EGU24-7613, updated on 08 Mar 2024
https://doi.org/10.5194/egusphere-egu24-7613
EGU General Assembly 2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

Into the Deep - Marine Image Analysis Hub for Citizen Scientists

Caroline Johansen
Caroline Johansen
  • Interchange Non-Profit gUG, Germany (caroline@inter-change.eu)

Into the Deep is a Citizen Science Project that brings remote marine ecosystems directly to your laptop and allows adult learners to take part in real time research by annotating images of marine ecosystems. For this pilot, there are 4 data sets from different marine environments, and an intuitive image annotation tool called BiiGLE PARTY. In this session we will present how Citizen Scientists (CS) are being strategically recruited in two ways: through social media and through pre-existing partner networks. All participants are introduced to four ecosystems and each CS must first elect to follow a short course that was developed in close collaboration with the scientists and adult education experts. This dynamic, online course explains the importance of each ecosystem, detailing human impact on a habitat and gives them the information to answer a specific scientific question. The course is Non-Formal Education, achieving specific learning goals, but not formally evaluated. We will present key data aligning educational input and CS projects, showing how learning helps both maintain and actively engage adult learners in climate-positive action. Following the notion that when people are more educated about the topic (in this case marine ecosystems), it fosters a more positive attitude towards the ocean, and promotes greater compliance with measures put in place to protect it. After completing the short course, participants automatically enter the BiiGLE PARTY CS tool and can annotate images from the relevant habitation dataset with gamified prompts and point systems to keep them engaged. Statistical parameters and check points are incorporated into the program to exclude annotation outliers and cross-check for accuracy. The results of these annotations feedback to the scientific owner of the dataset and into ongoing research. We present some of the ways results provide valuable help to scientists, including training machine learning for automatic image detection. The main goal of Into the Deep is to provide an easy-to-use tool for both researchers and adult learners, and to facilitate the dialogue and continued commitment between CS and the researchers they assist. To this end, we will present an E-book and framework outlining how scientists can easily incorporate this tool for their own research purposes and information about how to reach interested CS.

How to cite: Johansen, C.: Into the Deep - Marine Image Analysis Hub for Citizen Scientists, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7613, https://doi.org/10.5194/egusphere-egu24-7613, 2024.