An On-the-Ground Challenge to Uses of Spatial Big Data in Assessing Neighborhood Character

Datos Bibliográficos

ID4489309
AutoresBloch (0000-0002-4021-4391, autor de correspondencia)
Año2020
Volumen110
Número1-2
Páginas210-223
Fecha de publicación2020-01-02
Peer ReviewedSí
Open AccessSí
TipoARTICLE
RevistaGeographical Review (JOURNAL)
Identificadores de la revistaISSN: 0016-7428 • E-ISSN: 1931-0846
EditorialInforma UK Limited (PUBLISHER • GB)
DOI10.1111/gere.12357
OpenAlexW2939442643
IdiomaEN
Citas recibidas11
Referencias citadas42

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

Aesthetics · Art · Big data · Character (mathematics · Common ground · Data mining · Data science · Epistemology · Ethnography · Graffiti · Media studies · Simplicity · Sociology · Computer Science · Geographies of human-animal interactions · Public Spaces through Art