2.0 sites have emerged that We believe that new forms of data management architec- allow personal information to be managed collaboratively tures are required that can provide an integrated approach to over the Web. Personal data can be of different types and data management for desktop and Web 2.0 applications with can be categorised into two main groups. First, there is data a clear separation of concerns between the management of which formerly has been managed locally by desktop appli- personal data and its publication on the Web to social net- cations, such as contacts, documents or pictures. Second, works. One of the main technical requirements is to provide there is a lot of personal data which has only emerged be- ways in which data can be synchronised between desktop cause of the Web, such as bookmarks or any kind of meta- applications and Web 2.0 applications. However, such an data associated with media content. Web 2.0 applications approach should also incorporate concepts that have proven that manage such personal information include sites such as useful in Web 2.0 applications. One such feature that can be Flickr and YouTube for images and videos, Blogs for writ- witnessed on sites such as Facebook is the ability to extend ing diaries or travel journals, Google Documents for man- these platforms based on plug-ins or modules. In order to aging and sharing documents or del.icio.us for Web book- successfully manage data for Web 2.0, we believe that the marks. It is important to note that while some of these sites data management architecture should reflect this notion of focus on a user’s private life, others are closely related to components. 13 ICWE 2008 Workshops, 7th Int. Workshop on Web-Oriented Software Technologies – IWWOST 2008 In this paper, we first motivate the need for a data man- Although there is a lack of detailed studies on how agement architecture that bridges the gap between the desk- Web 2.0 applications are being used to manage personal top and Web 2.0 and then present our approach that is in- data, general surveys such as [14] show that social net- tended for the development of data-centric applications. We working sites such as Facebook are heavily used for manag- begin in Section 2 with a background discussion of the state ing and sharing personal data such as photos in addition to of the art in developing Web 2.0 applications as well as cur- keeping in touch with friends. It should be emphasised that rent solutions in the domain of personal information man- personal data includes work-related data and not just data agement. Section 3 provides an in-depth analysis of the related to one’s private life. For example, increasingly re- challenges and requirements that must be met by any in- searchers are managing personal data related to their work tegrated approach to data management for Web 2.0 appli- such as contacts, bookmarks and information about their cations. In Section 4, we then propose an architecture that publications on the Web. addresses the requirements defined in the previous section. This shift from desktop data management to Web 2.0 Preliminary results and future work is discussed in Sec- data management raises a set of new issues for personal data tion 5. Finally, concluding remarks are given in Section 6. management. For example, it has become popular for users to publish collections of photos on various Web sites such as 2 Background Flickr and Facebook, in order that they can share this data with friends. But, typically, users also keep local copies of this data. Sometimes they even publish different or the In this section, we first review the data management fea- same photos to different Web 2.0 sites in order that they can tures of Web 2.0 applications and then go on to describe ap- share it with different communities. As a result, the data proaches that have been adopted in the PIM research com- objects may be replicated and users need to manually keep munity to address the problems of information fragmenta- track of which photos and which versions of these photos tion on the desktop. have been published to particular sites. Sometimes users As outlined in [18], Web 2.0 is a term used to refer to will make changes to the photos already published in which a category of Web-based applications that have become ex- case some form of synchronisation between the published tremely popular in recent years by defining a set of features and the desktop data is required. that they have in common. These features can be sum- Other types of personal data may be produced directly marised in terms of two main trends. On the one hand, on-line. For example, Blog posts or bookmark collections Web 2.0 applications are characterised by rich and respon- may be created using a Web 2.0 application which means sive user interfaces, and, on the other hand, the user be- that users lose control over that data and they cannot access comes a participant who not only consumes content, but ac- it offline. Also, one of the features of Web 2.0 is that users tively takes part in content creation. author content collaboratively which means that other users There has been a lot of attention given to the de- may tag photos, add comments to posted articles etc. And sign of application development frameworks for the imple- rather than each user having to manually maintain an en- mentation of Rich Internet Applications in both industry tire address book, each user only has to maintain their own e.g. [23, 22, 17] and academic environments e.g. [3, 21]. contact details and they are automatically shared by other However, to date, little attention has been paid to data man- users. agement issues in terms of both detailed studies on the use of Web 2.0 applications for PIM and also tools and infras- As a result, nowadays, personal information is not just tructure for managing and sharing user-generated content. fragmented across desktop applications but also between desktop applications and one or more Web 2.0 applications. An additional feature of many Web 2.0 platforms and ap- A user typically maintains several social networking pro- plications such as Facebook1 and Flickr is the provision of files, for example one for friends and family on Facebook an application development interface (API) which allows an and a Xing or LinkedIn profile for managing business con- application developer to access and retrieve platform data as tacts. Research efforts have already been made to allow the well as to build applications for that platform. The Google aggregation and integration of social networking informa- Open Social API2 is an effort to standardise interfaces to tion from various Web 2.0 applications [13]. In [11] per- social networking applications by defining a platform inde- sonal user data scattered over various Web 2.0 applications pendent interface which can be implemented by any social is integrated by providing an infrastructure for integrating networking application.
