Supporting an EOSC-ready digitally skilled workforce

Topic description

ExpectedOutcome:

Project results are expected to contribute to all the following expected outcomes:

• availability of highly and appropriately skilled professionals enabling the practice of Open Science with adequate knowledge of standards, applications and tools and best practices for delivering, managing, re-using, sharing and analysing FAIR data, as well as other digital research objects;
• researchers are able to transform the way they carry out research and exploit research outputs, leading to better quality and more productivity of research;
• contribute to the Horizon Europe EOSC Partnership.

Development of new support material, curricula and learning pathways for researchers, data curators, and data stewards and new types of professionals. To ensure an efficient uptake and exploitation of data by Public Authorities (e.g. for evidence-based policy making), policy makers should also become skilled in data acquisition, management and analysis. Proposals should therefore cover the following activities:

• Engage with the relevant stakeholders at national and institutional level in order to co-create, promote, broker and ensure the recognition of digital career profiles specifically related to Open Science. This includes the development of quality assurance mechanisms for professional training and qualifications.
• Promote existing and develop new curricula (at undergraduate, PhD and professional level) that meet the demands of open and data-intensive science, and the establishment of advanced learning environments, in order to train the next generation of scientists, librarians and infrastructure professionals on topics such as the management and integration of diverse data flows and artificial intelligence for FAIR data management.
• Foster the development of a distributed pan-European user support network, supporting the collaboration of existing networks of competence and data curation centres, in order to provide expertise on storing, sharing and reusing digital outputs, as well as on the onboarding of EOSC services and the provision of open science resources.
• Support the development of a quality assurance and certification framework for learning material taking into account the life cycle of materials to ensure that training is up to date with technology and policy changes, as part of lifelong learning programmes.
• Promote the training of civil servants, policy makers and agencies, as well as their engagement with researchers, in order to foster the efficient uptake of relevant scientific data by public administration and encourage its use for evidence-based policy making, building on best practices where appropriate^[1].

Proposals should take into account and collaborate with the resulting project/s from the topic H2020-INFRAEOSC-03-2020^[2] and building on the results of the projects funded under the topic H2020-INFRAEOSC-05-2020^[2] on training, earmarking the necessary resources to do so. In addition, similar collaboration should be envisaged with the resulting grant/s from the topic HORIZON-INFRA-2021-EOSC-01-05. They should establish synergies with national and regional programmes on digital skills and training as well as with other parts of Horizon Europe (e.g. Marie Skłodowska-Curie Actions, activities of EIT KICs^[4]) and other EU funding sources (e.g. Digital Europe Programme (DEP), Erasmus+), and policies (e.g. European Higher Education Area (EHEA)). They should be credible in that the necessary funds for hiring or continuing the employment of staff, such as “data curators and stewards” in universities and research performing institutions, have been ensured at institutional, regional or national level, as these funds are not to be provided by the Commission.

To ensure complementarity of outcomes, proposals are expected to cooperate and align with activities of the EOSC Partnership and to coordinate with relevant initiatives and projects contributing to the development of EOSC.

Co-programmed European Partnerships
EOSC and FAIR data

[1]e.g. Scientific Advice to European Policy in a Complex World

[2]https://ec.europa.eu/research/participants/data/ref/h2020/wp/2018-2020/main/h2020-wp1820-infrastructures_en.pdf

[3]https://ec.europa.eu/research/participants/data/ref/h2020/wp/2018-2020/main/h2020-wp1820-infrastructures_en.pdf

[4]Knowledge and Innovation Communities of the European Institute of Innovation and Technology