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.
As of February 2017, over 60 citizen scientists are monitoring camera traps at more than 190 sites across northeast England. They have uploaded over 110,000 images to MammalWeb, of which more than 74,000 have been classified by more than 200 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:
The MammalWeb user experience How our collaboration with educational institutions has produced actively involved citizen scientists in camera trap monitoring, and
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, and possible future directions for the work
This is joint work with Pen-Yuan Hsing; Lorraine Coghill; Vivien Kent; Russel Hill; Mark Whittingham; Philip Stephens
After studying maths and then Computer Science, Steven joined Durham University in 1997 as a lecturer in Computer Science. From 2004-2013 he was a part-time teaching fellow, spending the rest of his time on web consultancy, mainly on research projects across the university. Since 2013 he has been a full-time teaching fellow in the school of Engineering and Computing Sciences. He teaches programming and computer architecture and his research interests lie in automated assessment, plagiarism, and citizen science. He is also involved in outreach into schools.