Rec. 28: Curriculum frameworks and training

[sjDCC]

A concerted effort should be made to coordinate, systematise and accelerate the pedagogy and availability of training for data skills, data science and data stewardship.

• Curriculum frameworks should be made available and be easily adaptable and reusable.
  Stakeholders: Institutions.

• Sharing and reuse of Open Educational Resources and reusable materials for data science and data stewardships programmes should be encouraged and facilitated.
  Stakeholders: Institutions; Global coordination fora; Data services.

• Train-the-Trainer programmes for data science and data stewardship roles should be developed, implemented and supported, so they can scale.
  Stakeholders: Institutions; Data services; Data stewards; Funders.

• A programme of certification and endorsement should be developed for organisations and programmes delivering Train-the-Trainer and/or data science and data stewardship training. As a first step, a lightweight peer-reviewed self-assessment would be a means of accelerating the development and implementation of quality training.
  Stakeholders: Institutions; Global coordination fora; Standards bodies.

[hollydawnmurray]

F1000 position: The Carpentries would be a good reference point for this work, with a great deal of experience in each of these points.

[katerbow]

DFG position: See comments to Recommendation 26.

[Falco-KUB]

Should the resources, programmes and materials be FAIR objects themselves? At least they should be catalogued according to Rec. 4

[pkdoorn]

Combine with Rec. #26 : Data science and stewardship skills #26

[mromanie]

ESO position
The difference with Rec 26 is not immediately clear.

[gtoneill]

Fully support the development of skills training and open availability of resources for Data Science and Data Stewardship. It is also crucial that (especially early-career) researchers are adequately accredited and rewarded for successfully following FAIR Data courses via institutions or Open Educational Resources. There is some overlap with previous recommendations including Recommendations 13, 14, 26, and 27 on roles and rewards as well as skills for data scientists and stewards. Perhaps merge?

[etothczifra]

DARIAH-ERIC position:
In research areas where data-drivenness is not a straightforward and mature concept, there is an especially strong need for consolidated interpretative frameworks around the notion of research data as well as for data management trainings to help equip researchers at all career stages with the skills they need to excel in a digital and open research environment. For researchers in Humanities, the Research Data Management module of the PARTHENOS Training Suite is a highly relevant resource in this respect as it has been designed to raise awareness towards emerging data management trends and best practices specifically tailored to Humanities’ questions and needs.
Building a registry of discipline-specific training resources could not only contribute to their wider dissemination and facilitate tailored-to-needs solutions but would also help in avoiding duplicating efforts.

On the other hand, enabling reciprocal learning and facilitating mutual understanding between the different stakeholders (researchers, IT specialists, data stewards) is also needed to usefully combine skills and to design components of data management infrastructure that are truly tailored or translated to the needs of the respective research communities.