1. Standardisation activities in the statistical community
Francesco Rizzo, Istat
ESTP Training Course
“Information standards and technologies for describing, exchanging and disseminating data and metadata”
Rome, June 2018

2. Summary The international context Issues and common challenges
The emerging worldwide vision
The answers of the official statistics
High Level Group for the Modernisation of Official Statistics
The European Statistical System Vision 2020
OECD Statistical Information Systems – Collaboration Community
Enterprise architecture and standards

3. The international context
Satisfy new demands for statistical information:
more statistical indicators
more sectorial and territorial details
timeliness
better quality
Governments needs to help the formulation of good policy, not only at national level
Reduction of financial allocation
The ICT development has allowed a cost reduction in producing statistics and its easily accessibility and dissemination
this has implied competition from private enterprises
Internet and other new means are offering new opportunities:
creating new information products and new ways of combining and using information
wide variety of new information sources are available with few constrains and a lot of details
In the last the way to produce statistics is radically changing due the a series of challenges and chances that the producers of official statistics have to face.
First of all NSIs and IOs have to “satisfy new demands for statistical information” because both traditional and new users (institutional users but also consumer users) are requiring:
more statistical indicators
more sectorial and territorial details
timeliness
better quality
Furthermore policy makers need statistics not only at national level in order to formulate good policy.
On the other side NSIs have to deal with big constraints due to the reduction of financial allocation.
In this scenario the technology is playing a fundamental role:
From one side the ICT development has behaved a cost reduction in producing statistics and its easily accessibility and dissemination.
This has implied competition from private enterprises. (e.g. Google has recently started producing price indices based on online transactions, and disseminating statistics through its platform “data explorer”)
From the other side, Internet and other new means are offering new opportunities:
creating new information products and new ways of combining and using information
wide variety of new information sources are available with few constrains and a lot of details

4. Issues and common challenges
Rigid processes and methods
Technology environments inflexible and dated
High maintenance costs of the business model and the associated asset bases
Many statistical organizations have already started modernization programs
Vision
Implementation strategy
Enterprise Architecture for driving and handling the modernization process

5. The emerging worldwide vision
Modernization of the statistical information systems
standardization and industrialization
new products able to be competitive within the global market
harmonization of the information (concepts, classifications and dictionaries)
overcoming of the “stovepipe” logic
new methods for interchange of data and metadata
Reduce costs of producing data
Foster the collaborative development of tools
Managing information throughout its lifecycle
Statistical information systems metadata-drives
Industrialisation is:
Common processes
Common tools
Common methodologies
Recognising that all statistics are produced in a similar way: No domain is “special”
Increased flexibility to adapt to new sources and produce new outputs
Example of Industry standards widhin the statistical context are:
Generic Statistical Business Process Model
Generic Statistical Information Model
Statistical Data and Metadata eXchange
Data Documentation Initiative

6. “As-is” situation within a statistical organization
Specialized business processes, methods and IT systems for each survey / output
Accidental architecture

7. The result of the standardization within an Organization
Applying Enterprise Architecture
Disseminate

8. ... but if each statistical organization works by themselves ...

9. ... we get this ...

10. Standardization within Statistical Organizations
.. which makes it hard to share and reuse!

11. Reusing among statistical Organizations
… but if statistical organisations work together to define a common statistical production architecture ...
... sharing is easier!

12. The answers of the official statistics
International level - High-Level Group for the Modernization of Official Statistics
Oversees activities that support modernization of statistical organizations
Stimulates development of global standards and international collaboration activities
“Within the official statistics community ... take a leadership and coordination role”
European level – European Statistical System Vision 2020
It is the key reference to guide strategic decisions within the ESS in future years (until 2020)
Modernization programs within NSIs

13. High Level Group for the Modernization of Official Statistics
Created by the Conference of European Statisticians in 2010
Driven by Vision and Strategy endorsed by CES
11 members (IRL, AUS, CAN, IT, MEX, NL, NZ, KR, SLO, UK, ESTAT, OECD, UNECE)
The objectives of the HLG-MOS are:
To promote common standards, models, tools and methods to support the modernisation of official statistics;
To drive new developments in the production, organisation and products of official statistics, ensuring effective coordination and information sharing within official statistics, and with relevant external bodies;
To advise the Bureau of the CES on the direction of strategic developments in the modernisation of official statistics, and ensure that there is a maximum of convergence and coordination within the statistical "industry".
These objectives are met in a number of ways:
Annual projects on topics identified as key priorities by the Statistical Modernisation Community
Expert groups, task teams and evaluation projects on specific themes related to statistical modernisation

