Assessing data quality in citizen science

Kosmala, Margaret and Wiggins, Andrea and Swanson, Alexandra and Simmons, Brooke (2016) Assessing data quality in citizen science. Frontiers in Ecology and the Environment, 14 (10). pp. 551-560. ISSN 1540-9295

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Ecological and environmental citizen‐science projects have enormous potential to advance scientific knowledge, influence policy, and guide resource management by producing datasets that would otherwise be infeasible to generate. However, this potential can only be realized if the datasets are of high quality. While scientists are often skeptical of the ability of unpaid volunteers to produce accurate datasets, a growing body of publications clearly shows that diverse types of citizen‐science projects can produce data with accuracy equal to or surpassing that of professionals. Successful projects rely on a suite of methods to boost data accuracy and account for bias, including iterative project development, volunteer training and testing, expert validation, replication across volunteers, and statistical modeling of systematic error. Each citizen‐science dataset should therefore be judged individually, according to project design and application, and not assumed to be substandard simply because volunteers generated it.

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Journal Article
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Frontiers in Ecology and the Environment
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This is the peer reviewed version of the following article: Assessing data quality in citizen science. Frontiers in Ecology and the Environment. doi: 10.1002/fee.1436 which has been published in final form at This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving.
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21 Sep 2018 10:30
Last Modified:
17 Sep 2023 02:21