“How do you name a species?” seems like a simple enough question – that animal is an African bush elephant, Loxodonta africana, done and done. But what do you do when a species has two names, or three names, or, as is the case with the common palearctic butterfly, Plebejus argus, an astonishing one hundred and sixty names? If we need to aggregate data for that species, how do we ensure that we’re getting the right species? 

This is the ongoing struggle of taxonomy: to develop methods of integrating taxonomic data, i.e., dynamically matching species scientific names to accepted names in a taxonomic hierarchy, by ensuring interoperability between different data sources. In a new paper lead by former BGC postdocs Emily Sandall and Aurore Maureaud, the researchers investigated the current status of taxonomic interoperability and proposed six essential elements of a globally integrated structure of taxonomy (GIST) to support improved taxonomic integration across data user and provider groups and create a stronger role for taxonomists in biodiversity science. 

As Sandall, Maureaud, and authors explain in the paper, several communities create and use taxonomic data, from taxonomists to biodiversity researchers to conservationists, and these communities have different values, project goals, and obstacles in their use of taxonomic data. They all rely on taxonomic backbones such as the Catalogue of Life initiative, the Global Biodiversity Information Facility (GBIF), the Global Register of Introduced and Invasive Species (GRIIS), and the BGC Center’s Map of Life (MOL) to harmonize species names in their data. But, as Sandall, Maureaud, and colleagues showed in the paper, there is a surprising lack of interoperability between these backbones, with taxonomic groups like butterflies and flowering plants experiencing a particularly high rate of mismatched names. To improve taxonomic data integration, they suggest six key elements of taxonomic data structure: a ‘Global authoritative list’, a ‘Synonyms list’, ‘Authorship information’, ‘Name source and timestamp’, ‘Name instance’, and finally ‘Taxon concept in space and time’. These key elements seek to assist not only in matching names and taxonomic concepts but tracking their dynamic nature over time as taxonomies are continually updated and refined. 

Sandall, Maureaud, and colleagues hope that their work and the proposed GIST will support data providers and users in assessing the interoperability and integration status of their datasets, enhance communication across taxonomic communities by providing a common vocabulary, and advance the implementation of FAIR principles (findable, accessible, interoperable, reusable) in taxonomic data. According to the authors, it is crucial that strategies revolve around integrating existing data rather than generating novel data or infrastructures, and the proposed GIST seeks to help “prioritize consistent engagement and shared responsibility between all actors on the integration process”.

Read the new paper here!

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