Further support and information

Below are a list of additional resources that researchers interested in FAIR data and software may find useful. If there is something that you do not see and would like advice on regarding FAIR, please contact the team at rdm@sheffield.ac.uk.

Support from the University

Data Management Plans: Research Data Management page, DMPOnline tool
Ethics: Research Ethics Policy
Storing data securely: IT Services Research Storage pages
Managing your data: Research Data Management page
Data availability statements: Research Data Management page

Useful information elsewhere

OPENAIRE: How to make your data FAIR
FAIR principles
Library Carpentry Top 10 FAIR Data & Software Things
Global Indigenous Data Alliance CARE principles
Turing Way: Guide for reproducible research
Turing Way: FAIR principles
Sharing data in accessible formats
Selecting a license: Software
Hasselbring, W. et al. (2020) ‘From FAIR research data toward FAIR and open research software’, Information technology (Munich, Germany), 62(1), pp. 39–47.
The FAIR cookbook - resource to support FAIRification of data and software (focus is on the life sciences but has wider application)
Fairsharing educational

Subject-specific information and resources

These sections of the resource will continue to be developed over time. If you have suggestions of items you would like to see included, please contact rdm@sheffield.ac.uk .

Arts and Humanities

General

FAIR data principles and their application to speech and oral archives: https://www.tandfonline.com/doi/abs/10.1080/09298215.2018.1473449?journalCode=nnmr20
Applying FAIR principles in digital cultural heritage: https://pro.europeana.eu/post/europeana-and-the-fair-principles-for-research-data
Sustainable and FAIR data sharing in the Humanities from ALLEA: https://allea.org/portfolio-item/sustainable-and-fair-data-sharing-in-the-humanities/
Humanities: Historical Research: https://librarycarpentry.org/Top-10-FAIR/2018/12/01/historical-research/
Research data in the social sciences and humanities: https://dhd-blog.org/?p=12970

Archaeology

Chartered Institute of Archaeologists: https://www.archaeologists.net/work/toolkits/dig-digital/standards
Archaeology Data Service and FAIR: https://archaeologydataservice.ac.uk/about/adsFAIR.xhtml
FAIR research statement (University of Cambridge dept of Archaeology): https://www.arch.cam.ac.uk/research/fair-research-statement

History

Data meets history: A research data management strategy for the historically oriented humanities: https://www.degruyter.com/document/doi/10.1515/9783110679151-009/html?lang=en

Music

Open Science in Musicology: https://emusicology.org/article/view/8246/6257
Library Carpentry - Music: https://librarycarpentry.org/Top-10-FAIR/2019/05/31/music/
Open Data in music and science: https://musicscience.net/2018/05/25/open-data-in-music-and-science/
Special Issue on Open Science in Musicology: https://emusicology.org/issue/view/278
David M. Weigl et al. (2021) ‘FAIR Interconnection and Enrichment of Public-Domain Music Resources on the Web’, Empirical musicology review, 16(1), pp. 16–33. https://doi.org/10.18061/emr.v16i1.7643
Rose-Steel, T. and Turnator, E. (2016) ‘Medieval Music in Linked Open Data: A Case Study on Linking Medieval Motets’, International journal of humanities and arts computing, 10(1), pp. 36–50. https://doi.org/10.3366/ijhac.2016.0158 .

Engineering

General

Making Science and Engineering Data FAIR: https://medium.com/@jldjong/making-science-and-engineering-data-fair-9d2319abe24

Chemical engineering

Data science for Chemical Engineers: https://find.shef.ac.uk/permalink/f/98odl8/TN_cdi_webofscience_primary_000393938600012CitationCount
FAIR data is an enabler for artificial intelligence in Chemical Engineering: https://community.data.4tu.nl/2022/02/09/fair-data-is-an-enabler-for-artificial-intelligence-in-chemical-engineering/

Water science and enginering

Journal of Enviromental Engineering - From slide rule to big data: how data science is changing water science and engineering: https://ascelibrary.org/doi/10.1061/%28ASCE%29EE.1943-7870.0001578

