1. 1 1 Improving interoperability in Statistics Some considerations on the impact of SDMX 59th Plenary of the CES Geneva, 14 June 2011 Rune Gløersen IT Director Statistics Norway

2. 2 Contents The characteristics of processes and data at NSIs Applicable standards for various business processes The preconditions for increased interoperability A top-down approach to further standardisation SDMX as part of the industrialisation of statistics

3. 3 3 GSBPM – leaving stove pipes

4. 4 4 Data archiving

5. 5 Specify needs DesignBuildEvaluate Quality Management/Metadata Management Process stages and data archiving Data archiving spans the 4 main business processes, and comprises 4 steady states of the data life cycle

6. 6 Dissemination of aggregated statistics using SDMX SDMX Conversion SDMX Common Architecture Can (somewhat) easily be streamlined

7. 7 Dissemination of any statistical data using SDMX SDMX Conv SDMX Common Architecture Requires a paramount strategy

8. 8 Specify needs DesignBuildEvaluate Quality Management/Metadata Management Adopting standards DDI SDMX ?

9. 9 The diversity of users, needs and data flows Public Domain specific Research Questionnaires Data transfers Registers Common high level models, vocabulary etc

10. 10 Challenges The high-level decision to use SDMX for the exchange of statistical data; how should this be envisaged? –The role of the standardisation experts, the IT experts, the subject domain experts and the top management SDMX implementation is strategic, but is regarded as technical –The importance and impact of the Information Model and the Metadata Common Vocabulary Choosing standards; DDI, SDMX, DSPL etc. –No standard is likely to fit all purposes. –Will a common high-level information model contribute to easier implementation of standards? –Can a high-level information model bridge different standards? Provide well defined interfaces, or develop software to hide the challenges? –Common requirements for the quality of software

11. 11 Improved interoperability Some trends Organisational interoperability Technological interoperability Semantical interoperability

12. 12 Maturity growth in e-Government Organisational Interoperability Semantical Interoperability Source: www.semicolon.no Analytical Framework for e-Government Interoperabilitywww.semicolon.no Sharing Knowledge Aligning Work Processes Joining Value Creation Aligning Strategies Bilateral data exchange, semi automated, Technical specifications and standards Share best practises, metadata specifications, Set up standards for technical systems and data exchange Common information models, process models and service catalogues, shared development costs Legislation, Whatever

13. 13 Common Generic Industrial Statistics GSBPMGSIM MethodsTechnology Statistical ConceptsInformation Concepts Statistical HowTo Production HowTo conceptual practical Industrializing Statistics De-coupling content and technical standardisation

14. 14 Conclusions Standardisation is not a goal in itself; any standardisation effort must be based on well defined business cases. Success requires a top-down, management driven approach. The adoption of SDMX must be aligned with the on-going process oriented developments among NSI’s. Utilize the benefits of SDMX for the exchange of aggregated data, improve the international harmonisation of requirements, and simplify implementation whenever possible. Agreeing on common high-level models, creates an opportunity for flexible, targeted and effective solutions on the detailed level, still harmonised within a standardised framework The statistical community should act as an industry, not only as individuals, in order to increase commercial attention to the industry of statistics

15. 15 Actions ? (Continue to) set up a common reference framework comprising the objectives of harmonisation/standardisation –Appreciate clustered initiatives, but require precise description on the contributions to the overall objectives –Better prioritisation among projects; it is unlikely that we can achieve all goals at once –Improve governance and coordination –Let the drivers drive –Evaluate Decide where to provide for best practises, architectures, standards and tools/shared software components Improve the strategy on how to coordinate process developments with subject matter/domain specific developments Provide for innovation