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Education Data and SDMX

Education Data and SDMX. Towards Implementation of SDMX January 9 – 11, 2007, World Bank, Washington D.C. Introduction. Part of a broad UNESCO Institute for Statistics (UIS) effort to improve quality and timeliness UNESCO Responsible agency for international education statistics

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Education Data and SDMX

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  1. Education Data and SDMX Towards Implementation of SDMX January 9 – 11, 2007, World Bank, Washington D.C.

  2. Introduction • Part of a broad UNESCO Institute for Statistics (UIS) effort to improve quality and timeliness • UNESCO • Responsible agency for international education statistics • Responsible agency for International Standard Classification for Education Statistics (ISCED). • Scope of cooperative project on SDMX and Education • Administrative data collections (international data) • Shared processing among UNESCO, OECD, Eurostat

  3. Actors in the system of international education data collections • Who collects data: International agencies cooperating as data requester • UNESCO Institute for Statistics (UIS) • Scope: All countries world wide (200+ countries) • OECD • OECD member states, partner countries (34 countries) • EUROSTAT • EU Member, EEA countries, Candidate countries, Western Balkan countries (35 countries) • Who provides data: National agencies nominated by country • Ministries of Education (up to 3 different ministries!) • National statistical offices

  4. Instruments used in the system of international education data collections (I) • The UNESCO-UIS / OECD / EUROSTAT (UOE) Data Collection on Education Statistics • EXCEL based questionnaire, organized in 31 work sheets • 47 countries, 14,000+ data points • Processing of countries split by organizations • The World Education Indicators Project (WEI) • Based on UOE Instruments, extended by 10 work sheets • 16 countries , >15,000+ data points • Processed by UIS • Examples at www.uis.unesco.org/publications/wei2006 • The UIS Survey • Pdf based E-Questionnaire infrastructure, plus paper form • All remaining countries, 5,000+ data points • Processed by UIS • Examples at www.uis.unesco.org -> current surveys

  5. The world of international education data collections

  6. The world of international education data collections • Each of the international organizations has its own data and indicator release • OECD • Education at a Glance, • EUROSTAT • Key figures in Education, New Cronos • UNESCO Institute for Statistics • UIS Web dissemination • Global Education Digest • Distribution to third parties • Education for all, MDGs, World bank WDI, Human Development Index, ….

  7. Instruments used in the system of international education data collections (II) Can be transformed Can be transformed UOE WEI i ii i i i i UIS

  8. The UOE - Collect together, disseminate separately • The UOE data requester • design the questionnaire in cooperation • Co-ordinate the e-mail dissemination of instruments • National agencies submit completed forms to a joint e-mail address, that forwards data to the 3 data requester • OECD processes OECD countries; EUROSTAT processes residual EU-interest countries; UIS processes residual countries • The UOE data requester • exchange processed data • produce and review statistics separately • release results

  9. Collect together, disseminate separately Data Processing Calculation and Dissemination OECD OECD Country EUROSTAT E-mail hub Processed data UIS UIS

  10. Challenges • Communication with countries • Updates • Countries submit updates to one or more organizations • Version control • Integration with already processed data • Data Verification and quality assurance • Different organizations focus on different sub-sets of data for their publications: Data verification is inconsistent and of different intensity for different sub-sets. • Punctuality • Different organizations work on different schedules: data are not readily processed by one organization for punctual use by another

  11. Challenges • IT • Handling of different and ever changing Instruments • Transformation of UOE data to UIS data • Dissemination • Different methodology in calculation of similar indicators • Use of different economic or population data for identical statistics

  12. What would an SDMX solution look like? • Why SDMX? • Implications for stakeholders • The data provider • The international agency receiving and processing the data • The other two international agencies dependent upon the data • The consumer (international report, international agency)

  13. Impact on Data Providers

  14. Impact on International Org. receiving the data

  15. Impact on International Orgs (2)

  16. Impact on the users of Statistics (external) • No visible or obvious changes from a data management perspective; • Data will have greater coherence across agencies; • Metadata will be more available; • Concepts and methods should be more harmonious; • Data will be of a higher quality; • Timeliness will be improved;

  17. The Data Structure Definition(s) • All education questionnaires and education outputs are being looked at and a conceptual data model is being developed; • The objective is to create a single DSD for all international education statistics (adhering to relevant standards);

  18. Is there a Business Case? • Elimination of redundant and possibly inconsistent data • Improvements to timeliness and quality; • Efficiency gains – reallocation of resources to functions providing higher value • IT investment costs will be somewhat offset by elimination of other ongoing costs supporting the current environment; investment considered strategic • Our role in the international statistical system imposes upon us the need to work on a DSD for Education. Risks • The technical risks are low. The IT aspects have been done before with other SDMX projects – and are generally not unique to SDMX. • This is the first social statistics project for SDMX. • The necessary changes to business processes may be difficult to effect.

  19. Future Plans? • UNESCO dissemination via SDMX to key institutional stakeholders in 2008 • Transform the current dissemination model from a ‘push’ model to a ‘pull’ model.

  20. Thanks Brian Buffett (b.buffett@uis.unesco.org) & Michael Bruneforth (m.bruneforth@uis.unesco.org)

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