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GIS and the statistical production chain Lessons learned in the GEOSTAT projects

This article discusses the GEOSTAT projects, which aim to develop guidelines for linking census statistics to a harmonized grid. It explores the integration of GIS into the Statistical Production Chain (GSBPM) and highlights the importance of specifying needs, designing data structures, and analyzing and disseminating spatial data. The projects also emphasize the use of frameworks and the validation of outputs to ensure improved integration and harmonization.

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GIS and the statistical production chain Lessons learned in the GEOSTAT projects

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  1. GIS and the statistical production chainLessons learned in the GEOSTAT projects Ola Nordbeck Statistics Norway

  2. GEOSTAT • The GEOSTAT action is about developing guidelines for datasets and methods to link census statistics to a common harmonised grid • Builds on the knowledge of a partner network from various NSIs and the European Forum for GeoStatistics (EFGS) • Is currently in a third phase called GEOSTAT 1C that follow the 1A and 1B phase • Material developed so far can be found at the EFGS.info website • Financed by ESS (European Statistical System)

  3. Traditional GIS workflow Collect and store Process Manipulate and analyse Disseminate

  4. The Statistical production chain = GSBPM • The Statistical production chain: • for assessing the possibilities and the need for standardisation and improvement of processes within NSIs • also known as the Generic Statistical Business Process Model (GSBPM) • GSBPM and has a widespread support in the international statistical community • GSBPM is a tool for planning: • new statistics, • activities to improve existing work processes, reduce risks and achieve better documentation • trainings

  5. Generic Statistical Business Process Model (GSBPM) A model on three levels: from general description to more detailed levels

  6. Integration of the GIS workflow into GSBPM • GEOSTAT 1B tried to integrate GIS into GSBPM • For GIS staff the GSBPM is an important communication tool in a Statistical Institute (NSI), since it allows: • Non-GIS staff to relate to the GIS work flow • GIS-staff to identify synergies in the NSI • A NSI to efficiently plan their activities with GIS as a part of GSBPM

  7. Phase 1: Specify needs • This phase is challenging and crucial for the GIS activities in a NSI due to: • that the needs are currently mostly understood and defined by external partners and not by NSI staff • make an NSI to prioritise GIS activities • see it as a part of a NSIs core activities • give examples of how GIS can result in better statistics • obtain efficiency • Important to answer the whys, whats and draft the hows • Initiatives in Eurostat and United Nations are aiming for more integration in between geography and statistics • GEOSTAT describes the need for spatially referenced statistics in a hierarchical system of stable and neutral grids

  8. Phase 2: Design • External Spatial Data Infrastructure frameworks as INSPIRE forms the NSIs’ data structure and internal geo-infrastructure • The GEOSTAT projects have also developed frameworks for GIS activities in NSIs: • Design data structure • http://www.efgs.info/geostat/1B/guidelines/efgs-standard-for-official-statistics-population-variables • Design of metadata and quality assessment parameters • http://www.efgs.info/geostat/1B/guidelines/efgs-modified-quality-assessment-parameters

  9. Phase 3-5: Build, collect and process • Based on the design of the methodological framework • Various types of primary data in the GEOSTAT project resulted in two different approaches to producing population grids: • Aggregation approach • Hybrid or mixed approach • In the individual NSI this is a continuous implementation of the predefined design striving for: • Collection of standardised (format and coordinate systems) georeferenced statistical microdata • Collection and processing routines of georeferenced data equal to the routines for other microdata

  10. Phase 6: Analyse • The GEOSTAT project found it important to focus on the following parts in the Analyse phase: “prepare draft results” and “validate outputs” • Prepare draft results to determine if GEOSTAT1B guidelines resulted in an improved integration and harmonisation of individual contributions • Validate outputs to test and validate the population grid with a case studies

  11. Phase 7: Disseminate • Disseminating spatial data needs to be adapted to INSPIRE directive considering; • Metadata • Data structure • Data services: web map service (wms), web feature service (wfs) and web coverage service (wcs) • The dissemination in the GEOSTAT project is so far related to posters and reports. However, the metadata and the data structure related to the GEOSTAT 2011 population grid is in adapted to the INSPIRE directive

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