The Use of GSIM in Statistics Norway
Norway's Statistics Department utilizes GSIM for statistical operations, with key figures on employees, releases, and participation in GSIM development and implementation. Additionally, they are involved in the RAIRD project to establish a remote access infrastructure for statistical data. The RAIRD Information Model based on GSIM v1.1 enhances user experience with redesigned information objects. The GSIM Glossary distinguishes between elements in and outside the RAIRD Information Model, emphasizing statistical support programs.
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The use of GSIM in Statistics Norway Jenny Linnerud (jal@ssb.no) Senior Adviser Department of IT Statistics Norway 10th June 2014, Nizhny Novgorod
Statistics Norway Key figures 910 employees (per 31.12.2013) 560 in Oslo, 350 in Kongsvinger In addition, 175 interviewers Around 420 different statistics Around 1000 releases of new statistics on ssb.no in 2013
Statistics Norways participation in GSIM Development 2012 GSIM sprint in Slovenia, February GSIM sprint in Republic of Korea, March Integration workshop in the Netherlands, November GSIM v1.0 December
Statistics Norways participation in GSIM Implementation 2013-2014 GSIM v1.0 Brochure and Communication document in Norwegian Informal task force on metadata flows in the GSBPM - ca. 20 GSIM information objects were mapped to the phases in GSBPM v4 GSIM v1.0 discussion forum GSIM Statistical Classification Model -> GSIM v1.1 December 2013 Contribute Statistical Classification services within the Implementing CSPA Project 2014 Try out GSIM v1.1 within the RAIRD project
Remote Access Infrastructure for Register Data (RAIRD) Statistics Norway and the Norwegian Social Science Data Services (NSD) aim to establish a national research infrastructure providing easy access to large amounts of register based statistical data managing statistical confidentiality protecting the integrity of the data subjects. The work is funded by the Research Council of Norway through 2017. See: www.raird.no
RAIRD Information Model (RIM) Based on GSIM v1.1 Design principles Information objects (ca. 115) - 27 new information objects for users (producers, administrators and researchers) and explicit statistical confidentiality - Less information objects for details of official statistical production
GSIM Glossary blue not in RIM, yellow in RIM Statistical Support Program Business A program which is not related to the post-design cyclic production of statistical products, but is necessary to support cyclical production. This type of program will include such functions as metadata management, data management, methodological research, and design functions. These programs correspond to the horizontal functions shown in the GSBPM, as well as programs to create new or change existing Statistical Programs. Subject Field Concepts One or more Concept Systems used for the grouping of Concepts and Categories for the production of statistics. A Subject Field is a field of special knowledge under which a set of Concepts and their Designations is used. For example, labour market, environmental expenditure, tourism, etc. subject area, theme Unit Concepts The object of interest in a Business Process Here are 3 examples - 1. Individual US person (i.e., Arofan Gregory, Dan Gillman, Barack Obama, etc.) 2. Individual US computer companies (i.e., Microsoft, Apple, IBM, etc.) 3. Individual US universities (i.e., Johns Hopkins, University of Maryland, Yale, etc.) Unit Data Point Structures A placeholder (or cell) for the value of an Instance Variable with respect to a Unit. This placeholder may point to multiple values representing different versions of the data. Values are only distinguished on the basis of quality, date/time of measurement or calculation, status, etc. This is handled through the mechanisms provided by the Datum information object. cell
GSIM and GSBPM GSIM describes the information objects and flows within the statistical business process.
GSIM in Statistics Norway - Vision META DATA
GSIM in Statistics Norway - Vision GSIM should lead to: A foundation for standardised statistical metadata use throughout systems A standardised framework for consistent and coherent design of statistical production Increased sharing of system components
