2024-03-28T12:58:45Z
https://zenodo.org/oai2d
oai:zenodo.org:5775552
2022-03-11T13:01:00Z
user-fairsfair
user-acme-fair
user-eu
Josefine Nordling
Angus Whyte
Ricarda Braukmann
René van Horik
2021-12-13
<p>Data interoperability is key to the FAIR principles, yet can be challenging to put into practice. This document provides guidance on practices involved in achieving data interoperability, more specifically, practices around data citation, persistent identifiers (PIDs), semantic resources, and metadata. All of these create a data interoperability framework and are important building blocks of a FAIR ecosystem. The purpose of such a framework is to set some specific requirements for the digital objects that it will be applied to. Generally these include that the digital object/data need to be accompanied by standardised metadata for it to be cited and be unambiguously identified, using a persistent identifier. The metadata should also describe the object according to a community-endorsed vocabulary, richly enough for it to be understandable and reusable by anyone in that community. In addition, the data files that comprise the object need to be represented in common and open formats.</p>
<p>ACME-FAIR is a 7-part guide developed in the FAIRsFAIR project, whose main purpose is to help managers of Research Data Management and related professional services to self-assess how they are enabling researchers, and the professional staff who support them, to put the FAIR data principles into practice (for short we refer to this as ‘FAIR-enabling practice’). This part addresses the key issue of <strong>Defining Data Interoperability Frameworks. </strong>Please give us your comments in any of the ways detailed on p.5.</p>
https://doi.org/10.5281/zenodo.5775552
oai:zenodo.org:5775552
eng
Zenodo
https://zenodo.org/communities/acme-fair
https://zenodo.org/communities/eu
https://zenodo.org/communities/fairsfair
https://doi.org/10.5281/zenodo.5775551
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
FAIR principles, interoperability frameworks, research data management
Defining Data Interoperability Frameworks: ACME-FAIR Issue #5
info:eu-repo/semantics/report
oai:zenodo.org:5728376
2022-03-11T11:49:59Z
user-fairsfair
user-acme-fair
user-eu
Laura Molloy
Angus Whyte
Marjan Grootveld
Lennart Stoy
Bregt Saenen
2021-11-25
<p>Making and keeping data FAIR requires extensive and complex technical infrastructure, but it also requires systematic and sustained improvements in the human practices of managing research data. These improvements can be brought about through training, mentoring and recognition measures, which naturally also have implications for policymaking at the supra-national, sectoral, national, institutional, departmental and project levels.</p>
<p>ACME-FAIR is a 7-part guide developed in the FAIRsFAIR project, whose main purpose is to help managers of Research Data Management and related professional services to self-assess how they are enabling researchers, and the professional staff who support them, to put the FAIR data principles into practice (for short we refer to this as ‘FAIR-enabling practice’). This part addresses the key issue of <strong>Professionalising Roles through Training, Mentoring, and Recognition. </strong>We welcome your feedback.</p>
https://doi.org/10.5281/zenodo.5728376
oai:zenodo.org:5728376
eng
Zenodo
https://zenodo.org/communities/acme-fair
https://zenodo.org/communities/eu
https://zenodo.org/communities/fairsfair
https://doi.org/10.5281/zenodo.5728375
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
FAIR data, capability maturity, engagement, research data management
Professionalising Roles through Training, Mentoring, and Recognition: ACME-FAIR Issue#3
info:eu-repo/semantics/report
oai:zenodo.org:6345332
2022-03-11T01:49:24Z
user-fairsfair
user-acme-fair
user-eu
Joy Davidson
Angus Whyte
Laura Molloy
Marjan Grootveld
Mark Thorley
2022-03-10
<p>The existence of FAIR-aligned and harmonised data policies across various stakeholders such as funding bodies, publishers and Research Performing Organisations (RPOs) is crucial for ensuring that we can progress from a vision of the European Open Science Cloud (EOSC) to it becoming a fully functioning reality. As noted in the Turning FAIR into Reality report and action plan, policies define and regulate various components of a FAIR ecosystem and the relationships between them. Indeed, policies are a cross-cutting theme in Turning FAIR into Reality (TFiR) and are reflected in many of the priority and supporting actions presented in the action plan. </p>
<p>This guide aims to help Research Performing Organisations to assess the data policy framework currently in place and to consider where possible improvements may be needed. To complement the guide, a FAIRsFAIR policy support checklist is available. This aims to help RPOs to consider the content of their data policy, and how they might better align it with the FAIR Principles.</p>
