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SDMX through the GSBPM

Meeting of the OECD Expert Group on SDMX 13 - 14 September, OECD, Paris Centralized Metadata System based on SDMX” Case Study : Swiss Federal Statistical Office Jean-François Fracheboud. SDMX through the GSBPM. 1 Specify Needs. 2 Design. 3 Build. 4 Collect. 5

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SDMX through the GSBPM

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  1. Meeting of the OECD Expert Group on SDMX 13 - 14 September, OECD, ParisCentralized Metadata System based on SDMX”Case Study : Swiss Federal Statistical OfficeJean-François Fracheboud
  2. SDMX through the GSBPM 1Specify Needs 2 Design 3 Build 4 Collect 5 Process 6 Analyse 7 Disseminate 8 Archive 9 Evaluate What about SDMX in the production of statistics ? SDMX generally focuses on dissemination (transmission of data and metadata) Case Studyot the SwissFederalStatistical Office How a statisticalmetadata system basedentirely on SDMX has been implemented
  3. Challenges A centralised system for a decentralised management of metadata A unique entry of metadata and a multiple usage of them An integrated system for the whole life cycle of statistics A harmonisation of metadata on severallevels : Harmonisation of the form : according to SDMX model Harmonisation of codelists Harmonisation of variables (concepts) Harmonisation of data and metadatamodels Acceptance of the system and adoption by the statistician
  4. Why a SMS ? Improve the quality of metadata and data Improve the comparability of data and metadataat national and international levels More efficiency in everystatisticalprocesses Optimise reuse of metadata and data Ensure the tracability in statistics Support for harmonisation Reducedelays in publishing
  5. Standard documents Contrat SMS Architecture Standard request Web Server IIS Web Services SDMXeditor Repository Repository Repository ETL SAS C#, .NET, etc. Repository Repository
  6. Functionalities Advanced Functions Plug-ins MetadataEditing Admin
  7. Functionalities Fonctionnalités avancées Metadataediting Entry Create, Modify, Validate, Versions, Historic, Save Import-Export SDMX, excel, Word, pdf, etc. Accessibility Web Services, Navigation, Visualisation Base Manage-ment Plugins
  8. Functionalities Advanced Functions Plugins (extensions) Export of metadata on othersystems (SAS, Oracle, SQL Server, etc.), automaticcreation of tables (from a DSD for example)Generator of codebook (DDI) Interface extension (customizing) Electronic questionnaire Validation of data with DSD Etc. etc. Plug-ins MetadataEditing Admin
  9. Functionalities Advanced Functions Plug-ins Vision for the future Accessing the data by the metadata Multidimensional visualisation of data Modeling and monitoring of business processes MetadataEditing Admin
  10. Metadatathrough the GSBPM Creation of metadata Most of metadatashouldbecreated during the first three stages Use of metadata
  11. Simplified Model StatisticalDomains Metadata Structure Definitions Variables Classifications and codelists Data Structure Definitions
  12. Statisticaldomains and activities Defining the statisticalactivities of FSO (political mandate) Organisingtheseactivities in one or more hierarchies (example : FSO statistical programme) Defining the data- and metadata-flowslinked to thesestatisticalactivities
  13. Model for Statistical Activities
  14. Attachmetadataflows and dataflows to the activities Metadataflows Statistical Activities(occurences) Dataflows
  15. Simplified Model StatisticalDomains Metadata Structures Variables Classifications and codelists Data Structures
  16. Variables / Concepts Import standard ConceptSchemes CreatedomainspecificConceptSchemes Describe the variables/concepts (definition, format, reference, etc.) Link the codelist to the variables Identification, nom et description des variables Définition type et format Nomenclatures associées Hiérarchisation des variables
  17. Simplified Model StatisticalDomains Metadata Structures Variables Classifications and codelists Data Structures
  18. Classifications andcodelists Import standard national and international codelists Create cross domain or domainspecific classifications and codelists
  19. Simplified Model StatisticalDomains Metadata Structures Variables Classifications and codelists Data Structures
  20. Data and MetadataStructure Definitions Modelingstatistical data and metadata Description of data and metadata (tables or files) Definingattributes (quality, confidentiality, observation status, etc.) atrequiredlevel (record, item, cell, etc.) Description of macro-data (times series, hypercubes, etc.)
  21. Data Structure Data Warehouse data
  22. Structural Metadata SDMX Artefacts Data Structure metadata Concepts Codelists Data Structures identify describe Data Warehouse data
  23. Structural Metadata SDMX Artefacts Data Structure Statistical Metadata System metadata Concepts Code lists Data Structures identify describe Data Warehouse data
  24. Extensions PredefinedMetadata MSD StatisticalDomains Metadata Structures Question-naires Variables Annotations Quality Metadata Classifications and codelists Data Structures DSD Metadata
  25. Download the IT application The basic IT application for the SMS isavailable free of charge and canbefoundatthe following adresses: www.sdmx.org or www.sdmx.ch
  26. Contacts For more information about the SwissStatisticalMetadata System please contact : sms@bfs.admin.ch
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