Data colonialism through accumulation by dispossession: New metaphors for daily data
Open accessAbstract
In recent years, much has been written on ‘big data’ in both the popular and academic press. After the hubristic declaration of the ‘end of theory’ more nuanced arguments have emerged, suggesting that increasingly pervasive data collection and quantification may have significant implications for the social sciences, even if the social, scientific, political, and economic agendas behind big data are less new than they are often portrayed. Compared to the boosterish tone of much of its press, academic critiques of big data have been relatively muted, often focusing on the continued importance of more traditional forms of domain knowledge and expertise. Indeed, many academic responses to big data enthusiastically celebrate the availability of new data sources and the potential for new insights and perspectives they may enable. Undermining many of these critiques is a lack of attention to the role of technology in society, particularly with respect to the labor process, the continued extension of labor relations into previously private times and places, and the commoditization of more and more aspects of everyday life. In this article, we parse a variety of big data definitions to argue that it is only when individual datums by the million, billion, or more are linked together algorithmically that ‘big data’ emerges as a commodity. Such decisions do not occur in a vacuum but as part of an asymmetric power relationship in which individuals are dispossessed of the data they generat…
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Preventing people from accessing their personal data through accumulation by dispossession parallels the primitive accumulation of land enclosure movements that separated producers from the means of production.
“preventing people from accessing their personal data through processes of accumulation by dispossession (Harvey 2003) parallels the primitive accumulation of the land enclosure movements that separated the producers from the means of production”
From Social Injustice in Surveillance Capitalism (2017) · cites this paper as Thatcher et al. 2016
The economic value of personal data is largely realized in aggregate patterns and future potential that become visible when data points are linked together through data analytics and algorithmic processing.
“the economic value of personal data is largely realized in the aggregate-patterns and future potential become visible when data points are linked together through data analytics and algorithmic processing (Thatcher et al. 2016).”
From Social Injustice in Surveillance Capitalism (2017) · cites this paper as Thatcher et al. 2016
Data about one individual's actions or properties at one moment needs to be combined with data about other actions, moments, and properties to generate valuable relations between data points.
“second, data about one individual's actions or properties at one moment needs to be combined with data about other actions, moments, and properties to generate valuable relations between data points (Arvidsson 2016;Thatcher et al. 2016, 995).”
From Data colonialism: rethinking big data’s relation to the contemporary subject (2019) · cites this paper as Thatcher et al. 2016
Data appropriation is a form of fundamental appropriation of resource or extraction.
“More helpful are approaches which see what is going on with data as a form of fundamental appropriation of resource (Greene and Joseph 2015;Thatcher et al. 2016, drawing on Harvey 2004) or extraction (Mezzadra and Neilson 2017).”
From Data colonialism: rethinking big data’s relation to the contemporary subject (2019) · cites this paper as Thatcher et al. 2016
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Data colonialism: rethinking big data’s relation to the contemporary subject
Couldry, N., & Mejias, U. A. (2019) · Television & New Media · doi:10.1177/1527476418796632 · Cited by 1,617 · see citing works
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Social Injustice in Surveillance Capitalism
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“In any case, the economic value of personal data is largely realized in the aggregate—patterns and future potential become visible when data points are linked together through data analytics and algorithmic processing (Thatcher et al. 2016).”
BackgroundStevens, N., & Gieseking, J. J. (2026) · Transactions of the Institute of British Geographers · doi:10.1111/tran.70046 · Cited by 2 · see citing works
- Authors
- Thatcher, J., O’Sullivan, D., & Mahmoudi, D.
- Affiliations
- University of Washington Tacoma (US)
- University of California, Berkeley (US)
- Portland State University (US)
- Corresponding author
- Thatcher, Jim
- Venue
- Environment and Planning D: Society and Space
- Publisher
- SAGE Publications
- Published
- 2016-07-26
- Volume
- 34
- Issue
- 6
- Pages
- 990-1006
- ISSN
- 0263-7758 (ISSN-L)
- 1472-3433
- OpenAlex
- W2298562067
- Cited by
- 512
- References
- 4
- Citations by year
- 2026: 49 · 2025: 68 · 2024: 69 · 2023: 68 · 2022: 60 · 2021: 75 · 2020: 43 · 2019: 42 · 2018: 23 · 2017: 9 · 2016: 6
- FWCI
- 64.63
- Type
- journal article
- Language
- en
- Open access
- green
- papers.ssrn.com
- Locations
- Environment and Planning D Society and Space (publishedVersion)
- University of Washington Tacoma Digital Commons (University of Washington Tacoma) (submittedVersion)
- PDXScholar (Portland State University) (submittedVersion)
- SSRN Electronic Journal (submittedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Maryland Shared Open Access Repository (USMAI Consortium) (submittedVersion)
- Digital Repository at the University of Maryland (University of Maryland College Park)
- Topics
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Social Sciences › Communication › Cultural Studies and Postmodernism
- Social Sciences › Sociology and Political Science › Political Economy and Marxism
- Keywords
- data colonialism, accumulation by dispossession, big data, commodification of everyday life, data commodification, power imbalance, everyday life
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