| Status | ||||
|---|---|---|---|---|
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A description of the main tasks usually handled by each role.
A collection of research data management responsibilities for each role.
Links to RDMkit guidelines and advice (where applicable) on useful information for getting started with data management specific to each role.
The table below is mostly based on De Novo and RDMkit. <linkjes>
Expert | Description | Metroline Steps |
|---|---|---|
Domain specialist | Domain specialists 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. | |
Information Professionals | Librarians, archivists, and information scientists involved in organizing and preserving data assets. | |
Institutional Review Board | The IRB is concerned with protecting the rights of human subjects and is charged with the responsibility of reviewing research to which the Medical Research Involving Human Subjects Act WMO is applicable involving human participants. Mooie zin van maken a committee at an institution that applies research ethics by reviewing the methods proposed for research involving human subjects, to ensure that the projects are ethical. The main goal of IRB reviews is to ensure that study participants are not harmed (or that harms are minimal and outweighed by research benefits https://www.amsterdamumc.org/en/research-support/ethical-review.htm | METC vs IRB? Onderzoek dat onder de Wet medisch-wetenschappelijk onderzoek met mensen (WMO) valt, moet vooraf worden getoetst door een onafhankelijke commissie van deskundigen. |
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. | |
TODO Research software engineers (RSE) design, develop and maintain software systems that help researchers reach their scientific goals. You are responsible for the implementation of IT infrastructure solutions and the access to data and software. 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. (copy-pasted)Mijke, since you were involved in RDMkit, do you know what they mean here? It’s called a “software engineer”, but we don’t see them engineering software / writing scripts in the description given by RDMkit. | ||
Semantic data modelling specialists | A semantic modeler is a specialist responsible for creating and managing semantic models. These models are a representation of knowledge and concepts in a structured format that a computer can understand. | |
Senior expert of standards for automated access protocols and privacy preservation | Has understanding/knowledge about:
| |
Senior healthcare interoperability expert | Has understanding/knowledge about:
| |
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. |
Potential Todo:
Add [Generic] expertise list to each of the Experts in the table (if possible)
Rewrite some descriptions that are copy-pasted
Verify Expertise already mentioned in step exists here
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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.
[Generic]
→ In list form, expertise required:
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The data to be FAIRified and how they are managed,
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the domain and the aims of the data resource within it
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architectural features of the software that is (or will be) used for managing the data
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access policies applicable to the resource
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the FAIRification process (guiding and monitoring it),
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FAIR software services and their deployment,
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data modelling,
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global standards applicable to the data resource
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.
[RDMkit]
Perhaps: https://rdmkit.elixir-europe.org/dm_coordination
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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.
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