We recently published a new paper on the integration of geographic information into survey research. The paper is the outcome of a collaborative effort with colleagues from the Leibnitz Institute for the Social Sciences (GESIS) in Mannheim and from the University of Salzburg (Z_GIS) and it provides an overview of how the consideration of geographic information can benefit traditional surveys. The inclusion of explicitly geospatial information opens up a wealth of additional insights and enables novel kinds of social empirical research. For instance, using geolocated data allows precise connections between causal context factors and survey responses can be established. The article further outlines in which ways GIS tools can expand the scope of traditional surveys. For example, recent developments like participatory GIS or the emergence of volunteered geographic information may be very valuable in terms of delivering layers of information that are not feasible without using GIScience concepts. Survey researchers may use these tools in the future to gain insights on geometric or topological constructions of geographic areas related to survey questions. These exist in the minds of people as mental maps, and the oftentimes unconscious nature of user-generated geographic information is akin to depictions of these. Another primer of the paper is on highlighting of methodological parallels between new data sources like geosocial media and in-situ survey responses. Both are subject to contextual influences and thus deliver additional information. However, with regard to data handling, modelling and analysis, both types of data are challenging from a methodological and conceptual viewpoint. The paper concludes by highlighting the points of contact between GIScience and Survey Research and explains how they can lead to a common future research agenda.
Bluemke, M., Resch, B., Lechner, C., Westerholt, R. and Kolb, JP. (2017): Integrating Geographic Information into Survey Research: Current Applications, Challenges and Future Avenues. Survey Research Methods, 11 (3), 307-327. DOI: 10.18148/srm/2017.v11i3.6733.