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Part B of CMF: Metadata, Standards Concepts and Models Jana Meliskova

Get insights on international standards, concepts, and models for statistical metadata with collective input from NSOs and IOs. Access resources like standards, models, and best practices for SMS design and implementation.

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Part B of CMF: Metadata, Standards Concepts and Models Jana Meliskova

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  1. Part B of CMF:Metadata, Standards Concepts and ModelsJana Meliskova UNECE Work Session on Statistical Metadata Geneva, 10-12 March 2010

  2. Common Metadata Framework (CMF) • CMF work under the umbrella of Conference of European Statisticians • CMF aim: to assist SOs in adoption, modeling, usage and implementation of SMS across all phases of their Statistical Business Process • Collective input of NSOs and IOs • Published online via Metis Wiki www.unece.org/stats/cmf

  3. CMF composition • Part A - Statistical Metadata in a Corporate Context- A guide for managersFocused on corporate management of metadata projects.(Finalized, publication available) • Part B - Metadata , Standards Concepts and ModelsProvides information about international standards concepts and models relevant to statistical metadata.(Under preparation, presented version available on the Metis Wiki) • Part C - Metadata and the Statistical Business ProcessPresents a Generic Business Process Model as a common process model for statistical surveys.(Model finalized, available on Metis Wiki) • Part D - ImplementationFocuses on the experiences of national and international statistical organizations that have recently implemented or re-engineered their statistical metadata systems.(Case studies available on Metis Wiki)

  4. Standards for metadata are indispensable Use of standards is a challenge There is a common understanding in SOs that the use of common standards related to statistics and metadata is indispensable. The number and diversity of existing standards, however, makes it a challenge for statistical experts to understand them and to incorporate them efficiently in the SMS global architecture.

  5. CMF Part B - a draft version Ad-hoc Task Force convened for Part B in early 2009 • Presented document is not a final version of CMF Part B. • It is a draft based on: • National and international experiences reported at the UNECE/Eurostat/OECD WSs on Metis, • Consultancies with experts, • Know-how available in writing a draft. Feedback and assistance in finalizing and further maintenance of Part B is highly welcomed.

  6. The aim of CMF Part B To offer SMS designers an overview of existing resources, which are likely to be applicable when designing and implementing SMS. • Resources: standards, concepts, models, best practices and other methodological materials. • Focus on internationally recognized resource. • Part B is designed primarily as an Internet publication, so that it can be kept as up to date as possible.

  7. CMF Part B – a unique source Part B of the CMF aims to be a unique sourceof information on existing statistical metadata standards. It provides a single point of reference, giving SMS designers and other potential SMS users a basic information about standards related to statistical metadata. It provides for each standard links to more detailed materials and resources.

  8. CMF Part B – groups of standards • Standards, related to statistical metadata are presented in the following groups: 1. Statistical concepts 2. Technical standards; 3. Models and statistical practices; 4. Methodological guidelines and recommendations. • Grouping aims to assist SMS designers decide in which areas of SIS metadata standards should be   implemented. 

  9. Template for source description • Name and version • Alternative name • Valid • Description • Intended use • Maintenance organization • ISO Standard Number • References • Relationship to other standards • Format • Language • Template last update

  10. Statistical concepts Refer to the content of statistics. The group encompasses internationally accepted standards and/or recommendations: • Concepts and definitions for compiling, disseminating and exchanging statistics; • Statistical classifications; • Statistical units; • Statistical subject matter domains; • Other standards related to statistical content.

  11. Technical standardsprovide technical specifications for: • exchange, storage, documentation and retrieval of statistical data and metadata, • other ICT supported activities, dealing with the use of metadata for the production of statistics, • ISO international standards on Statistical Data and Metadata Exchange (SDMX), • metadata registries, • Data Documentation Initiative (DDI), • Geographical information system (GIS)

  12. Models and statistical practices • Internationally developed models related to statistical metadata; • Nationally developed models, recognized and applicable internationally; • Neuchâtel Model on Statistical Classifications and Variables; • Corporate Metadata Repository ;  • the IMF Data Quality Assurance Framework • ESS standards for quality reports • others

  13. Methodological guidelines and recommendations A lot of methodological materials and recommendations related to statistical metadata have been developed in the framework of international cooperation organized by the UNECE together with OECD, Eurostat and other international organizations. • Guidelines for the Modeling Statistical Data and Metadata, • Guidelines for Statistical Metadata on the Internet, • Recommendations on Formats Relevant to the Downloading of Data from the Internet, • Best Practices in Designing Websites for Dissemination of Statistics.

  14. CMF Part B – relationships between the resources • Work has also started on defining the nature of the relationships between individual resources. The chart on the next slide shows the progress so far. • Several types of relationships have been identified:

  15. CMF Part B Relationships between resources

  16. CMF Part B – some issues to be considered Completeness There are many other resources that could be described in Part B. For example: • standards indirectly related to statistical metadata; • national standards and models. Are all the relevant resources described? Should any of those currently included be removed?

  17. CMF Part B – some issues to be considered A second level of resource descriptions. • Some of the resources described (for example statistical classifications and statistical units) refer just to a family of resources. • Is there a value in developing a second tier of resource descriptions to describe the elements in these resource families? An example could be resource descriptions of the main international classifications (ISIC, ISCO, ISCED etc.).

  18. CMF Part B – some issues to be considered Identification of links between resources Each resource could have links to all other resources. However, some links are stronger than others. At present only the stronger links are described. Is it sufficient for practical purposes?

  19. CMF Part B – some issues to be considered Maintenance and update • A regular maintenance of the resources described in the CMF Part B is an important pre requisite for its value to SMS designers. • To identify “owners”, responsible for maintaining each resource description seems to be indispensable.

  20. Conclusion • The work on the CMF Part B has progressed significantly during the last year. It can now be opened to the wider METIS group for comment. • Since the CMF Part B is a living document, it will never really be finished. It should remain open for further development and maintenance. • The important goal at present is to reach the stage where the METIS community will be confident that, the CMF Part B will be useful for statistical practice. • It is planned to promote CMF Part B to the wider statistical community by the end of 2010. • The input of the 2010 METIS Work Session will help the Task Force to reach this goal.

  21. Task Force Sergio Bacelar (INE, Portugal) Max Booleman (CBS, Netherland) Alice Born (Statistics Canada) Dan Gillman (US Bureau of Labor Statistics) Hamish James (Statistics New Zealand) Jana Meliskova (Consultant) Marco Pelegrino (Eurostat) Steven Vale (UNECE)

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