A checklist recipe: making species data open and FAIR

Area of Science:

• Biodiversity Informatics
• Data Science
• Conservation Biology

Background:

• Traditional species checklists often lack standardization, hindering data accessibility and reuse.
• Non-FAIR (findable, accessible, interoperable, reusable) data impede rapid information flow for biodiversity conservation policy.
• The biodiversity crisis necessitates efficient and open data sharing for effective decision-making.

Purpose of the Study:

• To develop and showcase a reproducible, semi-automated workflow for transforming traditional species checklists into FAIR and open data registries.
• To improve the accessibility and usability of species checklist data for research and policy.
• To facilitate faster and more efficient information flow to address the biodiversity crisis.

Main Methods:

• A reproducible, semi-automated workflow was developed using R for data transformation.
• Data transformation followed Darwin Core standards for interoperability.
• The workflow incorporates source data management, version control, data documentation, and publication to the Global Biodiversity Information Facility (GBIF).
• The workflow was applied to the Manual of Alien Plants for the TrIAS project.

Main Results:

• A FAIR and open species registry was successfully created from traditional checklist data.
• The workflow demonstrated reproducibility and semi-automation in data transformation.
• The Manual of Alien Plants was published as an open data resource via GBIF.

Conclusions:

• The proposed workflow provides a robust method for creating FAIR and open species registries from diverse checklist data.
• This approach can be applied across various thematic, taxonomic, and geographical scopes.
• Opening up species data is crucial for advancing biodiversity research and strengthening environmental decision-making.