An Infrastructure for Spatial Linking of Survey Data

• Main Authors: Felix Bensmann, Lars Heling, Stefan Jünger, Loren Mucha, Maribel Acosta, Jan Goebel, Gotthard Meinel, Sujit Sikder, York Sure-Vetter, Benjamin Zapilko
• Format: Article
• Language: English
• Published: Ubiquity Press 2020-07-01
• Series: Data Science Journal
• Subjects: spatial linking; georeferenced survey data; spatial data; environmental justice; research infrastructure; semantic web technologies
• Online Access: https://datascience.codata.org/articles/1066

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.