Author/s: Artemis Skarlatidou and Muki HaklayPresenter: Artemis Skarlatidou
Citizen science (CS) encompasses a wide range of activities (from dedicating an hour a year to count birds in your garden, to carrying out biological experiments in DIY Biology which take many hours every week), different levels of engagement, different types of projects, and different levels of technological use. These create implications in terms of how CS is applied and whether anticipated impacts are achieved, with insufficient evidence from real cases and their effect to the broader CS agenda. In this study we used the ‘escalator concept’ for first time, which helped us understand and encourage engagement in the European project, Doing It Together Science (DITOs), working with a detailed logic model and theory of change analysis to ensure that our assumptions for transformations in DITOs are identified, taken care of, and therefore impacts are achieved. We aim at providing practical evidence and a model that others can replicate for the successful implementation of their programme impacts.
Author/s: Pavel Bína, Fredrik Brouneus, Niclas Hagen, Martin Bergman, Gustav Bohlin and Dick KasperowskiPresenter: Pavel Bína
This E-poster will present findings from two surveys on attitudes and experiences of citizen science (CS) among researchers at Swedish universities. The first (n=636) was exclusively focused on CS and involved researchers and other personnel at Swedish University of Agricultural Sciences. The second (n=3 699) was on the broader topic, including CS, and was distributed to researchers from all Swedish universities. Our results show that CS is a far from well-known concept among Swedish researchers. And while those who have heard about CS are generally positive towards it, researchers overall are hesitant to invite citizens to the research process.
Author/s: Till Bruckermann, Hannah Greving, Milena Stillfried, Konstantin Börner, Anke Schumann, Ute Harms and Miriam BrandtPresenter: Anke Schumann
Citizen Science (CS) projects enable citizens to engage in different scientific activities. Although citizens are known to be more motivated to collect data rather than analyze data, investigations of citizens’ actual behavior concerning these two activities are sparse. Therefore, we analyzed and clustered log file data of a CS project on urban wildlife (N = 397). Citizens were more active during data collection than data analysis and lurked more (i.e. were more passive) during data analysis than data collection. Moreover, mostly highly engaged data collectors stayed as data analysts. Such differences in engagement patterns should be considered in future research.