1. International digital data management and sharing initiatives in the social sciences Peter Elias University of Warwick, England Presentation to the First African Digital Curation Conference Pretoria, 12 – 13 February 2008

2. Why do we need to share data? To address research on issues of global importance: (e.g. poverty; migration; economic growth and development; spread of infectious diseases; environmental change; response to natural disasters; threats to security) To facilitate international research collaboration To make best use of limited resources To exchange skills and knowledge about the use of research data To engage in comparative research

3. Macro vs. micro data Macro data are aggregates of micro data (where the unit of observation is the individual, household or organisation). Macro data are helpful in guiding the development of research and policy (e.g. trend analysis). Considerable progress has been made in providing access to international macro data.

4. Macro data access and mapping UK Economic and Social Data Service International UK Economic and Social Data Service International Web based tools for data presentation and mapping: – www.gapminder.org www.gapminder.org – www.worldmapper.org www.worldmapper.org

5. World map – land areas Territory size is shown proportional to surface areas of territories. Source: www.worldmapper.org

6. Infant mortality 2002 Territory size shows the proportion of infant deaths worldwide that occurred there in 2002. Infant deaths are deaths of babies during their first year of life. Source: www.worldmapper.org

7. Carbon emissions 2000 Tonnes of carbon dioxide emitted per person living in that territory in 2000 Source: www.worldmapper.org

8. Macro vs. micro data Micro data contain more useful variation than micro data. Micro data are more amenable to quality investigation and control. Micro data are more flexible as research data – they permit the analyst to reconstruct aggregates in different ways or to reclassify the information they contain. Micro data can be classified according to source: – censuses; surveys; administrative systems; transactions

9. What mechanisms for sharing micro data already exist? Sharing survey data: International Household Survey Network Census data sharing: Integrated Public Use Microdata Series — International (IPUMS International)IPUMS International Developing common surveys: Demographic and Health Surveys European Social Survey World Values Survey International Social Survey Programme International Social Survey Programme Longitudinal surveys of ageing (SHARE, ELSA, HRS) Sharing archives Council for European Social Survey Data Archives Inter-university Consortium for Political and Social Research

10. Need to improve knowledge about data and metadata Need to promote cross-disciplinary research Need to resolve problems of access to data deemed ‘sensitive’ or subject to ethical safeguards Need to gear data development to international research needs What else needs to be done to improve data sharing?

11. In 2002 the US National Science Foundation and the UK Economic and Social Research Council agreed to seek ways to improve international collaboration in the social, behavioural and economic sciences After preparatory work by the Social Science Research Council, six countries agreed to fund a major conference in Beijing (www.internationaldataforum.org)www.internationaldataforum.org Conference agreed to prepare plan for a new International body – the IDF The NSF/ESRC initiative

12. Plans to establish the International Data Forum Scientific committee has met twice (representatives from 9 countries and the ISSC) Proposal for IDF ready by May 2008 If accepted, launch of IDF at World Social Science Forum in May 2009

13. What would the IDF do? Data discovery Improving knowledge about existing data opportunities – worsening because of data deluge Data collection Working with research funders and research communities to identify gaps in data collection for research across national boundaries Data management Promoting efforts to build standards based data and metadata management processes into the data lifecycle; introduce interoperability and make it cumulative Data dissemination Identifying obstacles to data sharing, seeking to remove these and making data available to researchers Data re-purposing Promoting innovation in ways of re-using data