<p>ACME-FAIR is a 7-part guide developed in the FAIRsFAIR project, whose main purpose is to help managers of Research Data Management and related professional services to self-assess how they are enabling researchers, and the professional staff who support them, to put the FAIR data principles into practice (for short we refer to this as ‘FAIR-enabling practice’). This part addresses the key issue of <strong>Defining the FAIR data policy environment. </strong></p>
https://doi.org/10.5281/zenodo.6345332
oai:zenodo.org:6345332
eng
Zenodo
https://zenodo.org/communities/acme-fair
https://zenodo.org/communities/eu
https://zenodo.org/communities/fairsfair
https://doi.org/10.5281/zenodo.5820637
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
FAIR data principles
data policy
research data management
RDM
FAIR implementation
Defining the Policy Environment: ACME-FAIR Issue #1
info:eu-repo/semantics/report
oai:zenodo.org:5783449
2022-03-10T21:50:24Z
user-fairsfair
user-acme-fair
user-eu
Marjan Grootveld
Ricarda Braukmann
René van Horik,
Maaike Verburg
Angus Whyte
2021-12-15
<p>Ensuring sustainable access to the data collected and produced in research processes is a critical concern for governments and research funding bodies in Europe and internationally. Research Performing Organisations (RPOs) such as universities and research institutes are key players in this endeavour. This requires data to be produced and managed according to the FAIR data stewardship principles, to be <em>Findable, Accessible, Interoperable, and Reusable</em>. Curating the data involves keeping it FAIR, and this requires services capable of applying the TRUST principles. These involve providing <em>Transparency </em>about data holdings, taking <em>Responsibility</em> for the data integrity, maintaining <em>User focus</em> to serve communities, ensuring <em>Sustainability</em> of services to preserve data, and utilizing <em>Technology </em>to fulfill these principles. To make this happen, RPOs can partner with Trustworthy Repositories to achieve a level of technical preparedness that will ensure long-term accessibility to publicly-funded data holdings. This guide aims to offer RPO staff help to identify an appropriate level of preparedness for their circumstances.</p>
<p>ACME-FAIR is a 7-part guide developed in the FAIRsFAIR project, whose main purpose is to help managers of Research Data Management and related professional services to self-assess how they are enabling researchers, and the professional staff who support them, to put the FAIR data principles into practice (for short we refer to this as ‘FAIR-enabling practice’). This part addresses the key issue of <strong>ensuring trustworthy curation. </strong>Please give us your comments in any of the ways detailed on p.5.</p>
https://doi.org/10.5281/zenodo.5783449
oai:zenodo.org:5783449
eng
Zenodo
https://zenodo.org/communities/acme-fair
https://zenodo.org/communities/eu
https://zenodo.org/communities/fairsfair
https://doi.org/10.5281/zenodo.5783448
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
FAIR principles, research data curation, trustworthy repositories
Ensuring Trustworthy Curation: ACME-FAIR Issue #7
info:eu-repo/semantics/report
oai:zenodo.org:6345114
2022-03-11T01:49:21Z
user-acme-fair
user-eu
Angus Whyte
Marjan Grootveld
Maaike Verburg
René van Horik
2022-03-10
<p>To put the FAIR principles into practice research projects need to make choices, assisted by the professional support staff in their organisations. Research performing organisations (RPOs) therefore need to offer a supportive environment for selecting data, services, and repositories. Consider these choices from the investigators’ point of view. As a researcher, how should my project decide which data, of all that it produces, it should focus effort to make FAIR? Of all the services available, how do we identify some that will help manage data in a FAIR way? And which of the multitude of repositories we could potentially use to safeguard the data at the end of the project should we choose to do that? This guide aims to help organisations assess the support they offer researchers, data stewards and others whose role involves making such choices.</p>
https://doi.org/10.5281/zenodo.6345114
oai:zenodo.org:6345114
eng
Zenodo
https://zenodo.org/communities/acme-fair
https://zenodo.org/communities/eu
https://doi.org/10.5281/zenodo.6144794
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
research data appraisal
data selection
repository selection
FAIR principles
FAIR services
FAIR implementation
Selecting Data, Services, and Repositories for FAIR: ACME-FAIR Issue #6
info:eu-repo/semantics/report
oai:zenodo.org:6346747
