“COD CONSULTANCY” REPORT Jenny Bredin, UNHCR, 2011-09-09

Introduction The initial consultancy for a 6 months period during November 2010 – April 2011, was extended with additional 3 months, ending August 2011. The Terms of References covered two projects: Activity A: Support to the definition of the Common Operational Datasets (CODs) in Disaster Preparedness and Response, and of the basis of a related UN Humanitarian Data Model. Activity B: Facilitating the UNHCR Innovation and ICT in Refugee Settings Initiative.

The two activities being of different nature and having different stakeholders, there is no common deliverable.

This report covers activity A only. It aims at summarizing the different activities undertaken, refer to material and persons consulted, and give an overview of the outcomes and to propose next steps. Some contents have been copied from material prepared by other COD working group participants. The reason why is that some of the descriptive texts and even illustrations are results of an important amount of collaborative work which would be altered or lost by rephrasing.

It should be noted that the contents of this report correspond to the consultant’s individual understanding of the subject area; it does not represent the standpoint of any UN organization or body unless stated so in official reference documents.

I wish to thank everyone who contributed to this work, but especially each one of you listed under the annex chapter “Contact persons - Humanitarian Profile - Core group”

Terms of Reference The consultancy’s ToR for the part “Support to the definition of the Common Operational Datasets (CODs) in Disaster Preparedness and Response, and of the basis of a related UN Humanitarian Data Model” include to define the data sets, create metadata and set the basis of a humanitarian data model. The key activities were:  Inventory of existing and relevant data model or data structure  Survey of the IASC members on their relevant initiatives  Definition of initial core datasets of the model  Development of high level data model  Creation of a demo dataset The deliverables defined were:  Inventory and assessment of tools to be considered as building blocks to the model  Survey results on existing initiatives of IASC members  High level data model in a format to be agreed upon with FICSS  Demo dataset Context In November 2010, IASC endorsed the guidelines “Common Operational Datasets and the Fundamental Operational Datasets” 1.The IASC Information Management Task Force was and finalizing a review2 on the "IASC Operational Guidance Note on Information Management" and reviewing a report for the Review of the Inter-Agency Web Platform “OneResponse”3. In the same period the UN Secretariat Chief Information Technology Officer (CITO) Office expressed their intentions to develop an overall database (a distributed system close to the source) of datasets, for all Member States, that would span from COD to more development related datasets. The CITO Office is therefore interested in cooperating with the Task Force on COD.

In the beginning of the consultancy, UNHCR proposed the consultant’s services to IASC Information Management Task Force. At the time there was an urgent need to standardize the estimation of the humanitarian caseload and as a part of this effort, to develop more detailed guidance for the COD “Humanitarian profile” (see definition in the section below). It was agreed that the consultant should assist IASC IM TTF in this effort rather than focus on the initial Terms of Reference as defined by UNHCR.

On an IASC IM TF meeting held on 21 January 20114, the TF sub-group on datasets introduced Ms. Jenny Bredin from UNHCR as the focal point for the work on definitions and the humanitarian profiles related to the endorsed COD.

Background

CODs and FODs The Common Operational Datasets (CODs) are critical datasets that are used to support the work of humanitarian actors across multiple sectors. They are considered a de facto standard for the humanitarian community and should represent the best-available datasets for each theme.

The definition for Common Operational Data Sets (CODs) according to the COD guidelines is found in the box below.  “Common Operational Datasets are predictable, core sets of data needed to support operations and decision-making for all actors in a humanitarian response.  Some of the CODs, such as data on the affected population and damage to infrastructure, will change during the different phases of the response and therefore will need to be frequently updated and maintained.  Other CODs, such as rivers and village locations, are likely to remain the same throughout the response.  The CODs are proactively identified and maintained prior to an emergency as part of data preparedness measures and made available by the OCHA (or pre- agreed in-country alternate) within 48 hours of a given humanitarian emergency.

1 “ IASC Guidelines Common Operational Datasets (CODs) in Disaster Preparedness and Response”, IASC Endorsed November 1 2010. 2 “REVIEW OF THE OPERATIONAL GUIDANCE NOTE ON INFORMATION MANGEMENT”, Dr. Bartel Van de Walle, 2010. 3 ”Inception Report - Review of the OneResponse Inter-Agency Web Platform”, Glenn O’Neil, October 2010. 4 IASC Task Force on Information Management - Draft Summary Note - 21 January 2011  All CODs must meet minimum criteria for format and attribute information in accordance with national standards.”

