Perceptions, requirements, and reality: Barriers to full integration of citizen science in professional science

Background/Question/Methods

Citizen science, or public participation in science, is a rapidly expanding field that has the potential to democratize science, increase the rate of scientific discovery, and facilitate cost-effective research. Although some professional scientists are leveraging this tool for their research, citizen science projects and data are generally not well integrated with professional academic research. Citizen science has been touted as a means to solve problems of data collection at large temporal and geographic scales, but how do the data generated by citizen science compare to the data needs of professional scientists? Using peer-reviewed publications as one measure of successful integration, and biodiversity citizen science as a case study, we surveyed citizen science project managers (n=125), and  biodiversity scientists (n=423) to assess: 1) what factors influence whether professional scientists have published peer-reviewed articles using citizen science data, and 2) how the reality of citizen science compares to scientists’ perceptions of citizen science data, including scientists’ research practices and data requirements. We employed robust non-parametric recursive modeling and descriptive statistical techniques to identify the  primary factors influencing the use of citizen science data in peer-reviewed scientific literature.

Results/Conclusions

A combination of perceptions of data quality, narrow awareness of suitable citizen science projects, and preferences for data from certain data sources (academic institutions and college student data collectors) could be limiting scientist use of citizen science data. Interestingly, scientists’ preferences do not correlate with publication probability among citizen science projects. Factors associated with citizen science peer-reviewed publication include having publication as a goal, large participant numbers, and pre-tests during training. Further comparison of professional scientists’ data requirements and citizen science practices suggests that citizen science is largely meeting certain biodiversity research needs (e.g., location, presence, and absence is recorded), although other requirements are rare among projects (e.g., standardization of effort). Lastly, the strongest predictor of professional scientists using citizen science in their publications is an awareness of citizen science projects relevant to their research; that most scientists are unaware of relevant projects but would consider using citizen science data suggests broader visibility of citizen science may enable collaborations. If scientists are more aware of citizen science projects and rely on project characteristics instead of their perceptions of projects, and citizen science is responsive to scientists’ research requirements, we predict an increase in public participation in meaningful scientific research.