FAIR Convergence Matrix: Optimizing the Reuse of Existing FAIR-Related Resources

Kód výsledku v 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>

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

FAIR Convergence Matrix: Optimizing the Reuse of Existing FAIR-Related Resources

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

FAIR Convergence Matrix: Optimizing the Reuse of Existing FAIR-Related Resources

Popis výsledku anglicky

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.

Druh

J_ost - Ostatní články v recenzovaných periodicích

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2019

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Data Intelligence

ISSN

2641-435X

e-ISSN

2641-435X

Svazek periodika

2020

Číslo periodika v rámci svazku

2

Stát vydavatele periodika

CN - Čínská lidová republika

Počet stran výsledku

13

Strana od-do

158-170

Kód UT WoS článku

000691825600017

EID výsledku v databázi Scopus

2-s2.0-85090223977