Insects and AI in Aarhus
I am inspired by the rapid advances in technology and AI, which can profoundly improve our understanding of 'dark taxa' like insects and contribute to big data in entomology, insect ecology and overall biodiversity science. I think that these new technologies will deliver data that will be vital in decision-making to find urgent solutions to the biodiversity crisis. Applying for the STSM at InsectAI was a perfect opportunity for me to engage with and learn from leading experts in this exciting field.
Collecting insect biodiversity data is traditionally time-consuming due to the challenges of fieldwork and sample processing. As novel monitoring technologies emerge, they promise to generate unprecedented amounts of insect data which will be important for understanding biodiversity, species distributions, ecological patterns, and responses to environmental change over time. However, without proper metadata standards established from the beginning, this wealth of information could be inaccessible or difficult to use effectively. For my STSM, I wanted to learn more about developing FAIR metadata standards (Findable, Accessible, Interoperable, and Reusable) for automated insect camera traps. One of our aims was to see how datasets from camera traps could be integrated with global databases like the Global Biodiversity Information Facility (GBIF), increasing their value for research, conservation, and policy-making. By proactively developing these standards, we can ensure new monitoring technologies maximise their data delivery to open infrastructures at scale.
We explored existing biodiversity metadata standards, including controlled vocabularies from Darwin Core, Ecological Metadata Language, and CamTrapDP, and discussed challenges for insect camera traps, like taxonomic resolution and the definition of “event” and “deployment”. While focusing on the AMI moth trap as an example, we also brainstormed ideas of how different camera trap systems could adopt these standards to enable data sharing and reduce data overload. Some ideas included publishing only the first detection of each species, sub-sampling species occurrences across multiple frames, and offering the full dataset upon request to enable scrutiny.
This project allowed me to combine my knowledge of entomology curation and insect ecology with my interest of technology and AI. A highlight for me during the STSM was visiting the GBIF Secretariat in at the University of Copenhagen, where we met with Tim Roberts and Cecilie Svenningsen to discuss how metadata standards would work with GBIF’s infrastructure.
Learning from others is one of the greatest joys in science, and joining the InsectAI COST Action is a fantastic opportunity to connect with brilliant colleagues and collaborate across disciplines. If you’re considering applying for a STSM, my advice is to start by identifying the questions or challenges that ignite your curiosity. The initiative offers opportunities from data analysis and societal impacts to species identification, don’t be afraid to get creative and embrace the chance to explore new ideas. Thank you to InsectAI for this great opportunity, and to Toke Høye for warmly welcoming me into his lab, introducing me to the team, and hosting me for the week at Aarhus University.
For more info and to connect with the network: https://insectai.eu/