The Fundamental Operational Datasets (FODs) are datasets that are relevant to a humanitarian operation, but are more specific to a particular sector or otherwise do not fit into one of the seven COD themes.

The definition for Fundamental Operational Data Sets (FODs) according to the COD guidelines is found in the box below.  Fundamental operational datasets are datasets required to support multiple cluster/sector operations and complement the common operational datasets.  These datasets are characterized by thematic areas (such as education facilities) and are made available as soon as possible after the onset of an emergency given availability.

There is seven Common Operational Datasets defined in the IASC Guidelines on Common Operational Datasets in Disaster Preparedness and Response. Five of them are geographic data sets, meaning that they represent features having a geographical representation. These features might be physical (such as transportation network or hydrography), i.e. you can identify them in the terrain, or conceptual features such as boundaries of administrative units.

The two remaining datasets concern the population; they have no geographic representation in themselves, but are linked to administrative units or populated places.

The illustration below groups the CODs according to their geographical aspect.

The table on the following page is an extract from the IASC Guidelines on Common Operational Datasets in Disaster Preparedness and Response. It briefly introduces recommended governance and mandatory data characteristics for each of the CODs. Recommended Dataset Mandatory Data Characteristics Governance - Internally Displaced5 - Non-displaced affected - Guardian: OCHA - Host family/resident community affected Humanitarian Profile - Sponsor: OCHA (disaggregated by admin level and - Refugee6 populated place) - Source: Government, Assessments, UNHCR - Dead - Injured - Missing - Total population by admin level (Individuals) - Guardian: OCHA -Total population by admin level - Sponsor: OCHA,UNFPA (Other (Number of Households) Population Statistics potential sponsors could include - Age UNDP, Government agencies or - Sex INGOs) - Average family size by admin level - Source: Government - Unique identifier Administrative Boundaries - Guardian: OCHA (Geographic) - Sponsor: OCHA (Other potential - Unique identifier (P-Code) admin level 1 sponsors could include UNDP, - Name admin level 2 Government agencies or INGOs) admin level 3 - Source: Government admin level 4 - Unique identifier (P-Code) - Guardian: OCHA - Names - Sponsor: OCHA, (Other potential - Size classification Populated Places sponsors could include UNDP, - Population statistics (Geographic) Government agencies or INGOs) - Status if capital of administrative division - Source: Government - Type (Village, spontaneous settlement, collective center, planned settlement) - Roads (Classified by size) - Guardian: OCHA - Railways Transportation Network -Sponsor: Logistic Cluster (Geographic) - Airports/helipads -Source: Government - Seaports - Guardian: OCHA - Sponsor: OCHA (Other potential - Rivers (Classified by size) Hydrology sponsors could include UNDP, (Geographic) - Water bodies Government agencies or INGOs) - Source: Government - Guardian: OCHA Hypsography - Sponsor: UNOSAT -Elevation (Geographic) - Source: Remote sensing, -Resolution Government

5 As defined in the UN Guiding Principles on Internal Displacement UN Doc. E/CN.4/1998/53/Add.2 6 As defined in Refugee: Article 1, The 1951 Convention Relating to the Status of Refugees The Humanitarian Profile COD The humanitarian profile is fundamentally an attempt to account for, on an ongoing basis, the number of people having humanitarian needs arising from a given emergency. It can be thought of as humanitarian caseload. It is essentially a count of the number of “affected” people in the emergency. Because people may be affected in many different ways by an emergency, different groups are identified within the humanitarian profile, such as displaced, non-displaced, injured, missing, and dead.

