LAUSR

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.