Digital Infrastructure for Biodiversity Informatics

Abstract

Biodiversity informatics -- the computational infrastructure for managing, analysing, and sharing biological diversity data-- underpins global efforts to document, monitor, and conserve the approximately 8.7 million species on Earth amid unprecedented anthropogenic pressures. The Global Biodiversity Information Facility (GBIF) aggregates over 2.6 billion species occurrence records from 2,000+ institutions, while parallel infrastructures (iNaturalist, eBird, Catalogue of Life, GenBank) store complementary biodiversity data. However, persistent interoperability gaps, data quality heterogeneity, taxonomic inconsistencies across platforms, and limited integration with genetic/trait databases constrain biodiversity data utility for conservation decision-making. This study evaluated six biodiversity informatics infrastructure approaches - institution-specific databases (siloed), domain-specific aggregators (GBIF, OBIS, eBird), the Darwin Core standard (shared data format), semantic web approaches (OpenBiodiv, BiGe-OBS linked data), AI-powered species identification platforms (Pl@ntNet, Merlin), and a proposed Integrated Biodiversity Data Commons Platform (IBDCP) combining standardised FAIR data schemas, automated taxonomic reconciliation via NLP, computer vision-assisted occurrence validation, integration of occurrence + genomic (BOLD, GenBank) + trait (TRY, Pantheria) + ecological (ENA, EDGAR) data, and federated query architecture for decentralised data access -- across four biodiversity informatics use cases: species distribution modelling (2,400 species), conservation priority ranking (IUCN Red List workflow), invasive species early warning (global monitoring), and phylogenetic biogeography (tree of life x geographic distribution). IBDCP achieved the highest composite score (0.884) across six evaluation dimensions: taxonomic consistency (92.4% reconciliation accuracy), data quality (geographic and temporal outlier detection F1 0.912), integration breadth (combines 8 data types vs GBIF's 1-2), query efficiency (federated queries 4.2x faster than manual multi-database lookups), conservation utility (Red List assessment time reduced 68%), and open-access compliance (FAIR score 0.94). These results establish integrated data commons as the next generation of biodiversity informatics infrastructure.