Merging statistics and geospatial information, 2016 projects - Slovakia
Merging statistics and geospatial information in Member States – implementation of a GIS solution; 2016 project; final report February 2019
This article forms part of Eurostat’s statistical report on the Integration of statistical and geospatial information.
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Problem
The statistical office does not have a dedicated GIS department and only a few members of staff can work with GIS.
Objectives
Based on a SWOT analysis, the project provides an opportunity to improve technical solutions for the implementation of GIS within the existing infrastructure of the statistical office, for a wide spectrum of internal users (mostly sponsors of various surveys).
The main aim is to improve efficiency of creating statistical outputs, reduce the burden on trained staff, provide GIS tools for a wider spectrum of users, establish a GIS solution, integrate official statistics and spatial data, make the analysis of data more effective.
The project was to meet these objectives by providing user-friendly GIS tools. It was seen as a first step towards the further integration of statistical and spatial data.
Method
The first part of the work was an assessment of the technical infrastructure, in other words the ArcGIS platform developed for the GEOSTAT Census 2011. Following this assessment, ArcGIS server/portal, ArcGIS extension for Microsoft Office and ArcGIS extension for IBM BI Cognos were installed.
The second part was defining data structures and optimising datasets. For this study, datasets were used from business statistics and from population and living standards statistics. A geographical dimension was added to connect these datasets with spatial data.
The third part involved the production of output integrating survey data and geodata. Data were published within regular publications, through a web portal and within internal reports.
Results
Software was installed for use by IT staff and by other users within the statistical office. Training was provided to IT staff and to users.
Data models were developed for different statistical datasets in order to incorporate spatial data.
Data were published and used internally.
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