The Known Unknowns: What Citizen Science Projects in Germany Know about Their Volunteers—And What They Don’t Know

Abstract

The citizen science landscape in Germany offers an enormous range for participation. More than 170 projects currently present themselves on the national citizen science platform. In 2020, we conducted a survey among 140 projects (participation rate 56%), and they provided information on the organisational framework and characteristics (disciplines, initiators, funding, and project goals), as well as on the academic researchers and the volunteering citizen scientists involved. A surprising result was that the level of knowledge about the volunteers is very low overall. Many projects deliberately do not collect personal data (e.g., on socio-demographic variables, knowledge, and behaviour), partly for data-protection reasons and partly because they are unsure about how to collect it due to a lack of instruments and standards. We aim to illustrate the complexity of this issue and discuss various dilemmas arising between theoretical aspirations and the pragmatic and procedural realities in practice. We conclude with suggestions for developing project-specific strategies to increase diversity and inclusion. We argue that the task of conducting accompanying research on participant diversity cannot be borne by individual projects alone and consider the development and implementation of co-creative and qualitative approaches suitable for this purpose.

Quality assurance indicators for environmental citizen science. Development of indicators for volunteer-based biodiversity monitoring.

“…Analysis of citizen science projects in Germany in the Humanities and Social Science by Göbel et al (2020) showed that people engaged in these projects are predominantly males over 50 years of age, with an academic background. Moczek et al (2021) presented similar findings for citizen science in the…”

Untitled

“…Analysis of citizen science projects in Germany in the Humanities and Social Science by Göbel et al (2020) showed that people engaged in these projects are predominantly males over 50 years of age, with an academic background. Moczek et al (2021) presented similar findings for citizen science in the…”

Community engagement and data quality: best practices and lessons learned from a citizen science project on birdsong

“…Citizen scientists should have been supported with more specific instructions for the recordings, i.e., how (smartphone orientation), where (regions), and when (during the night). Such a task-lead approach facilitates data collection for citizen scientists (Moczek et al 2021 ) and enables them to get a common understanding of data quality (Land-Zandstra et al 2021 ). Positive feedback and confirmation of the number of successfully recorded nightingale songs likewise might have helped to increase quality (Peltola and Arpin 2018 ) and motivate citizen scientists to participate long-term (Pandya and Dibner 2018 ).…”