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Deep Lake Explorer: Bringing citizen scientists to the underwater world of the Great Lakes
Citation:
Wick, M., M. Nord, M. Pawlowski, R. Debbout, J. Launspach, Dave Bolgrien, AND T. Angradi. Deep Lake Explorer: Bringing citizen scientists to the underwater world of the Great Lakes. Lake Ontario Evening on Underwater Robots & Other Monitoring Technologies, Toronto, ON, CANADA, June 19, 2018.
Impact/Purpose:
We will present information on the development of Deep Lake Explorer, a citizen science application to facilitate analysis of underwater video collected as part of the National Coastal Condition Assessment. This project is one of the only projects to incorporate video footage into this type of analysis, and the first time EPA has used an online citizen science project to help interpret imagery or video. Our presentation will demonstrate the process and benefits of using citizen science to interpret underwater video, describe how the application can educate and connect citizen scientists with their local resource and illustrate how the EPA uses innovative technology to address complicated resource management challenges. The public talk will reach stakeholders and the public interested in a larger discussion on Underwater Robots and Other Monitoring Technologies.
Description:
Deep Lake Explorer is a web application hosted on the Zooniverse platform that allows the public to interpret underwater video collected in the Great Lakes. Crowdsourcing image interpretation using the Zooniverse platform has proven successful for many projects, but few projects to date have included videos. Results from the application will inform habitat and fisheries management programs. Users characterize habitat and identify presence/absence of round gobies and dreissenids in the Great Lakes nearshore. Deep Lake Explorer facilitates the consensus of multiple users on the content of underwater videos. Poor quality videos are identified based on lack of consensus of interpretations. A beta-testing phase allows users to provide input on design, support materials, and analysis workflows, as well as identify the number of interpretations needed to reach quality control targets. The application addresses technical challenges of underwater video analysis, but it also facilitates educational experiences for the public, increased personal connection with the resource, and increased stewardship of the resource. The project is part of a pilot project that aims to prove the method of crowdsourcing video analysis, which may then be applied to future video datasets in and outside of the Great Lakes.