TY - JOUR
T1 - An infrastructure for spatial linking of survey data
AU - Bensmann, Felix
AU - Heling, Lars
AU - Jünger, Stefan
AU - Mucha, Loren
AU - Acosta, Maribel
AU - Goebel, Jan
AU - Meinel, Gotthard
AU - Sikder, Sujit
AU - Sure-Vetter, York
AU - Zapilko, Benjamin
N1 - Publisher Copyright:
© 2020 The Author(s).
PY - 2020
Y1 - 2020
N2 - Research on environmental justice comprises health and well-being aspects, as well as topics related to general social participation. In this research field, among others, there is a need for an integrated use of social science survey data and spatial science data, e.g. for combining demographic information from survey data with data on pollution from spatial data. However, for researchers it is challenging to link both data sources, because (1) the interdisciplinary nature of both data sources is different, (2) both underlie different legal restrictions, in particular regarding data privacy, and (3) methodological challenges arise regarding the use of geo-information systems (GIS) for the processing and analysis of spatial data. In this article, we present an infrastructure of distributed web services which supports researchers in the process of spatial linking. The infrastructure addresses the challenges researchers have to face during that process. We present an example case study on the investigation of environmental inequalities with regards to income and land use hazards in Germany by using georeferenced survey data of the GESIS Panel and the German Socio-economic Panel (SOEP), and by using spatial data from the Monitor of Settlement and Open Space Development (IOER Monitor). The results show that increasing income of survey respondents is associated with less exposure to land-use-related environmental hazards in Germany.
AB - Research on environmental justice comprises health and well-being aspects, as well as topics related to general social participation. In this research field, among others, there is a need for an integrated use of social science survey data and spatial science data, e.g. for combining demographic information from survey data with data on pollution from spatial data. However, for researchers it is challenging to link both data sources, because (1) the interdisciplinary nature of both data sources is different, (2) both underlie different legal restrictions, in particular regarding data privacy, and (3) methodological challenges arise regarding the use of geo-information systems (GIS) for the processing and analysis of spatial data. In this article, we present an infrastructure of distributed web services which supports researchers in the process of spatial linking. The infrastructure addresses the challenges researchers have to face during that process. We present an example case study on the investigation of environmental inequalities with regards to income and land use hazards in Germany by using georeferenced survey data of the GESIS Panel and the German Socio-economic Panel (SOEP), and by using spatial data from the Monitor of Settlement and Open Space Development (IOER Monitor). The results show that increasing income of survey respondents is associated with less exposure to land-use-related environmental hazards in Germany.
KW - Environmental justice
KW - Georeferenced survey data
KW - Research infrastructure
KW - Semantic web technologies
KW - Spatial data
KW - Spatial linking
UR - http://www.scopus.com/inward/record.url?scp=85088891308&partnerID=8YFLogxK
U2 - 10.5334/DSJ-2020-027
DO - 10.5334/DSJ-2020-027
M3 - Article
AN - SCOPUS:85088891308
SN - 1683-1470
VL - 19
SP - 1
EP - 18
JO - Data Science Journal
JF - Data Science Journal
IS - 1
M1 - 27
ER -