How does the GTN ensure our training materials are FAIR?
Helena RascheThis infrastructure has been developed in accordance with the FAIR (Findable, Accessible, Interoperable, Reusable) principles for training materials Garcia et al. 2020. Following these principles enables trainers and trainees to find, reuse, adapt, and improve the available tutorials.
| 10 Simple Rules | Implementation in GTN framework |
|---|---|
| Plan to share your training materials online | Online training material portfolio, managed via a public GitHub repository |
| Improve findability of your training materials by properly describing them | Rich metadata associated with each tutorial that are visible and accessible via schema.org on each tutorial webpage. |
| Give your training materials a unique identity | URL persistency with redirection in case of renaming of tutorials. Data used for tutorials stored on Zenodo and associated with a Digital Object Identifiers (DOI) |
| Register your training materials online | Tutorials automatically registered on TeSS, the ELIXIR’s Training e-Support System |
| If appropriate, define access rules for your training materials | Online and free to use without registration |
| Use an interoperable format for your training materials | Content of the tutorials and slides written in Markdown. Metadata associated with tutorials stored in YAML, and workflows in JSON. All of this metadata is available from the GTN’s API |
| Make your training materials (re-)usable for trainers | Online. Rich metadata associated with each tutorial: title, contributor details, license, description, learning outcomes, audience, requirements, tags/keywords, duration, date of last revision. Strong technical support for each tutorial: workflow, data on Zenodo and also available as data libraries on UseGalaxy.*, tools installable via the Galaxy Tool Shed, list of possible Galaxy instances with the needed tools. |
| Make your training materials (re-)usable for trainees | Online and easy to follow hands-on tutorials. Rich metadata with “Specific, Measurable, Attainable, Realistic and Time bound” (SMART) learning outcomes following Bloom’s taxonomy. Requirements and follow-up tutorials to build learning path. List of Galaxy instances offering needed tools, data on Zenodo and also available as data libraries on UseGalaxy.*. Support chat embedded in tutorial pages. |
| Make your training materials contribution friendly and citable | Open and collaborative infrastructure with contribution guidelines, a CONTRIBUTING file and a chat. Details to cite tutorials and give credit to contributors available at the end of each tutorial. |
| Keep your training materials up-to-date | Open, collaborative and transparent peer-review and curation process. Short time between updates. |
Still have questions?
Gitter Chat Support
Galaxy Help Forum
Want to embed this snippet (FAQ) in your GTN Tutorial?
{% snippet faqs/gtn/fair_training.md %}
Persistent URL
Resource purlPURL: https://gxy.io/GTN:F00148References
- Garcia, L., B. Batut, M. L. Burke, M. Kuzak, F. Psomopoulos et al., 2020 Ten simple rules for making training materials FAIR (S. Markel, Ed.). PLOS Computational Biology 16: e1007854. 10.1371/journal.pcbi.1007854