Private, Public, Personal
Shifting Patterns in Geospatial Data Sources in Geographic Research
Bibliographic Data
| ID | 3775411 |
|---|---|
| Authors | Gabriel Appiah (0000-0001-9303-6018, Georgia Institute of Technology, corresponding author), Mira Kaufman (Georgia Institute of Technology), Billy Cooney (Georgia Institute of Technology), Clio Andris (0000-0002-8559-5079, Georgia Institute of Technology) |
| Year | 2025 |
| Volume | 115 |
| Issue | 1 |
| Pages | 39-57 |
| Publication date | 2025-01-02 |
| Open Access | No |
| Type | ARTICLE |
| Venue | Annals of the American Association of Geographers (JOURNAL) |
| Journal identifiers | ISSN: 2469-4452 • E-ISSN: 2469-4460 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/24694452.2024.2394078 |
| OpenAlex | W4402831621 |
| Language | EN |
| Citations received | 1 |
| References cited | 71 |
Geospatial data sources include data collected by the public sector (i.e., government), private sector (i.e., industry), or through field work. Of these categories, the private sector, especially through tech firms, has provided new types of cutting-edge data sets that are particularly large and novel. These include data from social media platforms and location-based technologies such as Global Positioning Systems and mobile phones. Here, we explore the extent to which peer-reviewed geospatial research has adopted these data sources, perhaps in lieu of more traditional data types. We review peer-reviewed journal articles from six flagship journals in geographic information systems, geography, and urban analytics that publish research that uses spatial data analysis. We find that geospatial researchers continue to rely on government-collected data for their research, but that researchers’ use of data from the private sector have increased in recent years. This finding implies that as spatial analysis studies increasingly rely on private data sets, we should revisit (1) how industry data collection faces fewer regulations on data quality and has different motivations for their collection, (2) how this affects our ability to trust our data sets, and (3) the role of government and field work in data collection and dissemination in the future
Cartography · Data science · Environmental planning · Environmental resource management · Geographic information system · Geography · Geospatial analysis · GIS and public health · Public participation GIS · Regional science · Computer Science · Data-Driven Disease Surveillance · Environmental Science · Geographic Information Systems Studies · Research Data Management Practices
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| Citations per year | 1 |
|---|---|
| Citation span | 2026 - 2026 (1) |
| Highly cited | No |