DATA REUSE INITIATIVE
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  • Home
  • Research
    • Papers and Media
    • Bibliography
    • Resources
    • Survey Design
  • Participation
    • People
    • How to Contribute
  • Education
DATA REUSE INITIATIVE
Resources on FAIR Standards
What is FAIR? From the INCF blog

1) Description on FAIR (Findable, Accessible, Interoperable, Reusable) Principles from FORCE11 
 (link).

​* metadata with attributes   (link).

​* digital twins applied to healthcare   (link).

* AI-ready data repositories   (link).



​2) Controlled Vocabularies from ddAlliance   (link)

​* subject heading lists and authority files (headings, cross-references).

* authority files (headings, cross-references).

* data thesaurus (words grouped by similar meanings).


3) Assorted References
* DataCite Schema  documentation (.pdf)  schema (.xsd)


* NIH Workshop on the Role of Generalist Repositories to Enhance Data Discoverability and Reuse  link

* researchobject.org  link

* Google Dataset Search   link


​References:
Brock, J. (2019). "A love letter to your future self": What scientists need to know about FAIR data.  Nature Index, February 11.


Dijkers, M. (2019). Reduce, reuse, recycle: good stewardship of research data. Spinal Cord, 57, 165–166.

Mons, B. (2020). Invest 5% of research funds in ensuring data are reusable. Nature World View, February 25.

Wilkinson, M.D. et.al (2016). The FAIR Guiding Principles for scientific data management and stewardship. Scientific Data, 3, 160018.
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