14. Key models promoted by HLG-MOS projects
Generic Statistical Business Process Model (GSBPM)
Generic Statistical Information Model (GSIM)
Common Statistical Production Architecture (CSPA)
is a reference architecture for the statistical industry
covers statistical production across the processes defined by the GSBPM
provides a practical link between statistical conceptual standards
includes application and technology architectures and associated principles for the delivery of statistical services
Generic Activity Model for Statistical Organisations (GAMSO)
Describes and defines the activities that take place within a typical statistical organisation (Strategy & Leadership, Capability development, Corporate support, Production)

15. How the HLG-MOS is organized
Data Architecture  Common Statistical Data Architecture (CSDA)
Data Integration  Data Integration Guidelines
Blue Sky Thinking Network  is the “ideas factory” for the statistical modernisation community. The network provides a research and innovation platform where members can share ideas and look for partners to explore how new innovations to our production process can benefit statistical organisations. The Network aims to identify and evaluate new opportunities and to produce reports, CSPA compliant software or proposals for further work
Supporting Standards  The goal of the group is to find ways how to develop, enhance, integrate, promote, support and facilitate implementation of the range of standards needed for statistical modernisation. It has operational responsibility for the maintenance and development of GAMSO, GSBPM, GSIM, and CSPA.

16. European Statistical System Vision 2020
It is a common strategic response of the European Statistical System (Eurostat, EU Member States and EFTA countries) to the challenges that official statistics is facing. It was adopted by the ESS Committee in May 2014
Developed jointly by all ESS members, it represents an adequate compromise to respond to both National and European needs
It will be the key reference for guiding strategic decisions within the ESS in the future years (until 2020)
It will serve as the basis for a revision in the medium term of the multiannual statistical program
It allows to align all the already running activities within the ESS (ESS.VIP, FRIBS, Modernization of social statistics)

17. The five key areas of the ESS Vision 2020
Projects/Acronyms Definition
SIMSTAT: SIngle Market STATistics
ESBRs: European System of interoperable Business Registers (network of European business registers)
VALIDATION: Common Data VALIDATION standards and rules
ADMIN: Enhanced use of administrative data sources for statistical production
SERV: shared SERVices - Towards sharing specific services in statistical production
DIGICOM: DIGItal COMmunication - Optimizing user analytics and communication and data dissemination tools
BIGD: BIG Data - Harnessing the arising new data sources (focus on Big Data)
ESDEN: Data highways for microdata exchange between ESS partners

18. OECD Statistical Information System – Collaboration Community
Vision
The SIS-CC vision is to provide an international collaboration framework for a more open, innovative and industrialised data dissemination, to collectively develop software, leverage innovations, mutualise costs, and promote standardisation.
Strategic objectives
Collectively produce and develop software
Share experiences, knowledge and best practices
Contribute to International Collaboration, by accelerating the implementation of standards and contributing to the international ‘Plug and Play’ architecture vision.
OPEN INNOVATION IN PRACTICE
Pooling together ideas, skills, resources and developing products to better meet the needs for public statistics
Collectively produce and develop software, by leveraging on the .Stat platform and related components, and in so doing build a robust, component-based and scalable architecture
Share experiences, knowledge and best practices through multilateral collaboration and building of a collective capacity, concerning the Community.
Contribute to International Collaboration, by accelerating the implementation of standards and contributing to the international ‘Plug and Play’ architecture vision.
Members: Australian Bureau of Statistics; International Labour Organisation; International Monetary Fund; Italian National Institute of Statistics; National Bank of Belgium; OECD; Statistics Estonia; Statistics New Zealand; UK Data Service; UNESCO Institute for Statistics

19. Enterprise architecture and standards
GAMSO

20. Useful links
High-Level Group for the Modernisation of Official Statistics:
Level+Group+for+the+Modernisation+of+Official+Statistics
The European Statistical System Vision 2020:
OECD Statistical Information System – Collaboration Community: