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Reusable FAIR Implementation Profiles as Accelerators of FAIR Convergence

Identifikátory výsledku

  • Kód výsledku v IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21240%2F20%3A00350114" target="_blank" >RIV/68407700:21240/20:00350114 - isvavai.cz</a>

  • Výsledek na webu

    <a href="https://doi.org/10.1007/978-3-030-65847-2_13" target="_blank" >https://doi.org/10.1007/978-3-030-65847-2_13</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/978-3-030-65847-2_13" target="_blank" >10.1007/978-3-030-65847-2_13</a>

Alternativní jazyky

  • Jazyk výsledku

    angličtina

  • Název v původním jazyce

    Reusable FAIR Implementation Profiles as Accelerators of FAIR Convergence

  • Popis výsledku v původním jazyce

    Powerful incentives are driving the adoption of FAIR practices among a broad cross-section of stakeholders. This adoption process must factor in numerous considerations regarding the use of both domain-specific and infrastructural resources. These considerations must be made for each of the FAIR Guiding Principles and include supra-domain objectives such as the maximum reuse of existing resources (i.e., minimised reinvention of the wheel) or maximum interoperation with existing FAIR data and services. Despite the complexity of this task, it is likely that the majority of the decisions will be repeated across communities and that communities can expedite their own FAIR adoption process by judiciously reusing the implementation choices already made by others. To leverage these redundancies and accelerate convergence onto widespread reuse of FAIR implementations, we have developed the concept of FAIR Implementation Profile (FIP) that captures the comprehensive set of implementation choicesmade at the discretion of individual communities of practice. The collection of community-specific FIPs compose an online resource called the FIP Convergence Matrix which can be used to track the evolving landscape of FAIR implementations and inform optimisation around reuse and interoperation. Ready-made and well-tested FIPs created by trusted communities will find widespread reuse among other communities and could vastly accelerate decision making on well-informed implementations of the FAIR Principles within and particularly between domains.

  • Název v anglickém jazyce

    Reusable FAIR Implementation Profiles as Accelerators of FAIR Convergence

  • Popis výsledku anglicky

    Powerful incentives are driving the adoption of FAIR practices among a broad cross-section of stakeholders. This adoption process must factor in numerous considerations regarding the use of both domain-specific and infrastructural resources. These considerations must be made for each of the FAIR Guiding Principles and include supra-domain objectives such as the maximum reuse of existing resources (i.e., minimised reinvention of the wheel) or maximum interoperation with existing FAIR data and services. Despite the complexity of this task, it is likely that the majority of the decisions will be repeated across communities and that communities can expedite their own FAIR adoption process by judiciously reusing the implementation choices already made by others. To leverage these redundancies and accelerate convergence onto widespread reuse of FAIR implementations, we have developed the concept of FAIR Implementation Profile (FIP) that captures the comprehensive set of implementation choicesmade at the discretion of individual communities of practice. The collection of community-specific FIPs compose an online resource called the FIP Convergence Matrix which can be used to track the evolving landscape of FAIR implementations and inform optimisation around reuse and interoperation. Ready-made and well-tested FIPs created by trusted communities will find widespread reuse among other communities and could vastly accelerate decision making on well-informed implementations of the FAIR Principles within and particularly between domains.

Klasifikace

  • Druh

    D - Stať ve sborníku

  • CEP obor

  • OECD FORD obor

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

Návaznosti výsledku

  • Projekt

  • Návaznosti

Ostatní

  • Rok uplatnění

    2020

  • Kód důvěrnosti údajů

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

Údaje specifické pro druh výsledku

  • Název statě ve sborníku

    ADVANCES IN CONCEPTUAL MODELING, ER 2020

  • ISBN

    978-3-030-65846-5

  • ISSN

  • e-ISSN

  • Počet stran výsledku

    10

  • Strana od-do

    138-147

  • Název nakladatele

    Springer

  • Místo vydání

    Wien

  • Místo konání akce

    Vídeň

  • Datum konání akce

    3. 11. 2020

  • Typ akce podle státní příslušnosti

    WRD - Celosvětová akce

  • Kód UT WoS článku

    000604160100013