The BioWhere Project: Unlocking the Potential of Biological Collections Data

Abstract

Vast numbers of biological specimens (e.g. flora, fauna, soils) are stored in collections globally. Many of these have only a natural-language location description, such as ‘ 200ft above and south of main highway, 1.1 miles west of Porters Pass ’, and numerical coordinates are unknown. The BioWhere project is pioneering methods to automatically determine the geographic coordinates (georeferences) of complex location descriptions. Particular challenges are posed by the variable accuracy of recent and historical data that might be used to train models to predict geographic coordinates from the natural-language descriptions; by the presence of historical place names in the descriptions that are not stored in existing gazetteers; and by the vague and context-sensitive nature (e.g. above , on , south of ) of the descriptions. We are addressing these challenges by extending the latest transformer-based deep learning models to parse locality descriptions, and to build models for specific spatial terms that incorporate geographic context and data quality to more accurately predict georeferences. We also describe a gazetteer that contains enriched cultural content to support georeferencing of historical records, and to serve as a store of New Zealand Māori cultural knowledge for future generations.