Artificial Intelligence Meets Biodiversity Science: Mining Museum Labels

Artificial intelligence (AI) methods hold great potential for the digitization and data extraction of natural history collections, as well as for generating collection-based, FAIR research data. Realizing this potential requires robust technical workflows, interdisciplinary expertise, and appropriate funding structures.

As part of the pilot project KIEBIDS – a collaboration between the Museum für Naturkunde Berlin and the ECO AI LAB („KI-Ideenwerkstatt für Umweltschutz“), an initiative of the German Federal Ministry for the Environment, Climate Action, Nature Conservation and Nuclear Safety (BMUKN) – an open-source framework was developed to extract biodiversity-relevant information from collection labels. The goal is to facilitate the use of historical data resources in biodiversity research and environmental protection.
More information about the project is available at: https://www.ki-ideenwerkstatt.de/unterstuetzung-materialien/pilotprojekte/mit-ki-verborgene-schaetze-entdecken/

The webinar will present the project and its key outcomes. Short talks will provide context on data extraction from natural history collections and collection-based biodiversity research. Participants are invited to discuss requirements, application areas, and future perspectives for AI-driven extraction of environmentally relevant information from historical documents.

Following the online session, participants will have the opportunity to join an onsite guided tour of the butterfly collection at the Museum für Naturkunde Berlin (15:00 – 16:00). The tour offers hands-on insights into collection work, the challenges of digitizing historical labels, and the chance to speak directly with staff from the Museum and the AI Innovation Lab.

Language: English

PLEASE REGISTER HERE

Picture: Museum für Naturkunde Berlin, Eran Wolff