Citizen Science and Crowd Science

Citizen science and crowd science (CS) projects involve members of the public who participate in response to an open call and who can perform a broad range of research tasks. Scholars using the citizen science lens focus on the fact that many participants do not have formal scientific training, while scholars using the crowd science lens emphasize that participants are often recruited through an open call. CS projects have resulted in large-scale data sets, novel discoveries, and top-tier publications (i.e., scientific impact), but they can also have large societal and practical impacts by increasing the relevance of research or accomplishing other objectives such as science education and building awareness. The diverse landscape of CS projects reflects five underlying paradigms that capture different rationales for involving crowds and that require different organizational setups: crowd volume, broadcast search, user crowds, community production, and crowd wisdom. Within each CS project, the breadth of crowd involvement can be mapped along stages of the research process (e.g., formulating research questions, designing methods, collecting data). Within each stage, the depth of crowd involvement can be mapped with respect to four general types of contributions: activities, knowledge, resources, and decisions. Common challenges of CS projects relate to recruiting and engaging participants, organizational design, resource requirements, and ensuring the quality of contributions. Opportunities for future research include research on the costs and boundary conditions of CS as well as systematic assessments of different aspects of performance and how they relate to project characteristics. Future research should also investigate the role of artificial intelligence both as worker who can take over tasks from crowd members and as manager who can help organize CS activities.