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Short Description 

To be able to reach your FAIRification goals, having a team with the right skillset is important. The composition of the team depends on the exact goals and different skills may be necessary in different phases of the of the process. See, for example:

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Expert

Description

Metroline Steps

Clinicians specialised in the domain

Has understanding/knowledge about:

  • Access policies applicable to the resource

  • Semantic data modelling

  • The data to be FAIRified and how they are managed 

  • The domain and on what is a data resource is used forAccess policies applicable to the resource

  • Semantic data modelling

Data manager

Has understanding/knowledge about:

  • The data to be FAIRified and how they are managed 

EDC system specialist

Has understanding/knowledge about:

  • The data to be FAIRified and how they are managed 

    • Global standards applicable to the data resource interoperability

    • Architectural features of the software that is (or will be) used for managing the data

    • FAIR software services and their deployment

    • Global standards for data access 

    • Global standards applicable to the data resource interoperability

    • The data to be FAIRified and how they are managed 

    FAIR data stewards

    <See the other page>

    • Global standards applicable to the data resource interoperability

    • Global standards for data access 

    • Semantic data modelling

    • The data to be FAIRified and how they are managed 

    • The FAIRification process (guiding and monitoring it)

    • Semantic data modelling

    • Global standards applicable to the data resource interoperability

      Global standards for data access 

    Health-RI expert team

    Has understanding/knowledge about:

    • On FAIR software services and their deployment

    Institutional Ethical Review Board

    Has understanding/knowledge about:

    • Access policies applicable to the resource

    Local data stewards = Data Steward

    Data stewardship is a relatively new profession and a catch-all term for numerous support functions, roles and activities. It implies professional and careful treatment of data throughout all stages of a research process.

    Has understanding/knowledge about:

    • Semantic data modellingAccess policies applicable to the resource

    • Global standards applicable to the data resource interoperability

    • Global standards for data access 

    • Semantic data modelling

    • The data to be FAIRified and how they are managed Access policies applicable to the resource

    • The FAIRification process (guiding and monitoring it)

    Even nakijken: weet een data steward iets van standards/semantic modeling? Kan je dat verwachten?

    Patient advocate for the domain

    Has understanding/knowledge about:

    • On the data to be FAIRified and how they are managed 

    • On the domain and on what is a data resource is used for

    Semantic data modelling specialists

    Has understanding/knowledge about:

    • Semantic data modelling

    Senior expert of standards for automated access protocols and privacy preservation

    Has understanding/knowledge about:

    • Global standards for data access 

    Senior healthcare interoperability expert

    Has understanding/knowledge about:

    • Global standards applicable to the data resource interoperability

    Software developer = Research Software Engineer

    Research software engineers (RSE) in the life sciences design, develop and maintain software systems that help researchers manage their software and data. The RSE’s software tools and infrastructure are critical in enabling scientific research to be conducted effectively.

    Has understanding/knowledge about:

    FAIR software services and their deployment

    • Architectural features of the software that is (or will be) used for managing the data

     

    Expertise/Knowledge

    Example Experts

    a

    On

    • the data

    to be FAIRified and how they are managed 

  • Local data steward

    • FAIR

    data steward

  • Data manager

  • EDC system specialist

  • Clinicians specialised in the domain

  • Patient advocate for the domain

    • b

    On the domain and on what a data resource is used for

    • Clinicians specialised in the domain

    • Patient advocate for the domain

    c

    On architectural features of the

    • software

    that is (or will be) used for managing the data

    • EDC system specialist

    • Software developer

    d

    On access policies applicable to the resource

    • Local data steward

    • Clinicians specialised in the domain

    • Institutional Ethical Review Board

    e

    On the FAIRification process (guiding and monitoring it)

    • Local data stewards

    • FAIR data stewards

    f

    On FAIR software

    • services and their deployment

    • EDC system specialist

    • Software developer

    • Health-RI expert team

    g

    On semantic data modelling

    • Local and FAIR data steward

    • Semantic data modelling specialists

    • Clinicians specialised in the domain

    h

    On global standards applicable to the data resource interoperability

    • Local and FAIR data stewards

    • EDC system specialist

    • Senior healthcare interoperability expert

    i

    On global standards for data access 

    • Local data and FAIR stewards

    • EDC system specialist

    • Senior expert of standards for automated access protocols and privacy preservation

    [Generic] 

    Data FAIRification requires different types of expertise and should therefore be carried out in a multidisciplinary team guided by FAIR data steward(s). The different sets of expertise are on i) the data to be FAIRified and how they are managed, ii) the domain and the aims of the data resource within it, iii) architectural features of the software that is (or will be) used for managing the data, iv) access policies applicable to the resource, v) the FAIRification process (guiding and monitoring it), vi) FAIR software services and their deployment, vii) data modelling, viii) global standards applicable to the data resource, and ix) global standards for data access. A good working approach is to organize a team that contains or has access to the required expertise. The core of such a team may be formed by data stewards, with at least expertise of the local environment and of the FAIRification process in general. 

    → teams needs expertise in these areas (these are the exact same as used by De Nove table; I’m guessing de novo used the general paper. That’s great though. )

    1. The data to be FAIRified and how they are managed,

    2. the domain and the aims of the data resource within it

    3. architectural features of the software that is (or will be) used for managing the data

    4. access policies applicable to the resource

    5. the FAIRification process (guiding and monitoring it),

    6. FAIR software services and their deployment,

    7. data modelling,

    8. global standards applicable to the data resource

    9. global standards for data access.

    [RDMkit]

    Perhaps: https://rdmkit.elixir-europe.org/dm_coordination

    ...