Load more

Recommended publications
  • A Data-Driven Framework for Assisting Geo-Ontology Engineering Using a Discrepancy Index
    University of California Santa Barbara A Data-Driven Framework for Assisting Geo-Ontology Engineering Using a Discrepancy Index A Thesis submitted in partial satisfaction of the requirements for the degree Master of Arts in Geography by Bo Yan Committee in charge: Professor Krzysztof Janowicz, Chair Professor Werner Kuhn Professor Emerita Helen Couclelis June 2016 The Thesis of Bo Yan is approved. Professor Werner Kuhn Professor Emerita Helen Couclelis Professor Krzysztof Janowicz, Committee Chair May 2016 A Data-Driven Framework for Assisting Geo-Ontology Engineering Using a Discrepancy Index Copyright c 2016 by Bo Yan iii Acknowledgements I would like to thank the members of my committee for their guidance and patience in the face of obstacles over the course of my research. I would like to thank my advisor, Krzysztof Janowicz, for his invaluable input on my work. Without his help and encour- agement, I would not have been able to find the light at the end of the tunnel during the last stage of the work. Because he provided insight that helped me think out of the box. There is no better advisor. I would like to thank Yingjie Hu who has offered me numer- ous feedback, suggestions and inspirations on my thesis topic. I would like to thank all my other intelligent colleagues in the STKO lab and the Geography Department { those who have moved on and started anew, those who are still in the quagmire, and those who have just begun { for their support and friendship. Last, but most importantly, I would like to thank my parents for their unconditional love.
    [Show full text]
  • QUERY-DRIVEN TEXT ANALYTICS for KNOWLEDGE EXTRACTION, RESOLUTION, and INFERENCE by CHRISTAN EARL GRANT a DISSERTATION PRESENTED
    QUERY-DRIVEN TEXT ANALYTICS FOR KNOWLEDGE EXTRACTION, RESOLUTION, AND INFERENCE By CHRISTAN EARL GRANT A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 2015 c 2015 Christan Earl Grant To Jesus my Savior, Vanisia my wife, my daughter Caliah, soon to be born son and my parents and siblings, whom I strive to impress. Also, to all my brothers and sisters battling injustice while I battled bugs and deadlines. ACKNOWLEDGMENTS I had an opportunity to see my dad, a software engineer from Jamaica work extremely hard to get a master's degree and work as a software engineer. I even had the privilege of sitting in some of his classes as he taught at a local university. Watching my dad work towards intellectual endeavors made me believe that anything is possible. I am extremely privileged to have someone I could look up to as an example of being a man, father, and scholar. I had my first taste of research when Dr. Joachim Hammer went out of his way to find a task for me on one of his research projects because I was interested in attending graduate school. After working with the team for a few weeks he was willing to give me increased responsibility | he let me attend the 2006 SIGMOD Conference in Chicago. It was at this that my eyes were opened to the world of database research. As an early graduate student Dr. Joseph Wilson exercised superhuman patience with me as I learned to grasp the fundamentals of paper writing.
