Citizen Science: Theory and Applications

Citizen science (CS) is a collaborative research approach that involves the public in scientific research, with volunteers working alongside professionals to collect data. This model serves a dual purpose of educating the public on specific topics and providing valuable data to scientists. Although CS facilitates extensive data collection across broad areas at low costs, concerns arise regarding data accuracy compared to expert-driven methods. In biodiversity-focused CS initiatives, challenges like species misidentification pose significant concerns, impacting data quality. One potential solution involves implementing a ‘verified’ method, where all citizen-collected data undergo expert verification, though this incurs higher costs. This study specifically explores the role of CS programmes in bee research, addressing challenges such as misidentifications arising from visual similarities among bee species. Strategies to enhance accuracy include simplified identification tools, targeted approaches focusing on specific bee species or plants, and grouping bees for easier identification. In conclusion, CS programmes act as a crucial bridge between professionals and enthusiasts, contributing to conservation efforts and advancing our understanding of bees. The integration of digital technologies, emphasis on training, and participant motivations collectively enhance the success of these programmes in effectively monitoring and preserving bee populations.