Data-driven geography
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This wealth of data may serve as input for data-driven geography.
“This wealth of data may serve as input for what Miller and Goodchild called data-driven geography [126].”
From Opening up Smart Cities: Citizen-Centric Challenges and Opportunities from GIScience (2016) · cites this paper as [126]
With big data, the context of geographic research has shifted from a data-scarce to a data-rich environment.
“Miller and Goodchild commented that with big data, the context of geographic research has shifted from a data-scarce to a data-rich environment.”
From Opening up Smart Cities: Citizen-Centric Challenges and Opportunities from GIScience (2016) · cites this paper as [126]
Data-driven geography is an evolution of geography and can provide the paths between idiographic and nomothetic knowledge.
“They described data-driven geography as an evolution of geography, and argued that it can provide the paths between idiographic (i.e., description-seeking) and nomothetic (i.e., law-seeking) knowledge.”
From Opening up Smart Cities: Citizen-Centric Challenges and Opportunities from GIScience (2016) · cites this paper as [126]
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- Authors
- Miller, H. J., & Goodchild, M. F.
- Affiliations
- The Ohio State University (US)
- University of California, Santa Barbara (US)
- Corresponding author
- Miller, Harvey J.
- Goodchild, Michael F.
- Venue
- GeoJournal
- Published
- 2014-10-10
- Volume
- 80
- Issue
- 4
- Pages
- 449-461
- ISSN
- 0343-2521 (ISSN-L)
- 1572-9893
- OpenAlex
- W2006047816
- Cited by
- 391
- References
- 69
- Citations by year
- 2026: 22 · 2025: 19 · 2024: 23 · 2023: 20 · 2022: 32 · 2021: 36 · 2020: 54 · 2019: 60 · 2018: 46 · 2017: 41 · 2016: 21 · 2015: 12 · 2014: 1 · 2013: 1
- FWCI
- 176.84
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- GeoJournal (publishedVersion)
- Topics
- Social Sciences › Geography, Planning and Development › Geographic Information Systems Studies
- Social Sciences › Decision Sciences › Information Systems and Management › Big Data Technologies and Applications
- Social Sciences › Transportation › Human Mobility and Location-Based Analysis
- Keywords
- big data, georeferenced records, sensor data, messy data, spatial context, time geography, geographic information science, geographic knowledge discovery, spatial modeling, data cleaning, spurious patterns, model interpretability
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