    [Show full text]
  • Usage-Dependent Maintenance of Structured Web Data Sets
    Usage-dependent maintenance of structured Web data sets Dissertation zur Erlangung des akademischen Grades eines Doktors der Naturwissenschaften (Dr. rer. nat) am Institut f¨urInformatik des Fachbereichs Mathematik und Informatik der Freien Unviersit¨atBerlin vorgelegt von Dipl. Inform. Markus Luczak-R¨osch Berlin, August 2013 Referent: Prof. Dr.-Ing. Robert Tolksdorf (Freie Universit¨atBerlin) Erste Korreferentin: Natalya F. Noy, PhD (Stanford University) Zweite Korreferentin: Dr. rer. nat. Elena Simperl (University of Southampton) Tag der Disputation: 13.01.2014 To Johanna. To Levi, Yael and Mili. Vielen Dank, dass ich durch Euch eine Lebenseinstellung lernen durfte, \. die bereit ist, auf kritische Argumente zu h¨oren und von der Erfahrung zu lernen. Es ist im Grunde eine Einstellung, die zugibt, daß ich mich irren kann, daß Du Recht haben kannst und daß wir zusammen vielleicht der Wahrheit auf die Spur kommen." { Karl Popper Abstract The Web of Data is the current shape of the Semantic Web that gained momentum outside of the research community and becomes publicly visible. It is a matter of fact that the Web of Data does not fully exploit the primarily intended technology stack. Instead, the so called Linked Data design issues [BL06], which are the basis for the Web of Data, rely on the much more lightweight technologies. Openly avail- able structured Web data sets are at the beginning of being used in real-world applications. The Linked Data research community investigates the overall goal to approach the Web-scale data integration problem in a way that distributes efforts between three contributing stakeholders on the Web of Data { the data publishers, the data consumers, and third parties.
    [Show full text]
  • L Dataspaces Make Data Ntegration Obsolete?
    DBKDA 2011, January 23-28, 2011 – St. Maarten, The Netherlands Antilles DBKDA 2011 Panel Discussion: Will Dataspaces Make Data Integration Obsolete? Moderator: Fritz Laux, Reutlingen Univ., Germany Panelists: Kazuko Takahashi, Kwansei Gakuin Univ., Japan Lena Strömbäck, Linköping Univ., Sweden Nipun Agarwal, Oracle Corp., USA Christopher Ireland, The Open Univ., UK Fritz Laux, Reutlingen Univ., Germany DBKDA 2011, January 23-28, 2011 – St. Maarten, The Netherlands Antilles The Dataspace Idea Space of Data Management Scalable Functionality and Costs far Web Search Functionality virtual Organization pay-as-you-go, Enterprise Dataspaces Admin. Portal Schema Proximity Federated first, DBMS DBMS scient. Desktop Repository Search DBMS schemaless, near unstructured high Semantic Integration low Time and Cost adopted from [Franklin, Halvey, Maier, 2005] DBKDA 2011, January 23-28, 2011 – St. Maarten, The Netherlands Antilles Dataspaces (DS) [Franklin, Halevy, Maier, 2005] is a new abstraction for Information Management ● DS are [paraphrasing and commenting Franklin, 2009] – Inclusive ● Deal with all the data of interest, in whatever form => but semantics matters ● We need access to the metadata! ● derive schema from instances? ● Discovering new data sources => The Münchhausen bootstrap problem? Theodor Hosemann (1807-1875) DBKDA 2011, January 23-28, 2011 – St. Maarten, The Netherlands Antilles Dataspaces (DS) [Franklin, Halevy, Maier, 2005] is a new abstraction for Information Management ● DS are [paraphrasing and commenting Franklin, 2009] – Co-existence
    [Show full text]
  • Exploring Digital Preservation Strategies Using DLT in the Context Of
    Forget-me-block Exploring digital preservation strategies using Distributed Ledger Technology in the context of personal information management By JAMES DAVID HACKMAN Department of Computer Science UNIVERSITY OF BRISTOL A dissertation submitted to the University of Bristol in accordance with the requirements of the degree of Master of Science by advanced study in Computer Science in the Faculty of Engineering. 15TH SEPTEMBER 2020 arXiv:2011.05759v1 [cs.CY] 2 Nov 2020 EXECUTIVE SUMMARY eceived wisdom portrays digital records as guaranteeing perpetuity; as the New York Times wrote a decade ago: “the web means the end of forgetting” [1]. The Rreality however is that digital records suffer similar risks of access loss as the analogue versions they replaced - but through the mechanisms of software, hardware and organisational change. The first two of these mechanisms are straightforward. Software change relates to how data is encoded - for instance later versions of Microsoft Word often cannot access documents written with earlier versions [2]. Likewise hardware formats obsolesce; even popular technologies such as the floppy disk reach a point where accessing data on these formats becomes increasingly difficult [3]. The third mechanism is however more abstract as it relates to societal structures, and ironically is often generated as a by-product of attempts to escape the first two risks. In our efforts to rid ourselves of hardware and software change these risks are often delegated to specialised external parties. Common use cases are those of conveying information to a future self, e.g. calendars, diaries, tasks, etc. These applications, categorised as Personal Information Management (PIM) [4, p.