2022-03-11T13:49:07Z
user-fairsfair
user-acme-fair
user-eu
Angus Whyte
Laura Molloy
Marjan Grootveld
Mark Thorley
2022-03-11
<p>Data management plans (DMPs) are recognised as an important element of good practice in research management, including by the European Commission and Science Europe. Especially since the beginning of the EC Horizon 2020 programme, funders at national and international level expect research grant holders to complete a DMP demonstrating they have planned how data will be managed from the outset of a research project. Research Producing Organisations (RPOs) are expected to play their part, to help their researchers in producing data that is FAIR, and in depositing it in a trustworthy repository that can keep it in FAIR condition. And in some cases including the EC Horizon Europe programme, there is a need for DMPs to cover all research outputs (data, code, models, samples etc.), to be updated throughout the project, and ultimately made available as a project deliverable.</p>
<p>ACME-FAIR is a 7-part guide developed in the FAIRsFAIR project, whose main purpose is to help managers of Research Data Management and related professional services to self-assess how they are enabling researchers, and the professional staff who support them, to put the FAIR data principles into practice (for short we refer to this as ‘FAIR-enabling practice’). This part addresses the key issue of <strong>Supporting data management planning. </strong>The guide aims to help Research Performing Organisations assess their own needs to support DMPs, taking into account what they currently have in place and where improvements may be needed.</p>
https://doi.org/10.5281/zenodo.6346747
oai:zenodo.org:6346747
eng
Zenodo
https://zenodo.org/communities/acme-fair
https://zenodo.org/communities/eu
https://zenodo.org/communities/fairsfair
https://doi.org/10.5281/zenodo.5840528
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
DMP
Data Management Plans
FAIR principles
research data management
machine-actionable DMP
FAIR implementation
Supporting Data Management Planning: ACME-FAIR Issue #4
info:eu-repo/semantics/report
oai:zenodo.org:5747043
2022-03-11T11:50:00Z
user-fairsfair
user-acme-fair
user-eu
Laura Molloy
Angus Whyte
Marjan Grootveld
Lennart Stoy
Bregt Saenen
2021-11-25
<p>Making and keeping data FAIR requires extensive and complex technical infrastructure, but it also requires systematic and sustained improvements in the human practices of managing research data. These improvements can be brought about through training, mentoring and recognition measures, which naturally also have implications for policymaking at the supra-national, sectoral, national, institutional, departmental and project levels.</p>
<p>ACME-FAIR is a 7-part guide developed in the FAIRsFAIR project, whose main purpose is to help managers of Research Data Management and related professional services to self-assess how they are enabling researchers, and the professional staff who support them, to put the FAIR data principles into practice (for short we refer to this as ‘FAIR-enabling practice’). This part addresses the key issue of <strong>Professionalising Roles through Training, Mentoring, and Recognition. </strong>Please give us your comments in any of the ways detailed on p.5.</p>
https://doi.org/10.5281/zenodo.5747043
oai:zenodo.org:5747043
eng
Zenodo
https://zenodo.org/communities/acme-fair
https://zenodo.org/communities/eu
https://zenodo.org/communities/fairsfair
https://doi.org/10.5281/zenodo.5728375
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
FAIR data, capability maturity, engagement, research data management
Professionalising Roles through Training, Mentoring, and Recognition: ACME-FAIR Issue#3
info:eu-repo/semantics/report
oai:zenodo.org:6344742
2022-03-11T01:49:15Z
user-acme-fair
user-eu
Angus Whyte
Laura Molloy
Marjan Grootveld
René van Horik
Mari Elisa Kuusneimi
Mark Thorley
2022-03-10
<p>Research performing organisations (RPOs) are expected to provide a service offering professional support for researchers to produce and use FAIR outputs. A wide variety of internal and external stakeholders are likely to influence RPO expectations. Taking action in this complex landscape requires collaboration across the organisation, involving core Research Office, Library and IT services, and drawing specialist advice from Human Resources, Legal or Commercialisation units (for example). Establishing and maintaining a service will most probably involve team effort to set measurable objectives over the short, medium, and long terms. Regardless of the maturity of the service, the team will need to consider (or review) how it addresses such questions as ‘who are our customers or beneficiaries? What is the value offered to them? What are the key capabilities, roles and relationships we need to deliver them? How will we resource the costs of providing them?’ This guide aims to offer a basis for productive discussion among the people involved in addressing such questions.</p>
