An On-the-Ground Challenge to Uses of Spatial Big Data in Assessing Neighborhood Character. Issue 1 (2nd January 2020)

• Record Type: Journal Article
• Authors: Bloch, Stefano
• Is Part Of: Geographical review. Volume 110:Issue 1/2(2020)
• Page Start: 210
• Page End: 223
• Publication Date: 2020-01-02
• Subjects: graffiti -- qualitative methods -- Google Street View -- 311 data -- terrain vague; Geography -- Periodicals; 910
• DOI: 10.1111/gere.12357
• Languages: English
• ISSNs: 0016-7428

Abstract

Abstract: While big spatial data is certainly useful as a means of getting to know a place, to get closer to actually understanding a place, the rigorous and sometimes slow process of conducting on‐the‐ground ethnographic fieldwork cannot be replaced, no matter the admittedly seductive size, speed, and simplicity offered by big data. In this article, I caution against the overreliance on Google Street View (GSV) and municipal call‐for‐service, or 311, data when assessing neighborhood character and conducting research on visual disorder. Visual and municipal spatial big data such as GSV and 311 calls are increasingly relied upon given twenty‐first century computational technologies and mixed methods research proclivities. However, as I argue with examples of personally producing and researching the placement of illegal graffiti in Los Angeles and Providence's terrains vague, there is simply no proxy for qualitative data that is collected on the ground.