TY - JOUR
T1 - An analysis of existing production frameworks for statistical and geographic information
T2 - Synergies, gaps and integration
AU - Ariza-López, Francisco Javier
AU - Rodríguez-Pascual, Antonio
AU - Lopez-Pellicer, Francisco J.
AU - Vilches-Blázquez, Luis M.
AU - Villar-Iglesias, Agustín
AU - Masó, Joan
AU - Díaz-Díaz, Efrén
AU - Ureña-Cámara, Manuel Antonio
AU - González-Yanes, Alberto
N1 - Publisher Copyright:
© 2021 by the authors. Licensee MDPI, Basel, Switzerland.
PY - 2021/6
Y1 - 2021/6
N2 - 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.
AB - 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.
KW - Framework
KW - Geospatial information
KW - Interoperability
KW - Statistical data
UR - http://www.scopus.com/inward/record.url?scp=85108544151&partnerID=8YFLogxK
U2 - 10.3390/ijgi10060374
DO - 10.3390/ijgi10060374
M3 - Artículo
AN - SCOPUS:85108544151
SN - 2220-9964
VL - 10
JO - ISPRS International Journal of Geo-Information
JF - ISPRS International Journal of Geo-Information
IS - 6
M1 - 374
ER -