https://doi.org/10.5281/zenodo.6344742
oai:zenodo.org:6344742
Zenodo
https://zenodo.org/communities/acme-fair
https://zenodo.org/communities/eu
https://doi.org/10.5281/zenodo.6344741
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
FAIR principles
capability model
research data management
maturity model
Developing Sustainable Business Models: ACME-FAIR Issue #2
info:eu-repo/semantics/report
oai:zenodo.org:5840529
2022-03-11T12:45:24Z
user-fairsfair
user-acme-fair
user-eu
Angus Whyte
Laura Molloy
Marjan Grootveld
Mark Thorley
2022-01-12
<p>Data management plans (DMPs) are recognised as an important element of good practice in research management, including by the European Commission and Science Europe. Especially since the beginning of the EC Horizon 2020 programme, funders at national and international level expect research grant holders to complete a DMP demonstrating they have planned how data will be managed from the outset of a research project. Research Producing Organisations (RPOs) are expected to play their part, to help their researchers in producing data that is FAIR, and in depositing it in a trustworthy repository that can keep it in FAIR condition. And in some cases including the EC Horizon Europe programme, there is a need for DMPs to cover all research outputs (data, code, models, samples etc.), to be updated throughout the project, and ultimately made available as a project deliverable.</p>
<p>ACME-FAIR is a 7-part guide developed in the FAIRsFAIR project, whose main purpose is to help managers of Research Data Management and related professional services to self-assess how they are enabling researchers, and the professional staff who support them, to put the FAIR data principles into practice (for short we refer to this as ‘FAIR-enabling practice’). This part addresses the key issue of <strong>Supporting data management planning. </strong>The guide aims to help Research Performing Organisations assess their own needs to support DMPs, taking into account what they currently have in place and where improvements may be needed. Please give us your comments in any of the ways detailed on p.5.</p>
https://doi.org/10.5281/zenodo.5840529
oai:zenodo.org:5840529
eng
Zenodo
https://zenodo.org/communities/acme-fair
https://zenodo.org/communities/eu
https://zenodo.org/communities/fairsfair
https://doi.org/10.5281/zenodo.5840528
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
DMP, Data Management Plans, FAIR principles, research data management, machine-actionable DMP
Supporting Data Management Planning: ACME-FAIR Issue#4
info:eu-repo/semantics/report
oai:zenodo.org:6345280
2022-03-11T13:01:00Z
user-fairsfair
user-acme-fair
user-eu
Josefine Nordling
Angus Whyte
Ricarda Braukmann
René van Horik
2021-12-13
<p>Data interoperability is key to the FAIR principles, yet can be challenging to put into practice. This document provides guidance on practices involved in achieving data interoperability, more specifically, practices around data citation, persistent identifiers (PIDs), semantic resources, and metadata. All of these create a data interoperability framework and are important building blocks of a FAIR ecosystem. The purpose of such a framework is to set some specific requirements for the digital objects that it will be applied to. Generally these include that the digital object/data need to be accompanied by standardised metadata for it to be cited and be unambiguously identified, using a persistent identifier. The metadata should also describe the object according to a community-endorsed vocabulary, richly enough for it to be understandable and reusable by anyone in that community. In addition, the data files that comprise the object need to be represented in common and open formats.</p>
<p>ACME-FAIR is a 7-part guide developed in the FAIRsFAIR project, whose main purpose is to help managers of Research Data Management and related professional services to self-assess how they are enabling researchers, and the professional staff who support them, to put the FAIR data principles into practice (for short we refer to this as ‘FAIR-enabling practice’). This part addresses the key issue of <strong>Defining Data Interoperability Frameworks. </strong>Please give us your comments in any of the ways detailed on p.5.</p>
https://doi.org/10.5281/zenodo.6345280
oai:zenodo.org:6345280
eng
Zenodo
https://zenodo.org/communities/acme-fair
https://zenodo.org/communities/eu
https://zenodo.org/communities/fairsfair
https://doi.org/10.5281/zenodo.5775551
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
FAIR principles
interoperability frameworks
research data management
