Guidance framework to apply good practices in ecological data analysis: Lessons learned from building Galaxy-Ecology

Numerous conceptual frameworks exist for best practices in research data and analysis (e.g. Open Science and FAIR principles). In practice, there is a need for further progress to improve transparency, reproducibility, and confidence in ecology. Here, we propose a practical and operational framework for researchers and experts in ecology to achieve best practices for building analytical procedures from individual research projects to production-level analytical pipelines. We introduce the concept of atomisation to identify analytical steps which support generalisation by allowing us to go beyond single analyses. The term atomisation is employed to convey the idea of single analytical steps as “atoms” composing an analytical procedure. When generalised, “atoms” can be used in more than a single case analysis. These guidelines were established during the development of the Galaxy-Ecology initiative, a web platform dedicated to data analysis in ecology. Galaxy-Ecology allows us to demonstrate a way to reach higher levels of reproducibility in ecological sciences by increasing the accessibility and reusability of analytical workflows once atomised and generalised. DOI https://doi.org/10.32942/X2G033 Subjects Bioinformatics, Other Ecology and Evolutionary Biology

biodiversity, Reproducible analyses, Galaxy, Good practices, Atomisation, Generalisation, workflows, ecoinformatics, Conda, container, Common Workflow Language, RO-CRATE Dates Published: 2024-04-11 17:35 Last Updated: 2024-10-09 03:47 Older Versions License CC BY Attribution 4.0 International Additional Metadata Data and Code Availability Statement: Not applicable Language: English