Camera trap ecology can be viewed as the combination of three steps: data collection, data processing (photo classification), and data analyses. Careful application of these steps can yield valuable insights into ecological parameters. There have been highly successful citizen science projects which crowdsourced at least one of the first two steps, saving substantial time and resources for researchers. However, we believe there is potential to take citizen science camera trapping from “citizens as sensors” to having active participants in all phases of research, which could benefit both researchers and citizen scientists. To that end, we implemented our pilot project – MammalWeb – to integrate all three phases of camera trapping into a complete citizen science web platform. Through a partnership between Durham University and the Durham Wildlife Trust, we recruited citizen scientists from the public to deploy and monitor camera traps across the north east of England. They were trained in camera trapping methodology and asked to employ the same sampling protocol. To integrate camera trap ecology into education, computer science students at Durham University help develop the backend technology for MammalWeb, and secondary school students are leading multidisciplinary projects with teachers to create outreach material for ecological curricula and the public.
Results/Conclusions
As of February 2016, over 50 citizen scientists are monitoring camera traps at more than 130 sites across northeast England. They have uploaded over 43,000 images to MammalWeb, of which more than 28,000 have been classified by more than 100 registered users. An algorithm adapted from past work was developed by computer science students at Durham University to calculate consensus identifications of animals from the crowdsourced data, on which a user-facing dashboard is being created for participants to explore and interrogate the database. Our collaboration with secondary schools has engaged students in becoming seed ecological ambassadors, and created multimedia projects to share ecological knowledge with their communities. In this talk, I will describe (1) the MammalWeb user experience, (2) how our collaboration with educational institutions has produced actively involved citizen scientists in camera trap monitoring, and (3) how participants help develop MammalWeb into a modular and generalisable citizen science web platform for big data ecology. This platform can then be deployed by other organisations to crowdsource their research. Lastly, I will report key challenges faced by this approach, plus the potential for future work on integrating state of the art technology into citizen science ecology.