FAIR Convergence Matrix: Optimizing the Reuse of Existing FAIR-Related Resources
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21240%2F19%3A00338484" target="_blank" >RIV/68407700:21240/19:00338484 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1162/dint_a_00038" target="_blank" >https://doi.org/10.1162/dint_a_00038</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1162/dint_a_00038" target="_blank" >10.1162/dint_a_00038</a>
Alternative languages
Result language
angličtina
Original language name
FAIR Convergence Matrix: Optimizing the Reuse of Existing FAIR-Related Resources
Original language description
The FAIR Principles articulate the behaviors expected from digital artifacts that are Findable, Accessible, Interoperable and Reusable by machines and by people. Although by now widely accepted, the FAIR Principles by design do not explicitly consider actual implementation choices enabling FAIR behaviors. As different communities have their own, often well-established implementation preferences and priorities for data reuse, coordinating a broadly accepted, widely used FAIR implementation approach remains a global challenge. In an effort to accelerate broad community convergence on FAIR implementation options, the GO FAIR community has launched the development of the FAIR Convergence Matrix. The Matrix is a platform that compiles for any community of practice, an inventory of their self-declared FAIR implementation choices and challenges. The Convergence Matrix is itself a FAIR resource, openly available, and encourages voluntary participation by any self-identified community of practice (not only the GO FAIR Implementation Networks). Based on patterns of use and reuse of existing resources, the Convergence Matrix supports the transparent derivation of strategies that optimally coordinate convergence on standards and technologies in the emerging Internet of FAIR Data and Services.
Czech name
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Czech description
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Classification
Type
J<sub>ost</sub> - Miscellaneous article in a specialist periodical
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Data Intelligence
ISSN
2641-435X
e-ISSN
2641-435X
Volume of the periodical
2020
Issue of the periodical within the volume
2
Country of publishing house
CN - CHINA
Number of pages
13
Pages from-to
158-170
UT code for WoS article
000691825600017
EID of the result in the Scopus database
2-s2.0-85090223977