Commentary on "Preliminary Species Hypotheses" in Entomological Taxonomy: A Global Data and FAIR Infrastructure Perspective

Abstract

What if early taxonomic findings were treated like preprints, open to iterative improvement or managed with practices from the open-source community, such as Git branching, merging and patch management? Prompted by Buckley's article Charting a Future for Entomological Taxonomy in New Zealand (2024), this commentary explores these possibilities in the context of biodiversity informatics. In response to the need for rapid, scalable biodiversity monitoring, Buckley introduces preliminary species hypotheses (PSH) as a bridge between quick identification tools and the rigorous Linnaean system, leveraging DNA barcoding and AI-assisted image recognition to produce provisional classifications that can later be validated. Expanding on Buckley's framework, this commentary emphasises the critical role of data linking, versioning and integration to support evolving taxonomic data. Borrowing from software and open-source practices, I explore the idea of managing PSH with an infrastructure that treats each taxonomic update as a versioned "commit", which can be tracked, refined and integrated over time. Drawing insights from FAIR (Findable, Accessible, Interoperable, Reusable) principles and Digital Extended Specimens, I identify infrastructure requirements for PSH, including robust data standards, persistent identifiers and interoperability to support global biodiversity repositories. Additionally, Taxonomic Data Objects offer a model for dynamically integrating PSH into adaptable taxonomies that can evolve with new data and tools. By positioning PSH within an open, infrastructure-focused framework, this commentary advocates for scalable, hypothesis-driven biodiversity data that meets modern conservation needs, bridging traditional and emerging practices in taxonomy.

Keywords: FAIR; data integration; interoperability; open source; species; taxonomy.

Figure 1.

A simplified conceptual framework for version-controlled taxonomic data management This diagram illustrates the parallel between hypothesis-driven taxonomic workflows and Git-based version control systems. Drawing inspiration from software development practices, the framework demonstrates how version control concepts could be applied to manage and track the evolution of taxonomic hypotheses. The actual processes involved are much more complex, as described in Pyle's paper "An Introduction to Scientific Names of Organisms and the Taxon Concepts they Represent (Pyle 2022).