Towards a normalised, domain-independent model for modelling the contents of statistical data and associated metadata Or: How to design correct and globally.

Slides:



Advertisements
Similar presentations
Status on the Mapping of Metadata Standards
Advertisements

Building SDMX Data Structure Definitions based on a generic conceptual model for contents Experience with the joint Eurostat-Unesco-OECD.
13 September 2012 SDMX Technical Working Group1 Report of the SDMX Technical Standards Working Group SDMX Expert Group Meeting, Paris, September 2012.
OECD Expert Group on Statistical Data and Metadata Exchange Geneva May 2007 OECD.Stat SDMX Web Service (II) Jens Dossé, OECD.
OECD Expert Group on Statistical Data and Metadata Exchange (SDMX) Paris, September 2012 Governance of commonly used SDMX artefacts A.Götzfried.
April, 2004 Lars Thygesen International Trade Expert meeting Whats going on at OECD: statistical information management.
1 Meeting of the OECD Short-term Economic Statistics Expert Group June 2002 FUTURE OF SHORT-TERM ECONOMIC STATISTICS DISSEMINATED BY THE OECD.
Modelling the contents and structure of official statistics Or: How to design correct and globally consistent SDMX Data Structure Definitions Or: Navigating.
The systems approach to official statistics Bo Sundgren 2010
Gerrit de Bolster September 24, 2013 Generating Blaise from DDI.
1 Work session convened by the Friends of the Chair Group on Integrated Economic Statistics Bern, 6-8 June 2007 Session 3(c) DISSEMINATION STANDARDS (DATA.
DDI 3.0 Conceptual Model Chris Nelson. Why Have a Model Non syntactic representation of the business domain Useful for identifying common constructs –Identification,
Modernizing the Data Documentation Initiative (DDI-4) Dan Gillman, Bureau of Labor Statistics Arofan Gregory, Open Data Foundation WICS, 5-7 May 2015.
WP.5 - DDI-SDMX Integration
WP.5 - DDI-SDMX Integration E.S.S. cross-cutting project on Information Models and Standards Marco Pellegrino, Denis Grofils Eurostat METIS Work Session6-8.
NSI 1 Collect Process AnalyseDisseminate Survey A Survey B Historically statistical organisations have produced specialised business processes and IT.
M ETADATA OF NATIONAL STATISTICAL OFFICES B ELARUS, R USSIA AND K AZAKHSTAN Miroslava Brchanova, Moscow, October, 2014.
REFERENCE METADATA FOR DATA TEMPLATE Ales Capek EUROSTAT.
4 April 2007METIS Work Session1 Metadata Standards and Their Support of Data Management Needs Daniel W. Gillman Bureau of Labor Statistics Paul Johanis.
Classification of Statistical Activities – Proposed Revisions Expert Group Meeting on International Economic and Social Classifications May 18-20, 2011.
Recent Developments of the OECD Business Tendency and Consumer Opinion Surveys Portal coi/coordination
CHRIS NELSON METADATA TECHNOLOGY WORK SESSION ON STATISTICAL METADATA GENEVA 6-8 MAY 2013 Designing a Metadata Repository Metadata Technology Ltd.
Met a-data Resources in Europe: within NSIs and from Dosis Projects Wilfried Grossmann Department of Statistics and Decision Support Systems University.
©Ian Sommerville 2004Software Engineering, 7th edition. Chapter 7 Slide 1 Requirements Engineering Processes.
GSIM implementation in the Istat Metadata System: focus on structural metadata and on the joint use of GSIM and SDMX Mauro Scanu
United Nations Economic Commission for Europe Statistical Division Part B of CMF: Metadata, Standards Concepts and Models Jana Meliskova UNECE Work Session.
Statistical databases in theory and practice Part III: Designing statistical databases Bo Sundgren
Promoting the use of SDMX WPTGS November Presentation contents: 1. What is SDMX? 2. SDMX: NSI Perspective 3. OECD SDMX work 4. How SDMX is used.
Metadata Common Vocabulary a journey from a glossary to an ontology of statistical metadata, and back Sérgio Bacelar
Eurostat SDMX and Global Standardisation Marco Pellegrino Eurostat, Statistical Office of the European Union Bangkok,
1 Integration of the Eurostat and ESS Metadata Systems A. Götzfried Head of Unit B6 Eurostat.
Metadata Working Group Jean HELLER EUROSTAT Directorate A: Statistical Information System Unit A-3: Reference data bases.
SDMX and Metadata SDMX Basics Course 12 April 2013 Daniel Suranyi Eurostat B5 Management of statistical data and metadata.
The Role of International Standards for National Statistical Offices Andrew Hancock Statistics New Zealand Prepared for 2013 Meeting of the UN Expert Group.