    [Show full text]
  • Data in Context: Aiding News Consumers While Taming Dataspaces
    DBCrowd 2013: First VLDB Workshop on Databases and Crowdsourcing Data In Context: Aiding News Consumers while Taming Dataspaces Adam Marcus∗ , Eugene Wu, Sam Madden MIT CSAIL marcua, sirrice, madden @csail.mit.edu { } ...were it left to me to decide whether we should have a gov- reasons: 1) A lack of space or time, as is common in minute- ernment without newspapers, or newspapers without a gov- by-minute reporting 2) The article is a segment in a multi- ernment, I should not hesitate a moment to prefer the latter. part series, 3) The reader doesn’t have the assumed back- — Thomas Jefferson ground knowledge, 4) A newsroom is resources-limited and can not do additional analysis in-house, 5) The writer’s ABSTRACT agenda is better served through the lack of context, or 6) The context is not materialized in a convenient place (e.g., We present MuckRaker, a tool that provides news consumers there is no readily accessible table of historical earnings). with datasets and visualizations that contextualize facts and In some cases, the missing data is often accessible (e.g, on figures in the articles they read. MuckRaker takes advantage Wikipedia), and with enough effort, an enterprising reader of data integration techniques to identify matching datasets, can usually analyze or visualize it themselves. Ideally, all and makes use of data and schema extraction algorithms to news consumers would have tools to simplify this task. identify data points of interest in articles. It presents the Many database research results could aid readers, par- output of these algorithms to users requesting additional ticularly those related to dataspace management.
    [Show full text]
  • From Web 2.0 to Web
    Web 2.0 and Web 3.0 and its Applications in Library Services Dr. Jagdish Arora Advisor, NBA Email: [email protected] Evolution of library technology (adapted from Noh (2012) Library 2.0 and Library 3.0 • Web 1.0 (Tims Berner Lee) • Semantic Web - 2001 (Tims Berner Lee) • Web 2.0 (Tim O'Reilly, 2005) • Web 3.0 John Markoff, New York Times, 2006) • Web 4.0 (Distant Dream?) • Library 2.0 coined by Michael Casey in 2006 • Library 3.0 • Library 4.0 This talk is addressed to: • Librarian 2.0 • Librarian 3.0 1996 (1 L W; 50 L U) 2006 (10 Cr W; 50 L) 2016 (100 Cr W; 250 Cr U) Web 1.0 to Web 4.0: Process of Evolution Subtitle comes here Web 1.0: Read Web 2.0: Read & Write Web 3.0: Read, Write & Web 4.0: Read, Write, /Awareness / Static (2006) Execute (2016) Execute & Concur (1996) • Web Connecting • Web Connecting • Intelligent interaction • Unidirectional / People / Human Knowledge & between machines and Passive transmission Centric Participative Intelligence users • Limited Interaction Web • Semantic Web: Web of • Internet of Things (IoT) with Users • Dynamic, Interactive Data; Virtual World • Human are upgraded with • No Content and Collaborative • Social Computing technology extension Creation Creation of Information Environment (Always On) • Social Networking • Multi-directional Sites (SNS) • Semantic connections • Bi-directional • Data filtered • AI Source: .... 6 Web 2.0 Web 2.0 is About Cultivating Communities . Shared Picture Shared Video Shared News Shared Shared Bookmarks Everything • SmugMug • YouTube •Digg • Photobucket •Twitter •MySpace • Vimeo •Redddit • Google Photos • Dailymotion •Pinterest •Facebook •Delicious • Snapfish • Twitch •StumbleUpon •Twitter •Grow News • Flickr • LiveLeak •Dribble •Friendster •Newsvine • ImageShack • Break •Orkut • Metacafe •Slashdot • Fotolog •Pocket •Snapchat Its About being in the User’s Space .
