2.1 Statistical information model
Our current information models are fragmented and mostly in Norwegian.
2.2 Adoption of GSIM
Statistics Norway has participated in the development of GSIM v1.0 from the initial idea within the Statistical Network through sprint 1 in Slovenia, sprint 2 in south Korea and the integration workshop in Statistics Netherlands including reviews of v0.4 and v0.8. We are participating in the GSIM Implementers Group and have participated in the MetaData Task Force looking at the flow of GSIM v1.0 information objects throughout the GSBPM v4.0. We will continue to work with GSIM and DDI in connection with the RAIRD (Remote Access Infrastructure for Data to researchers) project togather with the Norwegian data archive. We intend to adopt v1.0 with extensions and give constructive feedback intended to strengthen GSIM in its fit for purpose role.
2.3 Statistical business process model
Our statistical business process model is based on the work done by Statistics New Zealand, by Statistics Sweden and by METIS.
The phases we are currently using are as follows: 1. Specify Needs, 2. Design, 3. Build, 4. Collect, 5. Process, 6. Analyse and 7. Disseminate. We also have two overarching phases 8 Quality management - evaluate and feedback and 9 Support and infrastructure.
Comparison with the Generic Statistical Process Model v4.0 from April 2009 by the UNECE secretariat: Phase 8. Archive is covered in our model by sub-processes. The quality management part of the overarching phase Quality management/Metadata management is covered by our phase 8 Quality management - evaluate and feedback, while the metadata management part is covered in our model by sub-processes.
For more information refer on Statistics Norway's Business Process Model see http://www.ssb.no/english/subjects/00/90/doc_200817_en/doc_200817_en.pdf
2.4 Relation to other models
We intend to use GSIM in conjunction with the GSBPM internationally and with our own business process model nationally. We are currently exploring the use of GSIM in combination with DDI and in combination with SDMX. We are also interested in the use of GSIM together with the Neuchâtel terminology for classifications and we are participating in a revision of the latter.