(Produced by Jasmin Boehmer, our outgoing expert on FAIR data)

Website: TIB Hannover Blog: The FAIR Data Principles for Resarch Data: https://blogs.tib.eu/wp/tib/2017/09/12/the-fair-data-principles-for-research-data/

Github: European Commission FAIR Data Expert Group Github: https://github.com/FAIR-Data-EG

Zenodo: European Commission FAIR Data Expert Group interim report: https://zenodo.org/record/1285272#.W1rbt_mFOLv

Zenodo: European Commission FAIR Data Expert Group interim action plan: https://zenodo.org/record/1285290#.W1rebfmFOLt

Website: ANDS FAIR data training: http://www.ands.org.au/working-with-data/fairdata/training

Initiative: FAIRsharing.org: https://fairsharing.org/

Website: Ask Open Science Forum FAIR data vs Open Data: https://ask-open-science.org/1116/what-the-difference-between-fair-data-and-open-data-there-any

Report: SURF report FAIR data advanced use cases: https://www.surf.nl/en/knowledge-base/2018/fair-data-advanced-use-cases.html

Paper: NetCDF data in 4TU.RD vs FAIR principles: https://zenodo.org/record/1316938#.W1reLvmFOLs

Paper: A design framework and exemplar metrics for FAIRness: https://www.nature.com/articles/sdata2018118

Paper: FAIR science for social machines: Let’s share metadata Knowlets in the Internet of FAIR data and services: http://www.data-intelligence-journal.org/static/publish/B5/D1/28/A85A05492CA4E681827A4F8BF7/0511-Barend_Mons.pdf

Paper: FAIRsharing: working with and for the community to describe and link data standards, repositories and policies: https://www.biorxiv.org/content/biorxiv/early/2018/01/17/245183.full.pdf

Paper: Advancing Discovery Science with FAIR Data Stewardship: https://www.tandfonline.com/doi/abs/10.1080/0361526X.2018.1443651

Paper: FAIR principles and the IEDB: https://academic.oup.com/database/article/doi/10.1093/database/bax105/4877121?searchresult=1

Paper: Navigating the unfolding open data landscape in ecology and evolution: https://www.nature.com/articles/s41559-017-0458-2

Book: Data Stewardship for Open Science Implementing FAIR Principles: https://www.taylorfrancis.com/books/9781498753180

Paper: How to make research information FAIR: DSpace-CRIS and best practices in open research information: https://dspacecris.eurocris.org/handle/11366/657

Paper: Enhancing Reuse of Data and Biological Material in Medical Research: From FAIR to FAIR-Health: https://www.liebertpub.com/doi/full/10.1089/bio.2017.0110

Paper: The FAIR guiding principles for data stewardship: fair enough?: https://www.nature.com/articles/s41431-018-0160-0

Paper: NOMAD: The FAIR Concept for Big-Data-Driven Materials Science: https://arxiv.org/abs/1805.05039

Paper: A Conceptual Enterprise Framework for Managing Scientific Data Stewardship: https://datascience.codata.org/articles/10.5334/dsj-2018-015/

Website: DTLS FAIR data: https://www.dtls.nl/categorie/fair-data/

Website: DTLS FAIR data tools: https://www.dtls.nl/fair-data/find-fair-data-tools/

Initiative: GO FAIR: https://www.go-fair.org/

Initiative: FAIRdom: https://fair-dom.org/

Paper: Interoperability and FAIRness through a novel combination of Web technologies: https://peerj.com/preprints/2522/

Github: DTL-FAIRData/FAIRDataPoint: https://github.com/DTL-FAIRData/FAIRDataPoint/wiki