Health

Global Health Training Centre course on data sharing: https://globalhealthtrainingcentre.tghn.org/data-sharing/
Biomedical Data Producers, Stewards, and Funders: https://librarycarpentry.org/Top-10-FAIR//2018/12/01/biomedical-data-producers/
National Institute for Health Research (NIHR) Data Guidelines - includes list of recommended repositories, subject-specific examples of metadata and citations: https://openresearch.nihr.ac.uk/for-authors/data-guidelines
Guidelines for implementing FAIR open data policy in health research: https://www.fair4health.eu/storage/files/Resource/15/D23%20Guidelines%20for%20implementing%20FAIR%20Open%20Data%20policy%20in%20health%20research.pdf
Wellcome: How to Publish: Data Guidelines: https://wellcomeopenresearch.org/for-authors/data-guidelines#fairdata
Use Cases Show the practical benefits of making data FAIR for Life Science industry: https://fairtoolkit.pistoiaalliance.org/category/use-cases/
Applying the FAIR principles to data in a hospital: challenges and opportunities in a pandemic: https://www.medrxiv.org/content/10.1101/2021.08.13.21262023v2.full
Initiatives, Concepts, and Implementation Practices of FAIR (Findable, Accessible, Interoperable, and Reusable) Data Principles in Health Data Stewardship Practice: Protocol for a Scoping Review: https://www.researchprotocols.org/2021/2/e22505/
ZonMw: Fairification: By FAIRifying your data, they can be found, understood and used by humans and by machines - variety of tools and guidance from organisation focused on health innovation and research: https://www.zonmw.nl/en/research-and-results/fair-data-and-data-management/fairification/
Guidelines for FAIR sharing of preclinical safety and off-target pharmacology data: https://pubmed.ncbi.nlm.nih.gov/33637997/
From Raw Data to FAIR Data: The FAIRification Workflow for Health Research: https://pubmed.ncbi.nlm.nih.gov/32620019/
Cancer research UK: Practical guidance for researchers on writing data sharing plans: https://www.cancerresearchuk.org/funding-for-researchers/applying-for-funding/practical-guidance-for-researchers-on-writing-data-sharing-plans

Clinical data

Applying FAIR Principles to Clinical Data: https://www.clinicallabmanager.com/insight/applying-fair-principles-to-clinical-data-247
Data Management for Clinical Research online course: https://www.coursera.org/learn/clinical-data-management

Sciences

General

FAIR Data Infrastructure for Physics, Chemistry, Materials Science, and Astronomy. https://www.fair-di.eu/about/info
‘"A love letter to your future self’’: What scientists need to know about FAIR data: https://www.natureindex.com/news-blog/what-scientists-need-to-know-about-fair-data

Chemistry

Open access network: Chemistry: https://open-access.network/en/information/subject-specific-open-access/chemistry
NFDI4Chem: Chemistry consortium in the NFDI (National Research Data Infrastructure Germany) - a range of information and resources including repositories, DMPs and terminology. 'An initiative to build an open and FAIR infrastructure for research data management in chemistry.': https://www.nfdi4chem.de/
NFDI4Chem Knowledge Base - detailed information on RDM in different areas of chemistry: https://knowledgebase.nfdi4chem.de/knowledge_base/
NFDI4Chem: FAIR data principles: https://knowledgebase.nfdi4chem.de/knowledge_base/docs/topics/fair/

Life sciences

A Guide to the FAIR Principles in Biopharma: https://frontlinegenomics.com/a-guide-to-the-fair-principles-in-biopharma
FAIR 'cookbook' for the life sciences: https://fairplus.github.io/the-fair-cookbook/content/home.html
Life sciences Research Data Management kit: https://rdmkit.elixir-europe.org/index.html
Interoperability standards for the life sciences: https://elixir-europe.org/platforms/interoperability/rirs
Eos - Advancing FAIR data in Earth, Space and Environmental Science: http://dx.doi.org/10.1029/2018EO109301

Mathematics

The International Council for Industrial and Applied Mathematics: https://iciam.org/news/19/10/1/about-fair-principles-research-data
Mathematical Research Data Initiative: https://www.mardi4nfdi.de/about/mission

Psychology

APA explanation of data sharing: https://www.apa.org/pubs/journals/resources/data-sharing-video#:~:text=Shared%20data%20should%20be%20FAIR,Accessible%2C%20Interoperable%2C%20and%20Reusable.
Martone, M.E., Garcia-Castro, A. and VandenBos, G.R. (2018) ‘Data Sharing in Psychology’, The American psychologist, 73(2), pp. 111–125. https://doi.org/10.1037/amp0000242 .
Houtkoop, B.. et al. (2018) ‘Data sharing in psychology: A survey on barriers and preconditions’, Advances in methods and practices in psychological science, 1(1), pp. 70–85. https://doi.org/10.1177/2515245917751886 .

Social Sciences

General

White Paper on implementing the FAIR principles for data in the social, behavioural, and economic sciences https://www.econstor.eu/bitstream/10419/229719/1/1743296207.pdf
The road to FAIR: FAIR data in the social sciences & humanities https://roadtofair.hypotheses.org/327
Project focusing on open and FAIR in the social sciences and humanities: https://sshopencloud.eu/
Research data management toolkit for the arts, humanities and social sciences: https://pro.europeana.eu/post/europeana-and-the-fair-principles-for-research-data
Research data in the social sciences and humanities: https://dhd-blog.org/?p=12970
CESSDA Data Management Expert Guide: https://www.cessda.eu/Training/Training-Resources/Library/Data-Management-Expert-Guide

Geography

How FAIR are the UK's geospatial assets? https://www.gov.uk/government/publications/how-fair-are-the-uks-geospatial-assets/how-fair-are-our-national-geospatial-data-assets-assessment-of-the-uks-national-geospatial-data-html
Ordnance Survey: introducing our data principles https://www.ordnancesurvey.co.uk/newsroom/blog/introducing-our-data-principles

Journalism

Preserving data journalism: a systematic review: https://www.tandfonline.com/doi/full/10.1080/17512786.2021.1903972