Generic Statistical Information Model (GSIM)

1. Generic Statistical Information Model (GSIM) EbboPetrikovits Czech Statistical Office ebbo.petrikovits@czso.cz

2. Content • What is GSIM? • Why GSIM? • GSIM v 1.0 • Selected chapter of GSIM • Conclusions

3. What is GSIM? (1) • reference framework of information objects, which enables generic descriptions of the definition, management, and use of data and metadata throughout the statistical production process. • internationally agreed set of definitions, attributes and relationships that describe the pieces of information that are used in the production of official statistics.

4. What is GSIM (2) • common language to describe information that supports the statistical production process from the identification of user needs through to the dissemination of statistical products. • is aligned with relevant standards, such as DDI and SDMX, but it is not directly tied to them, neither to specific technologies nor other concrete implementation details. GSIM provides common semantics that can be used unambiguously across and between different implementations.

5. Why GISM (1) • There is no common means to describe the information we use. This makes it difficult to communicate clearly within and between statistical agencies and without this there is no foundation for in-depth collaboration and nor greater standardisation and the sharing of tools and methods.

6. Why GSIM (2) • Provide definitions of the information objects supporting all statistical business processes, especially those defined in the GSBPM. • Improve communication between different disciplines involved in statistical production, within and across statistical organisations; and between users, producers and providers of official statistics. • Generate economies of scale by enabling intra and inter-agency collaboration, especially through reuse of information, methods or technology.

7. Why GSIM (3) • Enable configurable, rule-based and modular ways of producing statistics, thus minimizing human intervention in the production process. • Provide a basis for flexibility and innovation, including support for the easy deployment of new statistical products and the adoption of new types of statistical data sources.

8. GSIM version 1.0 • Published in December 2012 • Content of the document I. Introduction II. Information in a statistical organization Annex A. Extending the Model Annex B. Influence of existing standards Annex C. Glossary Annex D. UML class diagrams and object descriptions

9. GSIM v. 1.0 Information groups • Specification of information groups • Business Group • is used to capture the designs and plans of Statistical Program • Production Group • is used to describe each step in the statistical process, with a particular focus o describing the inputs and outputs of these steps • Concepts Group • contains sets of information objects that describe and define the terms used when talking about real/world phenomena that the statistics measure in their practical implementation

10. GSIM v. 1.0 Information groups (cont.) • Specification of information groups • Structure Group • contains set of information objects that describe and define the terms used in relation to data structure • Base Group • consists of several information objects that can be seen as the fundamental building blocks that support some other information objects and relationships in the model

11. Structure of the modelTop level

12. Structure of the modelSecond level

13. Relationships between components

14. Object descriptions For each object GSIM provides: • a definition • a preferred name • a set of relationships to other information objects • a set of attributes used to describe each object (new attributes may be added in next versions of GSIM)

15. GSIM and GSBPM • GSBPM is a business process model • GSIM models information about processes and their inputs and outputs

16. Exercise Define a simple process step. Apply this decomposition. What information do I need for each block?

17. A solution GSBPM: 5.3 validate and edit Manual correct error: If value a + value b <> value c then manual editing Process step definition contains 2 process methods: • manual correct error • manual editing Methodology: correct data

18. The big picture You are here

19. “Grand unification” • Generalized Statistical Production System GSBPM GSIM Common Generic Industrialized Statistics Technology Methods Grand Unification is a new approach that brings together the GSBPM and GSIM to make statistics To be developed ...

20. Key points • 1. Official statistics organizations have to modernize to survive2. Modernization is not an IT issue!It is strategic: Defining the future of official statistics3. GSBPM and GSIM are not software tools – they are new ways of thinking

21. Conclusions • Version 1.0 published by the end of 2012 • Long term investment • Unsure and uncertain • Good for communication • No common vision on standardisation and industrialisation • Budget cuts help?

22. Questions ?

23. Useful Links • GSBPM • http://www1.unece.org/stat/platform/display/metis/The+Generic+Statistical+Business+Process+Model • GSIM • http://www1.unece.org/stat/platform/display/metis/Generic+Statistical+Information+Model+(GSIM) • HLG-BAS • http://www1.unece.org/stat/platform/display/hlgbas • METIS • http://www1.unece.org/stat/platform/display/metis/METIS-wiki

24. Thank you for your attention