A chatbot that helps transform spreadsheets into GBIF-ready datasets wins the 2024 Ebbe Nielsen Challenge. Prizes also went to a tool for automating data extraction from specimen labels, and to a multilingual chatbot designed to simplify the use of the Darwin Core data standard.
The Ebbe Nielsen Challenge is an annual incentive prize that seeks to inspire innovative applications of open-access biodiversity data by scientists, informaticians, data modelers, cartographers and other experts.
1st Prize: ChatIPT: Rukaya Johaadien’s chatbot provides conversation-style support to students and researchers who hold biodiversity data but are first-time or infrequent data publishers. Its prompts guide users as it cleans and standardizes spreadsheets, creates basic metadata, and publishes well-structured datasets on GBIF.org as a Darwin Core Archive.
2nd Prize: Planetary Knowledge Base: Developed by Qianqian (Hiris) Gu, Ben Scott and Vince Smith of the Natural History Museum, London, this early prototype provides an automated transcription service that captures structured semantic data from specimen label images by leveraging large language models (LLMs) and Graph Convolutional Neural Networks (GCNNs). Through its innovative approach, the Planetary Knowledge Base (PKB) may transform processes for digitizing and analysing natural history collections.
3rd Prize: CoreTech Assistant: Chen Yao’s multilingual chatbot prototype leverages Retrieval-Augmented Generation (RAG) technology to bridge users’ linguistic gaps while reducing the steep learning curve for the Darwin Core data standard.