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Leveraging Big (Geo) Data with (Geo) Visual Analytics: Place as the Next Frontier

  • Alan M. MacEachrenEmail author
Chapter
Part of the Advances in Geographic Information Science book series (AGIS)

Abstract

A tension exists in the discipline of Geography between the concepts of space and place. Most research and development in Geographical Information Science (GIScience) has been focused on the former, through methods to formally structure data about the world and to systematically model and analyze aspects of the world as represented through those structured data. People, however, live and behave in socially constructed places; what they care about happens in those places rather than in some abstract, modeled ‘space’. Study of place, by human geographers (and other social scientists and humanist scholars), typically using qualitative methods and seldom relying on digital data, has proceeded largely independently of GIScience research focused on space. There have been calls within GIScience to formalize place to enable application of Geographical Information Systems methods to place-based problems, and some progress in this direction has been made. Here, however, a complementary view is offered for treating ‘place’ as a first class object of attention by capitalizing on the combination of “big data” and new human-centered visual analytical methods to enable understanding of the complexity inherent in place as both a concept and a context for human behavior.

Keywords

Visual analytics Big data Unstructured data Place versus space 

Notes

Acknowledgements

Examples in Section “Data Variety” were derived as part of the GeoTxt project, in collaboration with Jan Wallgrün, Morteza Karimzadeh, and Scott Pezanowski; A portion of this research was supported by the Visual Analytics for Command, Control, and Interoperability Environments (VACCINE) project, a center of excellence of the Department of Homeland Security, under Award #2009-ST-061-CI0001. See also: Wallgrün, Jan Oliver, Morteza Karimzadeh, Alan M. MacEachren, Frank Hardisty, Scott Pezanowski, and Yiting Ju. 2014. “Construction and First Analysis of a Corpus for the Evaluation and Training of Microblog/Twitter Geoparsers.” GIR’14: 8th ACM SIGSPATIAL Workshop on Geographic Information Retrieval, Dallas, TX.

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Copyright information

© Springer Nature Singapore Pte Ltd. 2017

Authors and Affiliations

  1. 1.GeoVISTA Center, Department of GeographyThe Pennsylvania State UniversityUniversity ParkUSA

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