Data Quality and Participant Engagement in Citizen Science: Comparing Two Approaches for Monitoring Pollinators in France and South Korea

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Citizen science has become a mainstream approach for collecting data on biodiversity. However, not all biodiversity monitoring programs achieve the goal of collecting datasets that can be used in robust scientific inquiries. Data quality and the capacity to engage participants in the long-term are the most challenging issues. We compared two methodologies of citizen science programs dedicated to pollinators monitoring in France (Spipoll) and South Korea (K-Spipoll). These programs aimed to launch long-term monitoring at a community-level to better understand environmental effects on the composition and stability of pollinator communities. We assessed, through different metrics, how the two approaches influenced (1) data quality (assessed by “Accuracy in data collection,” “Consistency in protocol relative to volume of sessions contributed by an individual,” “Spatial representation of data,” and “Sample size”), and (2) participant engagement (assessed by “the number of connected days,” “the number of active days,” “the proportion of participant contributing a single session,” “the average number of sessions per participant,” and “the distribution of numbers of contributions per participant in each program.”). On one hand, participants in the Spipoll program abided by the standard protocol more often and provided identification for the photographed insects, leading to efficient ecological analyses. On the other hand, the K-Spipoll program provided more sessions per participant and a lower rate of single participation, with a full session demanding less effort in terms of data input, providing critical data where baseline data have otherwise been unavailable. These differences have emerged through methodology choices: For the Spipoll, the dedicated website favored the emergence of a social network that facilitated identification and increased data quality; for the K-Spipoll, the development of a cell phone application facilitated participation, and regular on-field education sessions motivated participants. We conclude by providing suggestions for the implementations of future citizen science programs to improve both data quality and participant engagement.