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Cited by 387

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Grounded Visualization: Integrating the Analysis of Qualitative and Quantitative Data through Grounded Theory and Visualization

Open access
Knigge, LaDona, Cope, Meghan·2006·Environment and Planning A: Economy and Space

Abstract

Our purpose in this paper is to conceptualize and demonstrate an integrated analytical method for using both qualitative and quantitative data through geographic information systems (GIS) and ethnography. We acknowledge that the use of both types of data has been possible in GIS for some time, particularly for representation purposes. However, a recursive integration of different forms of data at the analysis level has been less explored and minimally theorized. Drawing on recent work in critical GIS and feminist perspectives, we suggest that visualization offers a strong technique for this effort but we approach it from the analytical base of grounded theory. Thus, we present an example of how grounded theory and visualization might be used together to construct an integrated analysis strategy that is both iterative and reflexive, both contextual and conceptual. We use Knigge's work on community gardens in Buffalo, New York, to provide a substantive example of the proposed methods.

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Crossref · 10.1068/a37327

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Metadata

Authors
Knigge, L., & Cope, M.
Venue
Environment and Planning A: Economy and Space
Published
2006-11
Volume
38
Issue
11
Pages
2021-2037
ISSN
  • 0308-518X (ISSN-L)
  • 1472-3409
OpenAlex
W2122322468
Cited by
387
References
2
FWCI
43.66
Type
journal article
Language
en
Open access
hybrid

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CoChat. (2026). Citation check: Grounded Visualization: Integrating the Analysis of Qualitative and Quantitative Data through Grounded Theory and Visualization. https://app.cochat.ai/papers/10.1068/a37327
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Knigge, L., & Cope, M. (2006). Grounded Visualization: Integrating the Analysis of Qualitative and Quantitative Data through Grounded Theory and Visualization. Environment and Planning A: Economy and Space. https://doi.org/10.1068/a37327

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.