    [Show full text]
  • Principles of Dataspaces
    Principles of Dataspaces Seminar From Databases to Dataspaces Summer Term 2007 Monika Podolecheva University of Konstanz Department of Computer and Information Science Tutor: Prof. M. Scholl, Alexander Holupirek Abstract. This seminar paper introduces a concept in the area of data management called dataspaces. The goal of this concept is to offer a way to handle multiple data sources with different models as answer to the rapidly increasing demand of working with such a data. Management challenges like providing search/query capability, integrity constraints, naming conventions, recovery, and access control arise permanently, in organizations, government agencies, libraries, on ones PC or other per- sonal devices. Often there is a problem with locating the data and discov- ering the relationships between them. Managing data in a principal way will offer significant benefits to the organizations. The paper presents an abstraction for a dataspace management system as supposed by [1] and [2]. Specific technical challenges in realizing it are outlined and some applications are described. 1 Introduction and Motivation In many real life situations the users are often faced with multiple data sources and the arising management challenges across these heterogeneous collections. General problem is how to locate all the relevant data and how to discover rela- tionships between them. Having the data, they cannot be fitted into a conven- tional relational DBMS and uniformly managed. Instead, we have different data models, providing different search and query capability. The idea of dataspace is to provide base functionality over all data sources. On the administration side, these challenges include integrity constraints and naming conventions across a collection, providing availability, recovery and access control.
    [Show full text]
  • The Web of Linked Data
    WebDB 2010 June 6th, 2010, Indianapolis, USA The Web of Linked Data A global public dataspace on the Web Christian Bizer Freie Universität Berlin Christian Bizer: The Web of Linked Data (6/6/2010) Outline 1. Foundations of Dataspaces and Linked Data Where do they overlap? 2. The Web of Linked Data What data is out there? 3. Linked Data Applications What i s b ei ng d one with the da ta? 4. Remarks on Identity Self-descriptive Data Pay-as-you-go Integration Christian Bizer: The Web of Linked Data (6/6/2010) The Dataspace Vision Alternative to classic data integration systems in order to cope with growing number of data sources. PtifdtProperties of dataspaces may contain any kind of data (structured, semi-structured, unstructured) require no upfront investment into a global schema provide for data-coexistence give best-effort answers to queries rely on pay-as-you-go data integration Franklin, M ., Halevy , A ., and Maier , D .: From Databases to Dataspaces A new Abstraction for Information Management, SIGMOD Rec. 2005. Christian Bizer: The Web of Linked Data (6/6/2010) Dataspace Architecture Source: Franklin et al: From Databases to Dataspaces,Christian Bizer: The SIGMOD Web of Linked Rec. Data (6/6/2010)2005. Linked Data Principles Set of best practices for publishing structured data on the Web in accordance with the general architecture of the Web. 1. Use URIs as names for things. 2. Use HTTP URIs so that people can look up those names. 3. When someone looks up a URI, provide useful RDF information. 4.
