# An approach to making life sciences FAIR—FAIR-DS as a tool for Aspergillus fumigatus

## TL;DR

This paper introduces FAIR-DS, a tool to help mycologists, especially those working with Aspergillus fumigatus, create FAIR-compliant data for better sharing and reuse.

## Contribution

The paper proposes FAIR-DS as a practical solution for FAIRifying complex life science datasets in mycology.

## Key findings

- FAIR-DS simplifies data uploads while preserving critical metadata for researchers.
- Two datasets were successfully converted into FAIR-compliant formats and published as open data.
- The approach supports collaboration and accelerates scientific progress in mycology.

## Abstract

Adhering to Findable, Accessible, Interoperable, and Reusable (FAIR) principles ensures that data is shared in ways that maximize reusability. However, not all researchers in biological fields, particularly those that rely on manual data entry, have embraced these principles, particularly when it comes to adhering to relevant ontologies. This hampers data sharing due to missing metadata, limiting reuse. This study addresses the production of FAIR data for mycology, a field characterized by high manual data entry demands. For this field, we propose specific data standards to enhance reusability in the Aspergillus fumigatus field and beyond, emphasizing their importance for fostering collaboration and accelerating scientific progress. We adopted the FAIR-Data Station (FAIR-DS) solution to this new domain and demonstrated how to improve the FAIRification of new types of complex life science datasets. For individual researchers, FAIR-DS simplifies data uploads to repositories while ensuring critical metadata is preserved. Following our approach, we have converted two types of datasets—spore counts and a compost monitoring programme on Dutch farms—into FAIR ontology-compliant formats and published them as open data.