Pritchard, R., Sauls, L.A. orcid.org/0000-0001-8868-7465, Oldekop, J. et al. (2 more authors) (2022) Data justice and biodiversity conservation. Conservation Biology, 36 (5). e13919. ISSN 0888-8892
Abstract
Increases in data availability coupled with enhanced computational capacities are revolutionizing conservation. But in the excitement over the opportunities afforded by new data, there has been less discussion of the justice implications of data used in conservation, that is, how people and environments are represented through data, the conservation choices made based on data, and the distribution of benefits and harms arising from these choices. We propose a framework for understanding the justice dimensions of conservation data composed of five elements: data composition, data control, data access, data processing and use, and data consequences. For each element, we suggest a set of guiding questions that conservationists could use to think through their collection and use of data and to identify potential data injustices. The need for such a framework is illustrated by a synthesis of recent critiques of global conservation prioritization analyses. These critiques demonstrate the range of ways data could serve to produce social and ecological harms due to the choice of underlying data sets, assumptions made in the analysis, oversimplification of real-world conservation practice, and crowding out of other forms of knowledge. We conclude by arguing that there are ways to mitigate risks of conservation data injustices, through formal ethical and legal frameworks and by promoting a more inclusive and more reflexive conservation research ethos. These will help ensure that data contribute to conservation strategies that are both socially just and ecologically effective.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2022 The Authors. Conservation Biology published by Wiley Periodicals LLC on behalf of Society for Conservation Biology. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, (http://creativecommons.org/licenses/by-nc-nd/4.0/) which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made. |
Keywords: | Equity; big data; remote sensing; datification; global analyses; critical data studies; political ecology |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Social Sciences (Sheffield) > Department of Geography (Sheffield) |
Funding Information: | Funder Grant number LEVERHULME TRUST (THE) ECF-2019-665 |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 15 Jun 2022 14:13 |
Last Modified: | 27 Jan 2023 15:24 |
Status: | Published |
Publisher: | Wiley |
Refereed: | Yes |
Identification Number: | 10.1111/cobi.13919 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:187925 |