An analysis of existing production frameworks for statistical and geographic information: Synergies, gaps and integration

The production of official statistical and geospatial data is often in the hands of highly specialized public agencies that have traditionally followed their own paths and established their own production frameworks. In this article, we present the main frameworks of these two areas and focus on the...

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Detalhes bibliográficos
Autores: Ariza-López, F.J., Rodríguez-Pascual, A., Lopez-Pellicer, F.J., Vilches-Blázquez, L.M., Villar-Iglesias, A., Masó, J., Díaz-Díaz, E., Ureña-Cámara, M.A., González-Yanes, A.
Formato: artículo
Estado:Versión publicada
Fecha de publicación:2021
País:España
Recursos:Universidad de Zaragoza
Repositorio:Zaguán. Repositorio Digital de la Universidad de Zaragoza
OAI Identifier:oai:zaguan.unizar.es:109723
Acesso em linha:http://zaguan.unizar.es/record/109723
Access Level:acceso abierto
Descrição
Resumo:The production of official statistical and geospatial data is often in the hands of highly specialized public agencies that have traditionally followed their own paths and established their own production frameworks. In this article, we present the main frameworks of these two areas and focus on the possibility and need to achieve a better integration between them through the interoperability of systems, processes, and data. The statistical area is well led and has well-defined frameworks. The geospatial area does not have clear leadership and the large number of standards establish a framework that is not always obvious. On the other hand, the lack of a general and common legal framework is also highlighted. Additionally, three examples are offered: the first is the application of the spatial data quality model to the case of statistical data, the second of the application of the statistical process model to the geospatial case, and the third is the use of linked geospatial and statistical data. These examples demonstrate the possibility of transferring experiences/advances from one area to another. In this way, we emphasize the conceptual proximity of these two areas, highlighting synergies, gaps, and potential integration. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.