The humanitarian profile dataset is unique among the common operational datasets in its operational importance to the humanitarian community, the dynamic nature of its data and the way its composition may vary according to the operational context and priorities of a particular emergency. The humanitarian profile includes the numbers of affected, missing, dead, and injured persons, where the affected category has sub-groups of importance for humanitarian response. The purpose is to provide, in a predictable way, numbers that can facilitate humanitarian planning and needs assessment7

The COD and FOD web-based registry In parallel to this consultancy, many related activities have been ongoing. OCHA has with support of ICT for Peace Foundation developed a web-based registry where available CODs and FODs are disseminated. The URL is http://cod.humanitarianresponse.info/ In addition to disseminating data, the registry web-page also aims at providing guidance on specific COD themes, one part of the result of the work on the humanitarian profile guidance described below can be found at http://cod.humanitarianresponse.info/node/52#overlay- context=node/53

Detailing guidance for Humanitarian Profile COD

Scope and deliverables On 21 January, members from the IASC IM TF proposed an activity aiming at providing more detailed guidelines for the COD humanitarian profile, covering:  Governance of COD HP dataset in field operations  Methodologies for deriving COD HP dataset including existing management tools  Definitions of Mandatory Data Characteristics The final deliverables are ambitious and cover:  2 pages Overall Guidance on the HP dataset  Annex of definitions for Mandatory Data Characteristics  Support package The purpose being to agree on definitions and a methodology or approach in defining the profile of the population affected by a disaster or conflict.

7 “IASC Operational Guidance for Coordinated Assessments in Humanitarian Crises” http://oneresponse.info/resources/NeedsAssessment/publicdocuments/Operational%20Guidance%20for%20Endorsement%20-%20%20Final%20Version.pdf Participants A core group of about 10 persons, from different UN Agencies and NGOs, worked on the humanitarian profile guidance between February and June 2011. 15 additional persons were invited to contribute. See details in Annex – Contact Persons.

Working methodology

Information collection from IASC IM TF members On an IASC Information Management Task Force (IM TF) meeting on 21 January 2011, IM TF members were encouraged to provide feedback on best practice from the field concerning governance, tools and mechanisms, and definitions related to the humanitarian profile of the COD. The following material was requested:  Summaries of how this dataset was managed in emergencies;  Tools that your agency has used to manage this data set;  Methodologies your agency has used to calculate this dataset;  Governance examples which have worked in field operations; and  Any other pertinent documentation

Only about 5 “best practices” were returned as a result of this request (see Annex – Best Practices), most of them from OCHA’s IMOs. These examples cover a wide range of aspects of humanitarian profile data management such as:  Data collection with specific methods when no physical access to the area is available;  An example of a portal for information sharing;  The use of proxy indicator to estimate the affected population by measuring anther, related indicator, such as destroyed habitat; and  A successful governance model.

Reference Material Most of the reference material for population estimation collected has been provided by Patrice Chataigner, ACAPS. In total, about 20 documents (see Annex – Reference documents) have been collected. In addition JIPS has a document repository with a larger scope, which is a part of the “Profiling Resource Kit” (PRK).

Contacts with researchers A couple of academia experts active in fields related to population estimation were contacted in March 2011. Eventually, none of them replied to the email message asking them if they were available to either provide direct input or guidance to what material to consult in order to help IASC to produce the specific guidance for the humanitarian profile.

However, Francesco Checci at London School of Hygiene and Tropical Medicine, with whom the consultant has personally met, has been very helpful. From this it might be concluded that it might be easier to achieve results from personal contacts and that other researchers could be approached again, by someone they know or can relate to. Findings

Mandatory data characteristics The mandatory data characteristics in “ IASC Guidelines Common Operational Datasets (CODs) in Disaster Preparedness and Response”, were used as a starting point:  Internally Displaced  Non-displaced affected  Host family/resident community affected  Refugee  Dead  Injured  Missing

It was found that not all the listed “classes” were mutually exclusive, e.g. the same person could be “Refugee” and “Injured”. It was also found that not all “classes” had well recognized definitions.

Going through many CAP (Consolidated Appeal Process) and Flash Appeal documents also showed that there is no standard for how to classify “affected population” between operations; it is highly depending on the context. Different bodies might have different classifications and even in the same context, in the same humanitarian operation, it might evolve over time, in particular to allow for more detail.

It was concluded that a refined version of the mandatory data characteristics for the humanitarian profile COD. The “core-group” proposed a classification system, with one mandatory part and one more detailed, but optional, part. One important difference is that it is now clear how the different classes add together. Double counting and/or omission should more easily be avoided by applying this system. Clear definitions of each term have also been agreed upon.

