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.
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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 1 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 2 3 GSBPM – leaving stove pipes 3 4 Data archiving 4 Process stages and data archiving Quality Management/Metadata Management Specify needs Design Build Evaluate Data archiving spans the 4 main business processes, and comprises 4 steady states of the data life cycle 5 Dissemination of aggregated statistics using SDMX SDMX Conversion SDMX Common Architecture Can (somewhat) easily be streamlined 6 Dissemination of any statistical data using SDMX SDMX Conv SDMX Common Architecture Requires a paramount strategy 7 Adopting standards Quality Management/Metadata Management Specify needs Design Build Evaluate DDI SDMX ? 8 The diversity of users, needs and data flows Common high level models, vocabulary etc Questionnaires Data transfers Registers Public Research Domain specific 9 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 10 Improved interoperability Some trends Organisational interoperability Semantical interoperability Technological interoperability 11 Maturity growth in e-Government Organisational Interoperability Aligning Strategies Joining Value Creation Sharing Knowledge Aligning Work Processes Source: www.semicolon.no Analytical Framework for e-Government Interoperability Legislation, Whatever Common information models, process models and service catalogues, shared development costs Share best practises, metadata specifications, Set up standards for technical systems and data exchange Bilateral data exchange, semi automated, Technical specifications and standards Semantical Interoperability 12 Industrializing Statistics conceptual Statistical Concepts Information Concepts GSBPM GSIM practical Common Generic Industrial Statistics Methods Statistical HowTo Technology Production HowTo De-coupling content and technical standardisation 13 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 14 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 15