1 High Level Seminar for Eastern Europe, Caucasus and Central Asia Countries (EECCA). Quality in Statistics: Metadata Tbilisi, Georgia, 27-29 June 2012.

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Presentation transcript:

1 High Level Seminar for Eastern Europe, Caucasus and Central Asia Countries (EECCA). Quality in Statistics: Metadata Tbilisi, Georgia, June 2012 Session 6 The statistical data and metadata exchange standard (SDMX) Francesco Rizzo ISTAT – Italian National Statistical Institute

2 Summary Challenge, chances and the international context The emerging worldwide vision Rationale for SDMX SDMX milestones What is SDMX Governance of SDMX Benefits from SDMX standards Initiatives, products and capacity building within the SDMX community The European Census Hub – case study SDMX implementation in ISTAT – case study

3 Challenge, chances and the international context  Satisfy new demands for statistical information:  more statistical indicators  more sectorial and territorial details  timeliness  better quality  Reduction of burden on respondents  Governments needs to help the formulation of good policy, not only at national level  Reduction of financial allocation  The ICT development has behaved 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

4 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

5 Rationale for SDMX National statistical agencies have asked international organisations for common solutions International organisations can expand their collaboration with each other and with national agencies Recent new IT technology seems to offer clear advantages Progress can be made within a coherent framework and on an incremental basis

6 SDMX milestones Seven international organizations (BIS, ECB, Eurostat, IMF, OECD, UN, World Bank) have joined forces to develop the standard Mar 2007 the sponsor organizations signed a Memorandum of Understanding Feb 2007 the SPC (now ESS Committee) endorsed SDMX and recognized its potential in delivering real benefits in the ESS in terms of data quality, timeliness and comparability Feb 2008 the UN Statistical Commission recognized “SDMX as the preferred standard for exchange and sharing of data and metadata in the global statistical community”

7 What is SDMX standard formats for data and reference metadata a content-oriented guidelines an architecture for the efficient exchange and sharing of statistical data and metadata SDMX version 1.0 (ISO Technical Specification 17369: April 2005) SDMX version 2.0 (approved in November 2005; follow up ISO review) SDMX version 2.1 (approved by the sponsors in April 2011 ) 16-0 April 2012

8 Governance of SDMX Sponsor Organizations (Chief Statisticians) Secretariat SDMX Technical WG Global Registry SDMX IT tools strategy SDMX security guidelines Improving technical documentation Interaction of SDMX with other technical standards (e.g. DDI) SDMX Statistical WG DSD and MSD Governance and Guidelines SDMX Registries Rules for Creation and Maintenance of Code Lists

9 Benefits from SDMX standards improve quality and efficiencies in the exchange and dissemination of data and metadata –harmonisation and coherence of data –preservation of meaning –open format (XML) rather than a proprietary one reduce national reporting burden to European and international institutions can be used as key building blocks in internal statistical IT systems used for collecting, compiling, storage and searching of statistical information can potentially reduce the cost of developing statistical software systems avoid duplication of efforts in developing and maintaining standards for the processing of statistical information

10 Initiatives, products and capacity building within the SDMX community Main appointments: –SDMX Global Conference (every 2 years) –OECD-Eurostat-UNECE SDMX Expert Group (every 2 years) IT tools –a repository of tools is available on SDMX website Capacity building actions: –regional seminars –regular training sessions within the European Statistical System for statisticians and IT staff –self-learning tutorials available on the SDMX website videos student books self tests

11 The European Census Hub case study

12 The Census Hub architecture Pull mode and data sharing Hub SDMX infrastructure

How the Hub works Eurostat Census Hub National Statistical Institute Census Hub Application

14 SDMX implementation in ISTAT case study

15 Milestones 2006 SODI project SDMX Istat Framework Demographic rapid questionnaire ESSnet SDMX Phase I ESSnet SDMX Phase I 2012 Single Exit Point Stat2015 Census Hub project

16 Strategy SDMX To provide data to the international and/or national organization Census hub OECD STS Bank of Italy Italian Regions to disseminate data in machine-to-machine modality Pilot exercise with: Bank of Italy JP Morgan Italian Regions Istat Metadata system”data user” point of view Excel plug-in Windows app. ISTAT relationships OECD SIS-CC Statistical Network SDMX TWG Eurostat SDMX-RI User group Data collection

17 Products