The details are documented in the IASC Guidelines on the Humanitarian Profile COD8, the illustration on the next page represents the classification system.

It should be noted that the guidance concerning governance of the Humanitarian Profile COD recommends choosing the humanitarian profile classes that are appropriate to the emergency and adjust definitions if needed.

8 IASC Guidelines on the Humanitarian Profile Common Operational Dataset 2011-05-20.doc Population estimation “tool-kit” Even though the humanitarian community and academia have a lot of experience of estimating the population affected by an event, there is currently no repository for population estimation methodologies, nor any guidance of which method to use in which context.

A system for tagging documents has been considered, but not finalized. One reason is that in May 2011, it was discovered that Joint IDP Profiling Services (JIPS) is developing a similar “tool-kit” and that it would be useful if not to integrate the two, at least to collaborate around certain aspects of the repositories.

Examples of relevant tags could be; region name, country name, Agency/Organization, Humanitarian Profile Class, Emergency phase, Estimation Methodology Type, Data Collection Type etc.

An attempt to tag the material collected shows that many documents would have the same tag, for example ”random sampling”. A search for documents covering “random sampling” would then return all documents. It was concluded that it is not evident how to tag this material and create a tool that will actually facilitate the users’ search for material relevant to their case.

The request for “best practices” did not result in many examples, OCHA proposed to contact further persons known to have experience in this field. For this purpose it has been judged useful to develop a template, so that each example will have the same sections and be more easily comparable.

Amongst the collected material, there are very few evaluations estimating the quality of different population estimation methodologies and their applicability in different contexts. An attempt was made to develop a “decision tree”, that depending on the context will propose a specific method for population estimation. Disaster type, Access to baseline data, Physical Access to area, Available satellite imagery and necessary skills etc. would be part of questions in such a decision tree.

It was found that estimation of affected population is done in so many different contexts, that even if not each situation is unique, there is at least a multitude of possibilities. One suggestion is to abandon the decision tree for the moment and instead develop scenarios. Some of the most common types of context would be described and estimation methodologies well adapted to the circumstances proposed.

Recommendations The main recommendation is to pursue the development of a humanitarian profile support package.

Case studies  Develop template for documenting best practices with standardized headings  Continue collection of best practices  Develop standard scenarios for “humanitarian response situations” that could work as a cook book, providing the standard “recipe” for how to manage humanitarian profile data in a specific situation.  Collect information on the quality and relevance of different estimation methodologies. There are many different methods described, but little about how good they are. If there are no such studies, the humanitarian community might want to consider the initiating collaborative research activities, with relevant academic institutions, in this field.

As input for this, the status of a research project supervised by Francesco Checchi, Faculty of Infectious and Tropical Diseases should be checked. A student was to write a thesis on the subject during summer 2011. Note that Patrice Chataigner, ACAPS might probably already have restarted the exchange on this subject.  Eventually pursue the development of a decision tree, guiding the decision of which estimation methodology to use  Publish best practices and scenarios

Document repository  Pursue collaboration with JIPS, especially on tagging of reference material  Complete a firs version of tagging standards  Tag collected material  Publish tagged, reference material in a tool providing search capacities

Other  Concerned organizations should include training on the specific guidance on the Humanitarian Profile COD in relevant Information Manager trainings and learning programmes.  To raise awareness on the fact that there exist guidance and standards on estimation of affected population, a general , less detail, training could be included in general emergency training, for all staff profiles.  The current guidance mainly covers “immediate response” or the “acute” phase of an emergency. It should be enriched with more specific guidance on how to prepare during a “pre-crises” or “preparedness” phase and how to continue “after the immediate response” or during a “chronic humanitarian crisis situation” and a “post crisis” phase.

