Doing Qualitative Research Using GIS: An Oxymoronic Endeavor?
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TL;DR
The contributors originally presented their papers in organized sessions on `Qualitative Research and GIS'' at recent annual meetings of the Association of American Geographers, in which they were asked to address the broader epistemological and theoretical questions associated with the use of GIS in qualitative research.
Abstract
Doing qualitative research using GIS: an oxymoronic endeavor?Geographical information systems (GIS) have been largely understood as a tool for the storage and analysis of quantitative data since the early days of their development.It seems `natural' to consider a tool implemented through computing technology as a means for handling quantitative dataöbecause what the computer can process is `digital' by nature and digital is often taken to mean `numerical'.This understanding of GIS has underpinned much of the critical discourse on GIS in the 1990s, in which both GIS critics and researchers considered GIS mainly as an apparatus for positivist/ empiricist science or quantitative methods (for example, Openshaw, 1991).This debate led to an understanding of geographical methods that places GIS at one pole of a series of binariesöpositivist/quantitative/GIS methods versus critical/qualitative methods, and GIS/spatial analysis versus social/critical geographies (Kwan, 2004).There have been attempts in recent years to redress this particular understanding of GIS and to conceive other possibilities of using GIS in geographic research.For instance, Eric Sheppard (2001) argues that GIS practices are not necessarily quantitative, empiricist, or positivist because GIS can handle other types of information (photographs, videos, or narratives) and ``can incorporate situated knowledge and ethnographic material'' (page 547).Mei-Po Kwan (2002a; 2002b) extends these arguments to address issues raised specifically by feminist critiques of science and vision.Drawing upon diverse sources including feminist theories of the body, subjectivity, art, and visual methodologies, she suggests that GIS users or researchers can engage in reenvisioning GIS as a critical practice that is congenial to feminist epistemologies and politics.Both authors have conceived alternative GIS practices for understanding people's lived experiences in an interpretive manner rather than for conducting spatial analysis that relies largely on quantitative geographical information.An important development in this direction is the emergence of studies that explore the possibility of using GIS in qualitative research (for example, Cieri, 2003;Ding and Kwan, 2004;Nightingale, 2003;Pavlovskaya, 2002; 2004).However, to date there has been no systematic treatment or collection of articles for researchers to draw upon as a resource on issues pertinent to the use of GIS in qualitative research.We hope to fill this gap through the papers in this theme issue.All of the contributors originally presented their papers in organized sessions on ``Qualitative Research and GIS'' at recent annual meetings of the Association of American Geographers, in which they were asked to address the broader epistemological and theoretical questions associated with the use of GIS in qualitative research, on the basis of their own experiences.The first paper by Marianna Pavlovskaya ( 2006) provides an insightful discussion of theoretical issues related to the distinction between qualitative and quantitative methods.She explores the potential of using GIS in qualitative research through interrogating the conventional association of GIS with quantitative methods.Critically examining the construction of the opposition between quantitative and qualitative methods in geography and the process of delinking of epistemologies and methods that has occurred in the last decade, she argues that GIS are often not as quantitative as many geographers assume.Through revisiting the relationship between GIS and computer science, spatial analysis, data representation, visualization, database management, mathematical modeling, and statistics, Pavlovskaya suggests that there