An overview of SDMX November Presentation contents: 1. What is SDMX? 2. SDMX: NSI Perspective 3. OECD SDMX work 4. How SDMX is used in sharing and.
Integrated metadata systems History Status Vision Roadmap
Aim: “to support the enhancement and implementation of the standards needed for the modernisation of statistical production and services”
Eurostat 1.SDMX: Background and purpose 1 Edward Cook Eurostat Unit B5: “Central data and metadata services” SDMX Basics course, October 2015.
OECD Expert Group on Statistical Data and Metadata Exchange (Geneva, May 2007) Update on technical standards, guidelines and tools Metadata Common.
1 Enhancing data quality by using harmonised structural metadata within the European Statistical System A. Götzfried Head of Unit B6 Eurostat.
ITS Meeting Sept 2006 New Developments at the OECD: The Common Processing Application (COPRA) ITS Experts Meeting – September 2006 Trevor Fletcher ITN/CBS.
Statistical Data and Metadata Exchange SDMX Metadata Common Vocabulary Status of project and issues ( ) Marco Pellegrino Eurostat
UNECE METIS 2008 Pre-work session survey of participants.
CountryData SDMX for Development Indicators MDG Data Structure Definition and CountryData.
How official statistics is produced Alan Vask
SDMX Basics course, March 2016 Eurostat SDMX Basics course, March Introducing the Roadmap Marco Pellegrino Eurostat Unit B5: “Data and.
METADATA MANAGEMENT AT ISTAT: CONCEPTUAL FOUNDATIONS AND TOOLS Istituto Nazionale di Statistica ITALY.
IAEA International Atomic Energy Agency Implementing SDMX for Energy Domain: From Discussion to Actual Implementation and Testing Andrii Gritsevskyi Oslo.
Streamlining the Statistical Production in TurkStat Metadata Studies in TURKSTAT High Level Seminar for Eastern Europe, Caucasus and Central Asia Countries.
Global data structure definitions
Metadata Standards for Statistical Classifications
Interoperable data formats: SDMX
SDMX Information Model
SISAI STATISTICAL INFORMATION SYSTEMS ARCHITECTURE AND INTEGRATION
SDMX data sharing between IMF and OECD
11. The future of SDMX Introducing the SDMX Roadmap 2020
Presentation contents:
2. An overview of SDMX (What is SDMX? Part I)
The Generic Statistical Information Model
Statistical Information Technology
Metadata use in the Statistical Value Chain
Annegrete Wulff Statistics Denmark
1. SDMX: Background and purpose
ESTP course on Statistical Metadata – Introductory course –
Petr Elias Czech Statistical Office
7. Introduction to the main SDMX objects for metadata exchange
Statistical databases in theory and practice Part III: Statistical information systems (extra material) Bo Sundgren 2010.
Statistical databases in theory and practice Part IV: Modelling the contents and structure of official statistics Bo Sundgren 2010.
Presentation transcript:

Towards a normalised, domain-independent model for modelling the contents of statistical data and associated metadata Or: How to design correct and globally consistent Data Structure Definitions Bo Sundgren, Statistics Sweden OECD Expert Group Meeting on Statistical Data and Metadata eXchange

Contents By Example (based on a simple generic model) Actors Utilities Complex objects

UNESCO model version 1 (to be revised)

Everything clickable OBJECT VARIABLE Lefthand click Righthand click Select: - object - variable Retrieve metadata: - definition - value set, classification - questionnaire - quality declaration - survey documentation

Our propositions The statistical data/metadata model presented here is general and domain-independent. It will cover all kinds of data and metadata to be made publicly available on the Internet and to be exchanged between national statistical agencies and international organisations. This proposition has been verified in a number of cases. So far the proposition has not been falsified in any case. This generic model can be transformed in a systematic way into an SDMX-compliant generic model expressed in XML. Since cube models, as actually practiced in national statistical agencies and international organisations, differ slightly between themselves and cannot always be said to be standardised, we propose the transformation to take place in two steps: –Step1: Non-standardised cubes are transformed into normalised cubes as defined here. –Step 2: Normalised cubes are transformed into standardised SDMX cubes (to be defined).