...
Policy & strategy. Design strategies for raising awareness of RDM policies and regulations.
Compliance. Advise on institutional compliance with RDM policies and regulations.
Facilitating good RDM practices. Support stakeholders in adopting effective RDM practices.
RDM services. Develop, implement and monitor RDM workflows and practices.
Data infrastructure. Identify requirements for adequate RDM infrastructure and tools.
Knowledge management. Assess and ensure the sustainability of RDM knowledge and skills.
Network & communication. Build and maintain (inter)national RDM collaborations.
Data sharing & publishing. Identify gaps in support for data sharing and publishing.
Coordination of work. Supervise and support less experienced colleagues.
Coaching & process improvement. Improve work processes at different levels.
Soft skills. Apply competencies such as accuracy, persuasiveness, communication, collaboration and networking.
Step 4 - Ensure support and compliance
If extending your team with includes a FAIR data steward, also take the considerations below into account.
...
ensure they have access to the right support and resources.
Training opportunities. Ensure data stewards receive continuous training to stay updated on best practices, tools and policies.
Institutional and national networks. Connect data stewards with institutional, national and international networks to foster collaboration and professional growth. Central networks should be the first point of contact, including institutional data steward groups (via the Local Digital Competence Centers (LDCC)), regionally (e.g. your regional or the Open Science CommunityCommunities), nationally national networks (e.g. the Data Stewards Interest Group) or the and international level initiatives (e.g. RDA professionalising data stewardship Interest Group or the ELIXIR RDM Community). See also the Building your Community page. Depending on the nature of your project, it's beneficial for the FAIR data steward to have domain specific knowledge relevant to your research field. This enables them to better understand the context and requirements of the data being generated and ensures that they can effectively communicate page for more details.
Domain-specific knowledge. A data steward with expertise in your research field can better understand the data’s context and communicate effectively with researchers and stakeholders.
Funders more and more often Funder requirements. Many funders now require a data steward to be consulted or be part of a the project team. Check for specific responsibilities and tasks in the grant proposal and make sure your team’s FAIR data steward is able to meet them. Make sure data is handled in compliance with journal and institutional policies, and with (inter)national laws and regulations. Discuss in an early stage the condition of the journal you potentially consider to publish in, as well as the FAIR requirements by your institute. Ensure your team has the required FAIR data stewardship knowledge and skills. These could relate to, for instance, the use of relevant standards and uploading your (meta)data to a certain repository or cataloguegrant conditions to ensure compliance with specific expectations.
Publishing policies and local guidance. Ensure data handling aligns with institutional policies and national and international regulations. Discuss early stage requirements with local guidance bodies to meet FAIR standards and repository guidelines.
Expertise requirements for this step
...