FAIR implementation
Defining Data Interoperability Frameworks: ACME-FAIR Issue #5
info:eu-repo/semantics/report
oai:zenodo.org:6345294
2022-03-11T01:49:24Z
user-fairsfair
user-acme-fair
user-eu
Marjan Grootveld
Ricarda Braukmann
René van Horik,
Maaike Verburg
Angus Whyte
2022-03-10
<p>Ensuring sustainable access to the data collected and produced in research processes is a critical concern for governments and research funding bodies in Europe and internationally. Research Performing Organisations (RPOs) such as universities and research institutes are key players in this endeavour. This requires data to be produced and managed according to the FAIR data stewardship principles, to be <em>Findable, Accessible, Interoperable, and Reusable</em>. Curating the data involves keeping it FAIR, and this requires services capable of applying the TRUST principles. These involve providing <em>Transparency </em>about data holdings, taking <em>Responsibility</em> for the data integrity, maintaining <em>User focus</em> to serve communities, ensuring <em>Sustainability</em> of services to preserve data, and utilizing <em>Technology </em>to fulfill these principles. To make this happen, RPOs can partner with Trustworthy Repositories to achieve a level of technical preparedness that will ensure long-term accessibility to publicly-funded data holdings. This guide aims to offer RPO staff help to identify an appropriate level of preparedness for their circumstances.</p>
<p>ACME-FAIR is a 7-part guide developed in the FAIRsFAIR project, whose main purpose is to help managers of Research Data Management and related professional services to self-assess how they are enabling researchers, and the professional staff who support them, to put the FAIR data principles into practice (for short we refer to this as ‘FAIR-enabling practice’). This part addresses the key issue of <strong>ensuring trustworthy curation. </strong></p>
https://doi.org/10.5281/zenodo.6345294
oai:zenodo.org:6345294
eng
Zenodo
https://zenodo.org/communities/acme-fair
https://zenodo.org/communities/eu
https://zenodo.org/communities/fairsfair
https://doi.org/10.5281/zenodo.5783448
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
FAIR principles
research data curation
trustworthy repositories
FAIR implementation
Ensuring Trustworthy Curation: ACME-FAIR Issue #7
info:eu-repo/semantics/report
oai:zenodo.org:6144795
2022-03-10T19:42:33Z
user-acme-fair
user-eu
Angus Whyte
Marjan Grootveld
Maaike Verburg
René van Horik
2022-02-18
<p>To put the FAIR principles into practice research projects need to make choices, assisted by the professional support staff in their organisations. Research performing organisations (RPOs) therefore need to offer a supportive environment for selecting data, services, and repositories. Consider these choices from the investigators’ point of view. As a researcher, how should my project decide which data, of all that it produces, it should focus effort to make FAIR? Of all the services available, how do we identify some that will help manage data in a FAIR way? And which of the multitude of repositories we could potentially use to safeguard the data at the end of the project should we choose to do that? This guide aims to help organisations assess the support they offer researchers, data stewards and others whose role involves making such choices.</p>
https://doi.org/10.5281/zenodo.6144795
oai:zenodo.org:6144795
eng
Zenodo
https://zenodo.org/communities/acme-fair
https://zenodo.org/communities/eu
https://doi.org/10.5281/zenodo.6144794
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
research data appraisal, data selection, repository selection, FAIR principles, FAIR services, implementation
Selecting Data, Services, and Repositories for FAIR: ACME-FAIR Issue #6
info:eu-repo/semantics/report
oai:zenodo.org:6346797
2022-03-11T13:49:07Z
user-fairsfair
user-acme-fair
user-eu
Josefine Nordling
Angus Whyte
Ricarda Braukmann
René van Horik
2022-03-11
<p>Data interoperability is key to the FAIR principles, yet can be challenging to put into practice. This document provides guidance on practices involved in achieving data interoperability, more specifically, practices around data citation, persistent identifiers (PIDs), semantic resources, and metadata. All of these create a data interoperability framework and are important building blocks of a FAIR ecosystem. The purpose of such a framework is to set some specific requirements for the digital objects that it will be applied to. Generally these include that the digital object/data need to be accompanied by standardised metadata for it to be cited and be unambiguously identified, using a persistent identifier. The metadata should also describe the object according to a community-endorsed vocabulary, richly enough for it to be understandable and reusable by anyone in that community. In addition, the data files that comprise the object need to be represented in common and open formats.</p>
