Skills4EOSC/WP/Professional-Networks-lifelong-learning

(6.0) Professional Networks for lifelong learning

Objective(s):

Ingår i work package (WP): Skills4EOSC/WP/Professional-Networks-lifelong-learning

WP Leader: TU-Delft

Task leader: CBS

Bidragande organisationer: TU-Delft, CBS, UMEA

I Sverige: UMEA

WP objectives

(a) Map existing professional networks within countries/regions and across domains to identify any gaps; focus on networks of data stewards (including data curators, data librarians and other data professionals), Open Science Communities (OSCs) at national and European levels, as well as thematic networks (e.g. AI research, museum curators). (b) Address gaps by animating new networks to enable professionals to come together to exchange knowledge, best practices and to foster lifelong learning. (c) Ensure sustainability of professional networks by harmonising them under the umbrella of national competence centres, international bodies (such as RDA or the International Network of Open Science and Scholarship Communities) and domain specific-bodies (e.g. 4TU.ResearchData). (d) Foster growth of professional networks through a starter kit and a fellowship programme. (e) Engage with professional networks so that they support the development and embedding of the outcomes of this project, but also of the EOSC and its services as a whole.

Beskrivning av WP eller task

T6.1. Mapping of existing professional networks (M1-5, CBS) Existing professional networks will be mapped through a combination of desk research and requests (e.g. from the former EOSC WG on Skills and Training, the OpenAIRE NOADs, the GO FAIR Foundation Data Stewardship Competence Centers network, and the Skills4EOSC Competence Centre Network). This will be essential to understand which professional networks are active in which countries and to identify gaps.

T6.2. Development of starter kits for professional networks (M1-12, UEDIN) Starter kits will be developed to step-by�step support the creation of new professional and sustainable networks where gaps were identified (T6.1). The kits will build upon the existing “Open Science Community Starter Kit” and at least two kits will be developed: a generic network started kit, and a dedicated kit for data stewards networks.

T6.3 Harmonisation and fostering the creation of new professional networks (M1-36, TU-Delft/NHMW ). This task will animate the already existing professional networks and foster the creation of new ones, thus harmonising them.

T6.3.1 Data Stewards networks through national Competence Centers Competence Centres in the Skills4EOSC Network for data stewards based on the starter kit. Competence Centres will be responsible for long-term sustainability of these networks. The networks will be harmonised under the umbrella of the RDA Professionalising Data Stewardship IG.

T6.3.2 Open Science Communities across Europe Open Science Communities (OSCs) create bottom-up fora for researchers and professionals at local universities to foster uptake of Open Science practices. Thus, OSCs are paramount to building and sustaining the EOSC-ready digitally skilled workforce. Universities will be supported in animating OSCs through the Starter Kit. Coordination framework and sustainability mechanisms will be developed based on the governance and infrastructure already built by the International Network of Open Science and Scholarship Communities (INOSC).

T6.3.3. Thematic networks. In addition to facilitating the creation of networks for researchers and professionals, thematic communities will be activated to stimulate the uptake of FAIR practices. FAIR Data for AI and FAIR Data for Health and Technology will be sustained by 4TU.ResearchData. The Museum Data Curator Network will be overseen by NHMW.

• For FAIR Data for AI: Desk research will be conducted to scope existing FAIR data practices in AI research, to profile community leaders and to identify key challenges. Subsequently, a writing sprint will be organised with the AI communities to explore the concepts of applying FAIR principles in Artificial Intelligence research. The outcome will be a “Top 10 FAIR Data Things for Artificial Intelligence”.
• For FAIR Data for Health and Technology: A network for those interested in making health technology data FAIR will be created. Work will involve identifying and evaluating the current FAIR data practices. A gap analysis will reveal areas for improvement which will be translated into published recommendations on improving the FAIRness of health technology data.
• The Museum Curator Network for FAIR data will facilitate the opening up of countless, non (fully) digital objects. The museum data curator network will advocate the spirit of openness, integrate the relevant multidisciplinary standards and support the community in professionalising FAIR data curation.

T6.4.Fellowship programme (M1-36, TU-Delft). To furtherstimulate life-long learning between (aspiring) data stewards acrossinstitutions, 3-monthslong fellowship programmes will be established (with dedicated mentorship). To incentivize the uptake of the programme, the mentor at the receiving institution and the visiting fellow will receive matching funds to support their participation in the scheme. There will be two open calls organised during the course of this project. Graduates will be encouraged to join the relevant professional networks (T6.3). In addition to matching funding requirement from the outset, there will be dedicated efforts to ensure long-term sustainability, including the investigation of possibilities for embedding within European exchange programmes (WP8, T8.3). The programme will be open also to EU widening countries.

Länkar och listor

Huvudsida: Skills4EOSC

Lista: Objectives

Lista: Arbetspaket (Work packages, WP)

Lista: Organisationer och stakeholders

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