1. MetaPlus Klas Blomqvist Statistics Sweden Research and Development – Central Methods klas.blomqvist@scb.se

2. Agenda The VHS-project –Background MetaPlus –The concepts, the product KMI-group –Support and management for classifications, metadata and content harmonisation The Lotta project, process reengineering at Statistics Sweden –A more effective production process –MetaPlus, future development MetaPlus and the production process

3. Why do we need metadata?

5. Metadata at Statistics Sweden SCBDOK –Word template, standardised structure free text description MetaPlus (Metadok) –Formalized metadata, coded information KDB, the classification database –Statistical standards and classifications Other documentation –Description of the statistics – the quality declaration –Product database –Private production documentation

6. The VHS-project The VHS-project started 2004 –Compilation of requirements: Metadok, new requirements Systems design from 2005 –Use cases, modeling System development 2006 –Application, data base Production 2007 –From January 2

7. MetaPlus Replace Metadok Scope: –Documentation tool with improved quality –Better overview over variables and data –Tool for standardisation and harmonisation –Possibilities for reuse and coordinated use –Consecutive documentation Requirement: –That the documented material in Metadok can be migrated

8. Information User groups The Metadata group (reference group) The methods council The IT council The register council The board of directors The scientific council Seminars

9. The plus with MetaPlus Support for the production –Cooperation with other metadata systems, Archiving, the Personal Data Act, connection to data User support –Search the microdata Improved quality –Contents, accessibility and comparability More cost-effective –Increased use of collected data Reduced respondent burden –No new collection if data already exists

10. Easier to document Starting point in already existing metadata –Classifications and standards –Documentations made by others –Search the metadata repository Document once - reuse Input data in the form of tables –Document the table at once instead of one cell at a time Consecutive documentation Effects: –Higher metadata quality –Automatic harmonisation

11. Using MetaPlus New requests (commissions), new surveys –Examine if the issue can be solved with already existing data. Information for facilitating coordinated use and harmonisation Search for variables –Look at value domains Find information on populations –Shows possibilities for matching data –Highlights differences in data materials

12. Content Standard variables Variables Object classes Classifications and value domains The survey’s registers Survey population and register population

13. The model Object class Value domain Context Population Variable Population Context variable Object variable Register Register version Register variant Conceptual value domain Value

14. Object class Population Variable Value domain Register variant Register version Column Database/ file The application structure Can be reused Content oriented IT- oriented Unique for the survey round

23. MetaPlus functionality, some examples Documentation Reuse Harmonisation Administration Classifications Variable groups Personal Data Act Administration System Advanced search Longitudinal registers Time series Historical information Archiving Web prototype

24. The KMI-group Research and Development department, all units represented –Management, Central Methodology, Register coordination and microdata and Central IT units Responsibilities –Classifications –Metadata –Content harmonisation MetaPlus support –Migration, training, helpdesk

25. The Lotta project Standardised production and tools –Process orientation –Customer focus –Efficiency –Standardisation –Quality control New organisation after summer –Internal review during summer

26. The Statistical Production Process Target,cust.demFrame and sample Data collection Data preparation Statistical computation Dissemination and communication Evaluation/ cust.satisf. Assessment Survey design The colours relate to potential areas for process ownership Customer contacts Tender/agr. Technical preparations Documentation preparations Compilation of frame Sampling Administrative registers Direct data collection Other primary statistics Coding Editing Corrections Data delivery Estimations Production of tables and diagrammes Statistical analysis Dissemination Data dellivery To customers Archiving Customer reactions Analysis of Process data and customer reactions Feed-back to the production process Identification of data sources Compilation of results Internal evaluation, quality control General for all processes: Deliveries between processes Process dataMeta dataSystem architect.Keeping of reg. Treatment of Time series breaks Prognosis Simulation models Cont.,predesign Level1Level1 Level2Level2

27. MetaPlus in the Statistical Production Process Target,cust.dem Frame and sample Data collection Data preparation Statistical computation Dissemination and communication Evaluation/ cust.satisf. Cont.,predesign MetaPlus Internal evaluation, quality control General for all processes: Deliveries between processes Process dataMeta dataSystem architect.Keeping of reg. Treatment of Time series breaks

28. Conclusions Reuse Harmonisation and standardisation tool MetaPlus 1.2 in production Organization (the KMI-group) Content – slow progress The End!