Annex – Contact persons

Humanitarian Profile - Core group Surname Name Organization Email Gornall Shelley UNHCR [email protected] Hendrix CJ OCHA [email protected] Holladay Simone Amimba UNHCR/JIPS [email protected] Bredin Jenny UNHCR [email protected] Nunes Nuno IOM [email protected] Patragallos Samuel WHO [email protected] Roberson Kimberly UNHCR [email protected] Baker Leila UNFPA [email protected] Chataigner Patrice ACAPS [email protected]

Humanitarian Profile - Reference group Surname Name Organization Email Czaran Lorant UNOOSA [email protected] Bjorgo Einar UNOSAT [email protected] Sartori Giorgio WFP [email protected] Peugeot Heidi UNICEF [email protected] Abdalla Jihad UNICEF [email protected] Kastlander Erik OCHA [email protected] McDonald Brendan OCHA [email protected] Pron Nicolas UNICEF [email protected] Holen Runar UNICEF [email protected] Ulgen Suha UN CITO [email protected] Verity Andrej OCHA [email protected] Cottray Olivier IMMAP [email protected] Wilkening Soren OCHA [email protected]

Humanitarian Profile – Additional contact persons Surname Name Organization Email de Radigues Xavier WHO [email protected] Universiteit olivier.degomme@uge Degomme Olivier Gent nt.be L'Université catholique de [email protected] Hoyois Philippe Louvain cl.ac.be Johns Hopkins Robinson Courtland University [email protected] Annex – Best practices Tools Methodologies Governance JIPS JIPS JIPS OCHA PAK • Affected Population data shared on website OCHA YEM • Inaccessible area • Estimation of affected population with Remote Sensing IASC Clusters PHL • All clusters had IM focal point • IM network was tasked by Cluster Coordinator to get all clusters to appoint focal points and attend meetings OCHA Proxy indicators such as the number of houses partially and totally destroyed indicating number of people affected. OCHA ZAF • Flooding • Estimation of affected population with GIS Annex – Reference documents Numbe r Typ Issue of Languagu File name e Document title Author year pages Description e 1996 WHO A modified cluster PDF A modified cluster sampling WHO 1996 7 A cluster-sampling method providing estimates for the EN sampling method for post disaster method for post-disaster rapid population remaining in a disaster affected area, the RAN assessments of needs number of people with specific needs within this area.

2003 CIEDRS Demographic PDF Demographic Methods In CIEDRS 2003 196 Guide for field-based organizations conducting EN Methods In Emergency Assessment Emergency Assessment - A Guide assessments CIEDRS For Practitioners 2003 ECLAC handbook PDF Handbook for estimating the ECLAC 2003 16 Estimating the population of affected areas with EN socio- economic and Redatam, a software package allowing to use and environmental effecs of disasters process population data and structure it into user defined geographical hierarchies.

2005 Are rapid population estimates PDF Are rapid population estimates Rebecca F. 2005 12 Field trial comparing T-square and quadrat sampling EN accurate accurate? A field trial of two Grais et al. methods. different assessment methods

2005 WHO Estimating population PDF Bulletin if the World Health WHO 2005 1 Overview of population estimatinon methods. EN size in emergencies Organization, March 2005, Estimating population size in emergencies 2006 ECLAC Estimating affected PDF ECLAC 2006 Extract of 3 EN population with GIS

2007 Estimating population at risk PDF Estimating Population risk for WHO 2007 10 Case study of the use of GIS/remote sensing (Shuttle EN for coastal disasters coastal disasters using spatial Radar Topographic Mission global elevation data, models with global data SRTM) and population data (Gridded population of the World, version 3, GPWv3 and the Global Rural-Urban mapping project, GRUMP)was used to estimate population in risk for coastal disaster

2007 IFRC Public Health guide for PDF The John Hopkins and IFRC IFRC 2007 42 An overview of key epidemiological principles and EN emergencies Public Health Guide for tools needed in managing emergency public health Emergencies programs. 2008 HPN Public health in crisis- PDF Humanitarian Practice Network - HPN 2008 64 The risks to health inherent in crises, and the potential EN affected populations Public health in crisisaffected for impact of health interventions, using the language of populations - A practical guide for epidemiology. decision-makers

2010 UNICEF Rapid assessment PDF Rapid Assessment Sampling in UNICEF 2010 36 Key points and principles to take into consideration EN sampling in emergencies Emergency Situations when carrying out a rapid assessment in an emergency situation 2010 WFP Pakistan Flood Impact PDF WFP Pakistan Flood Impact WFP 2010 28 WFP impact assessment on floodings in Pakistan 2010. EN Assessment Assessment - September 2010 Based on a WFP Initial Vulnerability Assessment (IVA) and Multi-cluster rapid assessment mechanism