    [Show full text]
  • The Use of Blockchain Technology for Private Data Handling for Mobile Agents in Human-Technology Interaction*
    1 The Use of Blockchain Technology for Private Data Handling for Mobile Agents in Human-Technology Interaction* Tim Uhlott, Thomas Kirks, Jana Jost1 Abstract—With the rising importance of automation and dig- face impairments and need support more often. In relation itization in the fields of logistics and production systems, society to Industry 4.0, it is straight-forward to represent the human is facing new challenges when it comes to human-technology worker by a virtual entity and let this entity support the worker interaction and the authority over personal data management. This paper proposes a method to use individual-related data by mitigating problems in place of him or her and adapt for process optimization and raise of acceptance of technology to specific situations. It makes sense to deploy these entities and at the same time keeping the data safe and giving the with human interface devices like wearables. Wearables and individual sovereignty over the use of its personal information. human interface devices available on the market today, offer In this work a multi-agent system is used for the integration many features, are quite powerful and appear in different types of humans in technical systems, where a special software agent keeps information about the dedicated human, like abilities and of variation, so that they are very useful interfaces for HTI. properties, and acts in favour of the human. To ensure the privacy There are smartphones, smartglasses and smartwatches, only of this data, the human can decide which data he wants to expose to mention the most common.
    [Show full text]
  • Quarrying Dataspaces: Schemaless Profiling of Unfamiliar Information Sources
    Quarrying Dataspaces: Schemaless Profiling of Unfamiliar Information Sources Bill Howe#1 David Maier∗2 Nicolas Rayner∗3 James Rucker∗4 #Oregon Health & Science University, Center for Coastal Margin Observation and Prediction 20000 NW Walker Road, Beaverton, Oregon [email protected] ∗Portland State University, Department of Computer Science 1900 SW 4th Avenue, Portland, Oregon [email protected] [email protected] [email protected] Abstract— Traditional data integration and analysis ap- existing applications and domain knowledge must be brought proaches tend to assume intimate familiarity with the structure, to bear to understand a source sufficiently to adapt it to semantics, and capabilities of the available information sources new needs. Our interest is dataspace profiling, analogous to before applicable tools can be used effectively. This assumption often does not hold in practice. We introduce dataspace profiling database profiling, which Marshall defines as “the process of as the cardinal activity when beginning a project in an unfamiliar analyzing a database to determine its structure and internal dataspace. Dataspace profiling is an analysis of the structures relationships” [8]. However, most database profiling tools and properties exposed by an information source, allowing 1) assume a starting point of relational data with a domain- assessment of the utility and importance of the information specific schema. In dataspace settings, however, the starting source as a whole, 2) assessment of compatibility with the services of a dataspace support platform, and 3) determination point may have no a priori schema, or only a generic one. and externalization of structure in preparation for specific data An example of the former is collections of entity-property- applications.
    [Show full text]
  • Building Internet of Things-Enabled Digital Twins and Intelligent Applications Using a Real-Time Linked Dataspace
    Chapter 16 Building Internet of Things-Enabled Digital Twins and Intelligent Applications Using a Real-time Linked Dataspace Edward Curry, Wassim Derguech, Souleiman Hasan, Christos Kouroupetroglou, Umair ul Hassan, and Willem Fabritius Keywords Decision support · Internet of Things · Intelligent systems · Smart environments · Energy management · Water management · Dataspaces 16.1 Introduction Smart environments have emerged in the form of smart cities, smart buildings, smart energy, smart water, and smart mobility. A key challenge in delivering smart environments is creating intelligent applications for end-users using the new digital infrastructures within the environment. In this chapter, we reflect on the experience of developing Internet of Things-based digital twins and intelligent applications within five different smart environments from an airport to a school. The goal has been to engage users within Internet of Things (IoT)-enabled smart environments to increase water and energy awareness, management, and conservation. The chapter covers the role of a Real-time Linked Dataspace to enable the creation of digital twins, and an evaluation of intelligent applications. The chapter starts in Sect. 16.2 with a description of Digital Twins and the role that Boyd’s OODA Loop can play in their realisation. Creating digital twins and intelligent application using a Real-time Linked Dataspace is detailed in Sect. 16.3. The results from the smart energy and water pilots are detailed in Sect. 16.4. Section 16.5 discusses experiences and lessons learnt, and the chapter concludes in Sect. 16.6. © The Author(s) 2020 255 E. Curry, Real-time Linked Dataspaces, https://doi.org/10.1007/978-3-030-29665-0_16 256 16 Building Internet of Things-Enabled Digital Twins and Intelligent..
    [Show full text]