FAIR Data, Workflows, and Research

These lessons will teach you how to make your research objects more FAIR with practical, hands-on advice.

Material

You can view the tutorial materials in different languages by clicking the dropdown icon next to the slides () and tutorial () buttons below.

FAIR Data Management

The FAIR (Findable, Accessible, Interoperable, Reusable) data stewardship created the foundation for sharing and publishing digital assets. These lessons will apply to machine accessibility and emphasize that all digital assets should share data in a way that will enable maximum use and reuse.

Lesson Slides Hands-on Recordings Input dataset Workflows
FAIR in a nutshell
fair open data stewardship
Introduction to Data Management Plan (DMP) for Peatland Research and PeatDataHub
fair open data management plan
Making clinical datasets FAIR
fair open data stewardship
Sequence data submission to ENA
FAIR ENA
FAIR data management solutions
fair dmp data stewardship
FAIR Galaxy Training Material
fair gtn training
FAIR Bioimage Metadata
fair data management bioimaging
REMBI - Recommended Metadata for Biological Images – metadata guidelines for bioimaging data
fair data management bioimaging
FAIRification of an RNAseq dataset
fair dmp data stewardship

Make workflows FAIR with RO-Crate

This section brought to you by the BY-COVID project, and will teach you how to make your research objects more FAIR with practical, hands-on advice.

Lesson Slides Hands-on Recordings Input dataset Workflows
RO-Crate - Introduction
Workflow Run RO-Crate Introduction
ro-crate
Exporting Workflow Run RO-Crates from Galaxy
ro-crate workflows
RO-Crate in Python
ro-crate jupyter-notebook
Best practices for workflows in GitHub repositories
ro-crate jupyter-notebook
Submitting workflows to LifeMonitor
ro-crate

FAIR Pointers

This series of lessons will tackle FAIR from the perspective of the 15 FAIR Principles published in 2016. You will learn about: FAIR and its origins The FAIR Principles and its basic characteristics.

Lesson Slides Hands-on Recordings Input dataset Workflows
FAIR and its Origins
fair dmp data stewardship
Metadata
fair dmp data stewardship
Data Registration
fair dmp data stewardship
Access
fair dmp data stewardship
Persistent Identifiers
fair dmp data stewardship

DataPLANT ARCs

This set of tutorials will introduce you to DataPLANT ARCs, and all the relevant tools to create your own ARCs

Lesson Slides Hands-on Recordings Input dataset Workflows
DataPLANT ARCs
plants fair data stewardship

Other

Assorted Tutorials

Lesson Slides Hands-on Recordings Input dataset Workflows
An earth-system RO-Crate
earth-system ro-crate ocean marine omics
Data management in Medicinal Chemistry
fair data-management medicinal-chemistry computational-chemistry

Frequently Asked Questions

Common questions regarding this topic have been collected on a dedicated FAQ page . Common questions related to specific tutorials can be accessed from the tutorials themselves.

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Editorial Board

This material is reviewed by our Editorial Board:

orcid logoSimone Leo avatar Simone Leoorcid logoLuca Pireddu avatar Luca Piredduorcid logoStian Soiland-Reyes avatar Stian Soiland-Reyesorcid logoPaul De Geest avatar Paul De Geestorcid logoKatarzyna Kamieniecka avatar Katarzyna Kamienieckaorcid logoKrzysztof Poterlowicz avatar Krzysztof Poterlowicz

Contributors

This material was contributed to by:

orcid logoPaul De Geest avatar Paul De Geestorcid logoNick Juty avatar Nick Jutyorcid logoBruno P. Kinoshita avatar Bruno P. Kinoshitaorcid logoWendi Bacon avatar Wendi Baconorcid logoXenia Perez Sitja avatar Xenia Perez Sitjaorcid logoSabrina Zander avatar Sabrina Zanderorcid logoDominik Brilhaus avatar Dominik Brilhausorcid logoAndrew Mason avatar Andrew Masonorcid logoSaskia Hiltemann avatar Saskia Hiltemannorcid logoStian Soiland-Reyes avatar Stian Soiland-Reyesorcid logoCristina Martins Rodrigues avatar Cristina Martins Rodriguesorcid logoPeter Sefton avatar Peter Seftonorcid logoLuca Pireddu avatar Luca Piredduorcid logoGabriela Lopez-Gonzalez avatar Gabriela Lopez-Gonzalezorcid logoSimone Leo avatar Simone LeoMarie Josse avatar Marie Josseorcid logoYvan Le Bras avatar Yvan Le BrasSonal Henson avatar Sonal Hensonorcid logoEmily Angiolini avatar Emily AngioliniStella Eggels avatar Stella Eggelsorcid logoEli Chadwick avatar Eli Chadwickorcid logoBranka Franicevic avatar Branka Franicevicorcid logoKhaled Jum'ah avatar Khaled Jum'ahLaura Cooper avatar Laura Cooperorcid logoSaskia Lawson-Tovey avatar Saskia Lawson-ToveyGareth Price avatar Gareth Priceorcid logoSara Morsy avatar Sara Morsyorcid logoJulia Jakiela avatar Julia Jakielaorcid logoMarco Enrico Piras avatar Marco Enrico Pirasorcid logoNicola Soranzo avatar Nicola Soranzoorcid logoKatarzyna Kamieniecka avatar Katarzyna Kamienieckaorcid logoHelena Rasche avatar Helena Rascheorcid logoPhilippe Rocca-Serra avatar Philippe Rocca-SerraSandra Ng avatar Sandra Ngorcid logoMunazah Andrabi avatar Munazah Andrabiorcid logoKevin Frey avatar Kevin FreyTim Beck avatar Tim Beckorcid logoBjörn Grüning avatar Björn GrüningKellie Snow avatar Kellie Snoworcid logoRobert Andrews avatar Robert AndrewsKorneel Hens avatar Korneel Hensorcid logoMartin Kuhl avatar Martin Kuhlorcid logoKrzysztof Poterlowicz avatar Krzysztof PoterlowiczLaura Cooper avatar Laura Cooper

Funding

These individuals or organisations provided funding support for the development of this resource

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ELIXIR Europe
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EuroScienceGateway
EuroScienceGateway was funded by the European Union programme Horizon Europe (HORIZON-INFRA-2021-EOSC-01-04) under grant agreement number 101057388 and by UK Research and Innovation (UKRI) under the UK government’s Horizon Europe funding guarantee grant number 10038963.
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DFG
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BeYond-COVID
BY-COVID is an EC funded project that tackles the data challenges that can hinder effective pandemic response. This project has received funding from the European Union’s Horizon Europe research and innovation programme under grant agreement № 101046203 (BY-COVID)
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DataPLANT
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DASH UK
This Fellowship was funded through the ELIXIR-UK DaSH project as part of the UKRI Innovation Scholars: Data Science Training in Health and Bioscience call (DaSH). (MR/V038966/1). The project aims to embed Research Data Management (RDM) know-how into UK universities and institutes by producing and delivering training in FAIR data stewardship using ELIXIR-UK knowledge and resources.
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Fair-Ease
FAIR-EASE is a RIA project funded under HORIZON-INFRA-2021-EOSC-01-04, and it involves a consortium of 25 partners from all over Europe.