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Abstract:
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Geographic Information Systems (GIS) comprises a powerful avenue for researchers to take advantage of spatial data. We have seen widespread expansion of the power and scope of GIS over the past decades due to advances in computing power, cloud-based storage, and the proliferation of mobile devices for data collection. In the social sciences generally and survey research world specifically, GIS may be employed prior to, during, and after data collection in multiple ways. For example, a researcher may geocode address information in advance of a study, plot survey respondents during production, and conduct data linkage and spatial statistics post-hoc. As GIS is preoccupied with representing geographic information and enabling subsequent analysis, the total survey error (TSE) framework applies at multiple stages. For example, geographic data models themselves contain generalization at all scales, prior to any analysis. We explore aspects of TSE that are specific to GIS and carry implications for researchers in the social sciences.
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