1. GSBPM and GSIM as the basis for the Common Statistical Production Architecture
Steven Vale
UNECE

2. Standards-based Modernisaton%
43%
34,600

4. Problem statement:
Specialised business processes, methods and IT systems for each survey / output

5. Applying Enterprise Architecture
Disseminate

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

7. ... we get this ...

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

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

10. ... sharing is easier!

11. Layers of Architecture

13. Generalised Statistical Production System
Conceptual
GSIM
GSBPM
GSIM
Business
Process
Information
informs
informs
informs
Service Inputs
Service
Service Outputs
Methods
Technology
Service defined by methods and business need
Standards Based
e.g. DDI, SDMX
In this diagram, the goal of achieving a Generalised Statistical Production System is realized through defining services which align with business needs (eg to perform activities described within GSBPM). These services accept inputs and produce outputs whose definition is consistent with GSIM and which can be represented in practice using standards such as SDMX and DDI.
As the “service interfaces” are designed on a consistent basis, it is possible to assemble selections of services in a flexible manner to meet business needs. It is easy at a later time to “unplug” use of an existing service/component within a statistical business process and “plug in and play” a new service/component which offers improved quality (which may include improved performance and/or reduced cost).
The centre of the diagram illustrates the value of a service oriented approach when seeking to realize a Generalised Statistical Production System. A service oriented approach requires well defined business architecture. It is essential services align with underlying business needs if they are to be reused widely.
Service oriented architecture (SOA) is driven by a set of design principles. It is not prescriptive in terms of technologies to be used. For example, web services are often chosen as a means to implement solutions, but their use is not mandated.
The “plug and play” paradigm that members of HLG are seeking can be defined and supported using SOA concepts and techniques.
enables
business process
Practical
Generalised Statistical Production System

14. GSBPM defines the “shape” GSIM defines the interfaces
CSPA Service

15. 2013 - CSPA development project
Architecture Proof of Concept

16. The Proof of Concept 5 countries built CSPA services
3 countries implemented them

17. What did we prove?

18. CSPA is practical and can be implemented by various agencies in a consistent way

19. You can fit CSPA statistical services into existing processes
Statistics New Zealand (Workflow)
Istat (CORE)

20. CSPA does not depend on a specific technology platform
Statistics New Zealand (Workflow)
Istat (CORE)

21. You can swap out CSPA compliant services easily
Statistics New Zealand (Workflow)

22. You can re-use the same statistical service by configuration
Survey A
Survey B
Statistics Sweden (Workflow -Triton)

23. Project Outcomes The CSPA approach works It promises increased:
sharing
interoperability
collaboration opportunities
Some licensing issues!

24. 2014 – CSPA Implementation

25. Services built Seasonal adjustment – France, Australia, New Zealand
Confidentialised analysis of microdata – Canada, Australia
Linear error localisation – Netherlands
Linear rule checking – Netherlands
Error correction – Italy
Statistical chart generator – OECD
SDMX transform – OECD
Sample selection – Netherlands
By the end of the year we will have several CSPA-compliant services (or components) in use. There are 8 currently being developed. Some in collaboration between organisations, others within individual organisations, but the important point is that they will share common specifications.

26. Architecture Working Group: Australia, Austria, Canada, France, Italy, Mexico, Netherlands, New Zealand, Turkey, Eurostat
Catalogue team: Australia, Canada, Italy, Hungary, New Zealand, Romania, Turkey, Eurostat
An “Architecture Working Group” has been set up to oversee the development of these services, and ensure compliance with the agreed architecture principles.
A “Catalogue Team” will develop a repository for the finished services, to make them available to other statistical organisations. This can be seen as the box where the Lego pieces are kept, ready for re-use.

27. Architecture Working Group
Meetings every fortnight
25 Definition, Specification and Implementation reviews
30 architectural and implementation issues
Update of CSPA framework

28. CSPA Global Artefact Catalogue
Support efficient sharing and reuse of process patterns, information and services at an organization and international level
Allow users to reliably and efficiently discover what is available for reuse to support a particular business need
Allow users to assess whether services are "fit for purpose" to support a particular business need

29. Five layers of the CSPA Global Artefact Catalogue

30. 2015 – CSPA Goes Live!

31. Main activities
1 Governance - management of CSPA and determining if services are CSPA compliant
2 Support to implementers - guidelines, templates and a helpdesk
3 More services – based on the priorities identified by project partners
4 Catalogue – transition from wiki prototype to full version hosted by Eurostat

32. Call for participation in project teams

33. Alignment with ESS Vision 2020
Alignment of CSPA (GSIM and GSBPM) and the implementation of the new ESS Vision is a key priority
From a CSPA perspective, the implementation of the ESS Vision is an excellent opportunity to test CSPA on a larger scale and to further develop it

34. but Summary Each standard can be used by itself
There is greater value in using them as a set of linked standards

35. More information: CSPA Wiki http://www1. unece