Standing on the Shoulders of Giants: Advancing Biodiversity Research with FAIR Taxonomic Identifiers

The advancement of scientific knowledge has traditionally relied on the foundation provided by earlier work, epitomized by the phrase "standing on the shoulders of giants." In the context of our modern digital landscape, this principle translates into the enrichment and utilization of an evidence knowledge graph through the application of persistent identifiers. These identifiers are crucial for citing existing data and generating new, open digital objects that are Findable, Accessible, Interoperable, and Reusable (FAIR). A prime example of such identifiers is taxonomic names, which originated with Linnaeus's Latin Binomen in 1753. These names have long served to organize biodiversity data, but today they are transformed into persistent, machine-actionable identifiers that denote specific taxonomic concepts and their treatments. However, many of these identifiers remain confined within traditional publications. This presentation outlines how these can be emancipated and enhanced semantically to align with FAIR principles. This involves linking each identification of an occurrence, gene sequence, or observation with a corresponding taxonomic concept identifier. Significant advancements in this field have been facilitated by infrastructural developments under the EU-funded BiCIKL project and the Arcadia Fund. These include enhancements to the Catalogue of Life and GBIF ChecklistBank infrastructure for accessing taxonomic concepts, TreatmentBank for extracting data from publications, the Biodiversity Literature Repository at Zenodo for securing long-term access to FAIR treatments and figures, and the BiodiversityPMC which utilizes AI tools to further annotate and analyse a defined corpus of scientific literature. This lecture will introduce the newly developed tools that enable the creation and annotation of publication corpora in Zenodo, alongside Data Future’s tools for annotating individual articles. Attendees will gain insights into accessing these data, identifying taxonomic concepts, and contributing to the corpus by enhancing taxonomic concepts and treatments that have not yet been made FAIR.