1. United Nations Economic Commission for Europe Statistical Division Standards-based Modernisation An update on the work of the High-level Group for the Modernisation of Statistical Production and Services Steven Vale UNECE steven.vale@unece.org

2. Contents  Modernisation and the High-level Group  Standards  Projects  Big Data

3. Why is modernisation important?

4. In the last 2 years more information was created than in the whole of the rest of human history!

5. Making sense of the Data Deluge

6. Statistics fights back!  High Level Group for the Modernisation of Statistical Production and Services (HLG) Created by the Conference of European Statisticians in 2010 10 heads of national and international statistical organisations

7. The Challenges Increasing cost & difficulty of acquiring data New competitors & changing expectations Rapid changes in the environment Competition for skilled resources Reducing budget Riding the big data wave

8. These challenges are too big for statistical organisations to tackle on their own We need to work together

9. Using common standards, statistics can be produced more efficiently No domain is special! Do new methods and tools support this vision, or do they reinforce a stove-pipe mentality?

10. The answer... Standards-based Modernisaton

11. The GSBPM

12. Why a Generic Statistical Business Process Model?  To define and describe statistical processes in a coherent way  To compare and benchmark processes within and between organisations  To make better decisions on production systems and organisation of resources Business register processes mapped to GSBPM (see 2011 paper)

14. GSIM and GSBPM  GSIM describes the information objects and flows within the statistical business process.

15. So what is GSIM?  A reference framework of information objects: Definitions Attributes Relationships  GSIM aligns with relevant standards such as DDI and SDMX GSIM gives us standard terminology

18. Projects for 2013

20. Reviewing GSBPM and GSIM  Gather feedback from users of the models through public discussion forums  New versions of GSBPM and GSIM by the end of 2013  But... any changes will need a strong business case and wide agreement Continuity is important Major change is unlikely

21. Mapping GSIM to DDI and SDMX  Detailed mapping between the information objects in the GSIM, with those in the information models of DDI and SDMX.  Aims to identify any issues affecting the coherence of these standards  Propose solutions where possible

23. Historically, statistical organisations have produced specialised business processes, methods and IT systems for each survey / output

24. How does architecture help?  Many statistical organisations are modernising and transforming using Enterprise Architecture  Enterprise Architecture shows what the business needs are, where the organisation wants to be and aligns the IT strategy to this  It can help to remove silos and improve collaboration across an organisation

25. Applying Enterprise Architecture Disseminate

26. ... but if each statistical organisation works by themselves...

27. ... we get this...

28. .. which makes it hard to share and reuse!

29. … but if statistical organisations work together to define a common statistical production architecture...

30. ... sharing is easier!

31. Big Data: A new project for 2014?

32.  Paper: What does Big Data mean for official statistics?  Project proposal from global task team: Objectives: Develop and test methods and tools Scope: Big Data in modernisation of official statistics Work package 1: Issues and methodology Work package 2: Shared computing environment (“sandbox”), practical application of methods and tools Work package 3: Training and dissemination HLG and Big Data

33.  Many un-answered questions: Data on-site or in the cloud? How to link Big Data with registers / surveys? How to define units? Classifications – on the fly? How to ensure sufficient confidentiality? Continuity? Big Data and Business Registers

34. Get involved! Anyone is welcome to contribute! More Information HLG Wiki: http://www1.unece.org/stat/platform/display/hlgbas LinkedIn group “Business architecture in statistics”