<p>ACME-FAIR is a 7-part guide developed in the FAIRsFAIR project, whose main purpose is to help managers of Research Data Management and related professional services to self-assess how they are enabling researchers, and the professional staff who support them, to put the FAIR data principles into practice (for short we refer to this as ‘FAIR-enabling practice’). This part addresses the key issue of <strong>Defining Data Interoperability Frameworks. </strong></p>
https://doi.org/10.5281/zenodo.6346797
oai:zenodo.org:6346797
eng
Zenodo
https://zenodo.org/communities/acme-fair
https://zenodo.org/communities/eu
https://zenodo.org/communities/fairsfair
https://doi.org/10.5281/zenodo.5775551
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
FAIR principles
interoperability frameworks
research data management
FAIR implementation
Defining Data Interoperability Frameworks: ACME-FAIR Issue #5
info:eu-repo/semantics/report
oai:zenodo.org:5820638
2022-03-10T22:18:47Z
user-fairsfair
user-acme-fair
user-eu
Joy Davidson
Angus Whyte
Laura Molloy
Marjan Grootveld
Mark Thorley
2022-01-05
<p>The existence of FAIR-aligned and harmonised data policies across various stakeholders such as funding bodies, publishers and Research Performing Organisations (RPOs) is crucial for ensuring that we can progress from a vision of the European Open Science Cloud (EOSC) to it becoming a fully functioning reality. As noted in the Turning FAIR into Reality report and action plan, policies define and regulate various components of a FAIR ecosystem and the relationships between them. Indeed, policies are a cross-cutting theme in Turning FAIR into Reality (TFiR) and are reflected in many of the priority and supporting actions presented in the action plan. </p>
<p>This guide aims to help Research Performing Organisations to assess the data policy framework currently in place and to consider where possible improvements may be needed. To complement the guide, a FAIRsFAIR policy support checklist will be available. This aims to help RPOs to consider the content of their data policy, and how they might better align it with the FAIR Principles.</p>
<p>ACME-FAIR is a 7-part guide developed in the FAIRsFAIR project, whose main purpose is to help managers of Research Data Management and related professional services to self-assess how they are enabling researchers, and the professional staff who support them, to put the FAIR data principles into practice (for short we refer to this as ‘FAIR-enabling practice’). This part addresses the key issue of <strong>Defining the FAIR data policy environment. </strong>Please give us your comments in any of the ways detailed on p.5.</p>
https://doi.org/10.5281/zenodo.5820638
oai:zenodo.org:5820638
eng
Zenodo
https://zenodo.org/communities/acme-fair
https://zenodo.org/communities/eu
https://zenodo.org/communities/fairsfair
https://doi.org/10.5281/zenodo.5820637
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
FAIR data principles, data policy, research data management, RDM
Defining the Policy Environment: ACME-FAIR Issue #1
info:eu-repo/semantics/report
oai:zenodo.org:6346589
2022-03-11T13:49:07Z
user-fairsfair
user-acme-fair
user-eu
Laura Molloy
Angus Whyte
Marjan Grootveld
Lennart Stoy
Bregt Saenen
2022-03-11
<p>Making and keeping data FAIR requires extensive and complex technical infrastructure, but it also requires systematic and sustained improvements in the human practices of managing research data. These improvements can be brought about through training, mentoring and recognition measures, which naturally also have implications for policymaking at the supra-national, sectoral, national, institutional, departmental and project levels.</p>
<p>ACME-FAIR is a 7-part guide developed in the FAIRsFAIR project, whose main purpose is to help managers of Research Data Management and related professional services to self-assess how they are enabling researchers, and the professional staff who support them, to put the FAIR data principles into practice (for short we refer to this as ‘FAIR-enabling practice’). This part addresses the key issue of <strong>Professionalising Roles through Training, Mentoring, and Recognition. </strong></p>
https://doi.org/10.5281/zenodo.6346589
oai:zenodo.org:6346589
eng
Zenodo
https://zenodo.org/communities/acme-fair
https://zenodo.org/communities/eu
https://zenodo.org/communities/fairsfair
https://doi.org/10.5281/zenodo.5728375
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
FAIR principles
capacity building
capability maturity
research data management
FAIR implementation
Professionalising Roles through Training, Mentoring, and Recognition: ACME-FAIR Issue#3
info:eu-repo/semantics/report