(i) Metadata standards and models: Progress on Part B of the Common Metadata Framework
- Alice Born, Statistics Canada (email@example.com);
- Alistair Hamilton, Australian Bureau of Statistics (firstname.lastname@example.org);
- Juan Muñoz López, Instituto Nacional de Estadística, Geografía e Informática, Mexico (email@example.com).
The 2010 METIS work session emphasised the importance of introducing new metadata standards and of updating existing metadata standards in Part B of the Common Metadata Framework (CMF). This session will introduce the Generic Statistical Information Model (GSIM) and geographical metadata standards. The session will also include the results of a review of the Neuchâtel Terminology Model for statistical classifications, which was first presented at the 2000 METIS Work Session in Washington, D.C. General issues about mapping between metadata standards such as SDMX, DDI and ISO/IEC 11179, and their relationships to the GSIM model, will be part of the session. Contributions to this session are welcome, in the form of papers describing experiences in using and implementing these metadata standards and models.
|WP2||UNECE||Thérèse Lalor and Steven Vale|
The Generic Statistical Information Model
|Thérèse to deliver||abstract paper slides|
|WP3||Metadata Technology||Arofan Gregoryfirstname.lastname@example.org||Implementing GSIM – Mappings to DDI and SDMX|
|abstract paper slides|
Stefania Bergamasco, Alessio Cardacino, Francesco Rizzo, Mauro Scanu, Laura Vignola
A strategy on structural metadata management based on SDMX and the GSIM models
|Stefania Bergamasco to present||abstract paper slides|
|WP5||Eurostat||Marco Pellegrino||Marco.Pellegrino@ec.europa.eu||DDI-SDMX Integration and Implementation||paper slides|
|WP6||ICPSR/DDI Alliance||Mary Vardiganemail@example.com||Strategic Priorities for the Data Documentation Initiative||abstract paper slides|
|Alice Born, Anne Gro Hustoft, Debra Mair, Tim Dunstan|
Neuchâtel Terminology Model: Classification database object types and their attributes, 2013 revision
|Only Alice attending.||abstract paper slides|
|WP8||Italy (ISTAT)||Giorgia Simeonifirstname.lastname@example.org|
Implementing ESS standards for reference metadata and quality reporting at Istat
|abstract paper slides|
|WP9||Metadata Technology||Chris Nelsonemail@example.com||Designing a Metadata Repository||FWN 27/02: Chris confirmed with Steve that his approach will be focused on "the issues faced and how we have overcome them".||abstract paper slides|
|WP10||USA (BLS), France (INSEE), FAO||Dan Gillman, Franck Cotton, Yves Jaques||eXtended Knowledge Organization System (XKOS)||Got an email from Guillaume Duffes saying he is presenting.... I'm confused, shall I add him to the authors as well?||abstract paper slides|
|WP11||Australia (ABS)||Alistair Hamiltonfirstname.lastname@example.org||The Spatial Statistical Framework at the Australian Bureau of Statistics||To present via WebEx||paper slides|
|WP12||Mexico (INEGI)||Juan Muñoz Lópezemail@example.com|
Geo-referencing statistical data: Geographical standards used in Mexico
(ii) Case studies and tools
- Jenny Linnerud, Statistics Norway (firstname.lastname@example.org);
- Klas Blomqvist, Statistics Sweden (email@example.com).
Part D of the CMF consists of a series of case studies describing the metadata systems of national and international statistical organizations, including lessons learned and future plans. Case studies have already been contributed by 17 statistical organizations. The goal of this session is to review existing case studies, to solicit new ones from national statistical offices and to present and discuss metadata tools, such as classification database systems.
Kaja Sõstra, Eda Froš
|firstname.lastname@example.org||Metadata management and statistical business process at Statistics Estonia||abstract paper slides|
|WP14||Statistics New Zealand||Evelyn Warehamemail@example.com|
Metadata Infrastructure and Standardisation at Statistics New Zealand
Flavio Rizzolo (with Tim Dunstan and Kathryn Stevenson)
|Canada’s Updated Case Study and the Benefits and Challenges of Implementing the Generic Statistical Information Model||Flavio is only one attending so will present|
Statistical metadata systems in the national statistical institute of Bulgaria
|Sent shortened version of presentation 29/04||slides|
|WP17||Spain||Ana Isabel Sanchez-Luengofirstname.lastname@example.org||Development of metadata in the National Statistical Institute (INE) of Spain||abstract paper slides|
|WP18||New Zealand/Metadata Technology||Andrew Hancock and Arofan Gregoryemail@example.com, firstname.lastname@example.org|
Redeveloping Statistics New Zealand's classification management system
|WP19||BIS & Eurostat||Gabi Becker and August Götzfried||Building a Data Portal with SDMX|
Will be showing a video file with sound (file already received): be sure to set up and test speakers. August may show some slides, time permitting
|slides video file|
Use of SDMX in stocking, disseminating and managing the Swiss classification of economic activities and throughout the production process of a statistic
|abstract paper slides|
|room paper||Turkey||Deniz Özkan, Nilgün Dorsan, Gülhan Eminkahyagilemail@example.com|
Implementation of GSBPM and Metadata Studies in the Turkish Statistical Institute
|Submitted too late to be included on agenda so no presentation, but have agreed they can submit paper anyway and will be put on website||paper|
(iii) Metadata in the statistical business process
- August Götzfried, Eurostat (firstname.lastname@example.org);
- Isabel Morgado, Statistics Portugal (email@example.com).
The Generic Statistical Business Process Model (GSBPM), developed as part C of the CMF, is a common reference model for the statistical business process and is intended to apply to all activities undertaken by producers of official statistics that result in information outputs. The model encompasses production processes using statistical surveys, administrative data sources or other data sources. The GSIM, introduced in session (i), complements the GSBPM and is intended as a reference framework of statistical information objects, enabling generic description of terms and definitions, management and use of data and metadata throughout the statistical production process. One aim of this session will be to explore the implications of the GSIM for the GSBPM and how the two are interrelated.
Metadata supports and drives all the statistical business processes. The metadata flows within GSBPM phases and sub-processes, including process metadata, need to be described in detail in a harmonised manner. Such detailed harmonised process metadata for all statistical business processes is a necessary precondition for business process integration. This will reduce or even eliminate unnecessary heterogeneity of statistical methods or metadata between statistical business processes, which in turn can reduce production costs.
Contributions to this session are welcome, in the form of papers describing experiences in using and implementing statistical business process models and documentation for supporting further standardisation and integration of the business processes. Papers discussing the role and use of metadata and metadata models for facilitating efficient metadata driven collection, processing and dissemination systems are also welcome.
|WP21||Australia (ABS)||Aurito Riverafirstname.lastname@example.org||Metadata Driven Business Process in the Australian Bureau of Statistics (ABS)||To present via WebEx||abstract paper slides|
|WP22||Statistics Portugal and Informal Task Force on Metadata Flows||Isabel Morgado and colleagues on task email@example.com||Metadata Flows in the GSBPM||abstract paper|
Antonio Consoli, August Götzfried, Håkan Linden, Barbara Rychel
|August.Goetzfried@ec.europa.eu||Better documenting statistical business processes: The Euro process metadata structure||August is the only one coming||abstract paper slides|
|WP24||IMF||Gareth McGuinness, Michaela Denk and Alberto Sanchez||Gareth to present||abstract paper slides|
|WP25||ILO||Edgardo Greisingfirstname.lastname@example.org||Dealing with Metadata in ILOSTAT||abstract paper|