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Health, Science, and Place pp 77–87Cite as

Geospatial Data Mining and Knowledge Discovery

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Part of the book series: Geotechnologies and the Environment ((GEOTECH,volume 12))

Abstract

This chapter surveys three emerging issues concerning geospatial data mining: the need to extend patient privacy protections beyond HIPAA, the use of geospatial visualization and data mining algorithms in medical geographic research, and the growth of geospatial data mining applications in public health. Geospatial data mining is the process of discovering interesting patterns in large and disparate geographic datasets so that the information is meaningful and useful to decision-makers. It involves geo-statistical algorithms, which are used for prediction, classification, and for finding interesting patterns in the data, such as associations, clusters and subgroups. A major challenge in the discipline of public health is harvesting knowledge discovery from the growing volume of data, because the discipline is a knowledge-intensive domain. Most health care applications are data-intensive and involve sophisticated data mining techniques. Since health is a geographical phenomenon, geospatial technologies play an important role in strengthening the process of epidemiological surveillance, information management and analysis.

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Authors and Affiliations

  1. TerraFirm International Corp., Inc., Wayne, PA, USA

    Amy J. Blatt

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  1. Amy J. Blatt
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© 2015 Springer International Publishing Switzerland

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Blatt, A.J. (2015). Geospatial Data Mining and Knowledge Discovery. In: Health, Science, and Place. Geotechnologies and the Environment, vol 12. Springer, Cham. https://doi.org/10.1007/978-3-319-12003-4_7

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