1 SHARING DATA: Lessons from IOM’s Data Sharing Mechanism in Eastern Europe and Central Asia UNECE Regional Workshop on international migration statistics Geneva, 4 – 6 December 2007 Jobst Koehler Research Officer, IOM

2 Why sharing data? Challenges to obtain data for migration management: different levels of development in infrastructure different practices of data collection different understanding of migration-related data variation in human and financial capacities There is a need for a “bottom-up” approach

3 Sharing data: What’s is in a name? Data-sharing is a « bottom-up » process to improve data that is : Democratic States determine own indicator Flexible States determine own pace Simple Share available data No major financial investments Convergence rather than uniformity is the aim.

4 IOM and International Data-Sharing IOM assisted data-sharing processes in different regions : Statistical Information System on Migration in Mesoamerica (SIEMMES) Caribbean Community (CARICOM): Collection and Sharing of Migration-Related Data in the Caribbean But most relevant for meetg : Data-Sharing Mechanism (DSM)) in Eastern Europe and Central Asia /The Programme for the Creation of a General Model for Collection, Application and Sharing of Migration-Related Data (“General Model)

5 IOM Research An approach to data management at national and regional level (applicable to any region ) that is based on the premise that: Level of development in migration data management varies Certain data exists but is not shared within and between states Producers and users should be connected. Dual track approach at the national and regional level is needed. “General Model”: What is it?

6 IOM Publications Main elements at the national level: Establishing a network of core institutions Mapping out existing national statistical infrastructure Establish an agreed minimum set of 5-10 aggregated overall data indicators plus documentation “General Model”: how does it work?

7 Organization Main elements at the regional level: Efficient electronic exchange mechanism Organizing regional workshops Addressing national needs through training modules “General Model”: how does it work?

8 DSM was a pilot test of the Programme for the Creation of a General Model for Collection, Application and Sharing of Migration-related Data, developed at IOM-OSCE workshop at Prague, 2002 Ended in 2006 Funding :OSCE-ODIHR, Danish Government, IOM and PRM Consistent Participants: Ukraine, Republic of Moldova, Kazakhstan Publication: “Sharing Data: Where to Start”, edited by Folden, Manke and Mortensen Applying the General Model: DSM in EECA

9 Potential New Areas of Research Creating a national network of institutions producing migration data: Choose a focal point from each agency and ensure continuity in the event of staff rotation Nominate a national coordinator and contact point for international inquiries Link data producers and users in a single national network Legislative framework to make network sustainable Lessons from DSM: “Know your Counterpart”

10 Training Objectives Lessons from DSM: “Work with your counterpart” Establishing an Inter-Ministerial Working Group (IMWG) to prioritize activities: Include decision-makers Create a clear structure and mandate for IMWG

11 Training Outputs Lessons from DSM: “Know Your Data” Mapping out existing infrastructure (sources and types of data) Make meta-data simple and comprehensive for policy-makers

12 Identify the national demand for indicators Prioritize and agree on a minimal set of statistical indicators Provides the basis for regular reporting Lessons from DSM: “Know your Needs”

13 Tools IT and Workflow assessment of the different stages of data management: Collection Storage Aggregation Dissemination Targeted IT upgrading. Lessons from DSM: “Know your Gaps”

14 Tools Training and “Train the Trainer” courses Encourage the process of self-learning through e-learning Raise training capacities of government officials Lessons from DSM: “Know your Skills”

15 Tools Data Base and Web Portal (DSM) is unique: New software created for the end-user after the review of ten regional based databases. DSM allows for several data-collection methods: through focal points or user-prompt mode, on paper; or via Excel charts. More than just data, a tool for policy and legal exchange (e-library). Hierarchical data access ensures data ownership Interstate Exchange and Regional Dialogue

16 Tools Regional Dialogue: Technical meetings Thematic meetings Study Tours Interstate Exchange and Regional Dialogue

17 Tools DSM in comparative perspective Interstate Exchange and Regional Dialogue Data Sharing Mechanism (DSM) in Eastern Europe and Central Asia (CIS countries) Statistical Information System on Migration in Mesoamerica (SIEMMES Aim To serve as a tool for migration-related data collection, application and exchange in the region. Mechanism is also used to share legal and policy information on migration. To monitor migration movements in, out and among Central America national and facilitate regional migration- related policy making. Type of Data Based on official data, data on non-nationals in total population, entries and exits of foreigners, work permits, applications for asylum and decisions International migration flows (arrivals and departures by sex, border station, age and nationality). Extra-regional emigration, population impact on destination countries and countries of origin, immigration in the region, remittances.

18 Tools DSM in comparative perspective Interstate Exchange and Regional Dialogue Data Sharing Mechanism (DSM) in Eastern Europe and Central Asia (CIS countries Statistical Information System on Migration in Mesoamerica (SIEMMES) Sources of Data Registers, entry and departure records, population censuses and household survey. Arrival and departure records, national population censuses and household surveys. Access to Data Restricted to participating states. Selected data and information to be made public Public

19 Tools Data-sharing is particularly an effective tool when: resources are limited and vary among states Some data exists Conditions for success: Data-sharing process needs to be integrated in the administrative structure Commitment at the State’s decision- making level Conclusion: how to make data-sharing effective? Interstate Exchange and Regional Dialogue