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Expert | Description | Metroline Steps |
|---|---|---|
Domain specialistexpert | Domain specialists experts have deep knowledge and expertise in a particular domain. They have a deep understanding of the intricacies, challenges, and nuances of their field. | |
FAIR Data Steward/Data manager | Individuals responsible for managing and curating research or healthcare data within organizations or projects. Job title and exact activities and responsibilities vary between organisations. In the Metroline steps we will refer to this role as “data steward”. Details on this role in the team are described in a separate step Have a FAIR data steward on board. | |
EDC system specialist | Individual who has experience with and knowledge of Electronic Data Capture (EDC) systems, such as Castor EDC, REDCAP or OpenClinica. They are in charge of setting up user access controls, data validation checks and electronic case report forms in the EDC system. They also troubleshoot problems, offer technical help to researchers, and ensure data integrity and regulatory compliance. | |
Information Professionals | Librarians, archivists, and information scientists involved in organizing and preserving data assets. | |
Institutional Review Board (IRB) / Medical Ethics Review Committee (METC) | Evaluate research protocols and ensure the research complies with regulatory requirements and ethical standards. For research to which the WMO (Medical Research Involving Human Subjects Act) is applicable, evaluation must be done by an accredited METC or by the CCMO (Central Committee on Research Involving Human Subjects). | |
IT and Systems Administrators | Professionals responsible for maintaining data infrastructure(s) and ensuring technical compatibility and accessibility for an organisation or department. | |
Decision-makers responsible for research data management policies that promote FAIR data practices within an institute. | ||
Leads a clinical trial or research project. Responsible for following the data management requirements and guidelines of the organisation and/or funder. Decisions regarding data management are documented in the DMP (data management plan). | ||
Researcher / scientist | Professionals involved in collecting, analyzing, and sharing data as part of a clinical trial, research project or other scientific endeavors. | |
A Research Software Engineer (RSE) is a professional with in-depth knowledge of one or more research fields and expertise in software development and methodology. To address research issues and find solutions within their field of study, RSEs concentrate on creating and/or maintaining research software. | ||
Semantic data modelling specialists | A semantic modeler is a specialist data modelling specialsit is primarily responsible for creating designing and managing implementing semantic data models. These models are a representation of knowledge and concepts in a structured format that a computer can understand. They use tools like RDF, OWL and SPARQL. | |
Senior expert of standards for automated access protocols and privacy preservation | Has understanding/knowledge about:
Has expertise with standards for protocols for secure and automated access to sensitive data while preserving privacy. They guarantee adherence to pertinent guidelines and laws, such the GDPR. | |
Senior healthcare interoperability expert | Has understanding/knowledge about:
A healthcare interoperability expert is responsible for ensuring smooth communication and data interchange between various healthcare systems and applications, including electronic health records and medical devices. In compliance with legal requirements, they create, put into practice, and uphold interoperability standards and protocols that facilitate the safe and effective interchange of patient data. | |
Professionals involved in training and educating others, such as PhD students, postdocs, researchers, technicians and PIs. In case of FAIR related training this includes practices for managing and sharing data. |
Todo:
Rewrite some descriptions that are copy-pasted → done?
Verify Expertise already mentioned in step exists here
Hier nog naar kijken: https://research-dream-team-toolkit.readthedocs.io/en/latest/scenario.html
Zie onderaan
In the FAIRification objectives step the following expertise is mentioned:
Domain expert; provides context to the FAIRification efforts from the perspective of a domain
Data stewards; helps defining FAIR objectives to meet the project’s, funder’s, journal’s and/or institute’s requirements
FAIR experts,such as metadata/semantics specialists; helps specifying the metadata/modeling aspects of FAIR objectives
ELSI experts, help identifying the legal compliance and ethical aspects of your FAIR objectives.
[RDMkit]
Perhaps: https://rdmkit.elixir-europe.org/dm_coordination
Practical Examples from the Community
Example team:
The VASCA FAIRification core team consisted of a local data steward, an external FAIR data steward, and an EDC system specialist. Throughout the project, additional expertise was consulted, such as a clinician specialised in vascular anomalies, the Institutional Ethical Review Board, FAIR software developers, and researchers. A full overview of the different kinds of expertise and which part of the FAIRification process they contributed to can be found in TableS1
Links to demonstrator projects. FAIR experts
It is the responsibility of a FAIR (Findable, Accessible, Interoperable, and Reusable) specialist to ensure digital assets and data follow the FAIR principles. Tasks involve developing and implementing plans to enhance data discoverability via metadata enhancement and standardised identifiers, ensuring accessibility by instituting appropriate data storage and access methods and fostering interoperability by adopting shared data standards and formats.
ELSI experts
Assessing and handling the ELSI (Ethical, Legal, and Social Implications) components of research in domains like genetics and medicine falls under the purview of an ELSI specialist. They offer direction on how to handle difficult ethical dilemmas involving data sharing, privacy, informed consent, and possible societal repercussions of research findings.
Table from the dreamteam source
Areas of expertise | Roles |
|---|---|
Privacy and security |
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Ethics |
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Commercialisation / valorsation |
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Citizen science / societal engegement |
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Communication, education and outreach |
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Data and software |
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Project administration |
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Project funding |
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Infrastructure and instrumentation |
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Practical Examples from the Community
VASCERN (European Reference Network on Rare Multisystemic Vascular Diseases) describe the team used for the VASCA (Vascular Anomalies Registry) FAIRification in their De Novo paper, with a detailed description available in the paper’s supplementary material, table S1.
VASCA is a demonstrator project. More information can be found on its demonstrator page on the Health-RI website.
Training
Relevant training will be added in the future.
...
Plan is om deze sectie weg te laten en alles te verwerken de teksten
Salome Scholtens, Mijke Jetten, Jasmin Böhmer, Christine Staiger, Inge Slouwerhof, Marije van der Geest, & Celia W.G. van Gelder. (2022). Final report: Towards FAIR data steward as profession for the lifesciences. Report of a ZonMw funded collaborative approach built on existing expertise (Versie 4). Zenodo. https://doi.org/10.5281/zenodo.7225070
Resource below is about organising a workshop. Could be more relevant for one of Fieke’s resources somewhere?
Toolkit for building your dream team: “a resource intended to make it as easy as possible to organise a workshop aimed at raising awareness of and facilitating discussion around the diversity of roles that contribute to research”. […] “[t]he knowledge sector is now looking towards a team-based approach bringing together more overtly diverse team members with specific skills in funding, research design, data analysis, data management, software development, research ethics, political relationships, dealing with business, interdisciplinarity, communications etc.” https://research-dream-team-toolkit.readthedocs.io/en/latest/index.html
[FAIRopoly] https://www.ejprarediseases.org/fairopoly/
[FAIRinAction] https://www.nature.com/articles/s41597-023-02167-2
[Generic] https://direct.mit.edu/dint/article/2/1-2/56/9988/A-Generic-Workflow-for-the-Data-FAIRification
Contributors
Dena Tahvildari; Sander de Ridder; Jolanda Strubel; Bruna dos Santos Vieira; Mijke Jetten; Fieke Schoots; Ines De Oliveira Coelho Henriques; Shuxin Zhang; Alberto Cámara; César Bernabé; Joeri van der Velde