FAIRsFAIR training resources


FAIRsFAIR contribution to Data Stewardship & professionalisation: the Competence Centre

In line with the EC Expert Group on FAIR Data recommendations to professionalise data science and stewardship and to coordinate, systematise and accelerate the pedagogy and availability of training for data skills, data science and data stewardship, FAIRsFAIR is addressing the development of a FAIR Data Competence framework. This is meant to include FAIR data competences to be acquired through higher education, e.g. data science programmes in data-intensive and data-driven disciplines (all three cycles), and for graduates continuing to work as professionals in FAIR data management (e.g. data stewards, research infrastructure managers).

The expected competence framework will be targeted at institutions offering FAIR and Data related courses or aiming to do so. This will enable higher education institutions to address FAIR related competences already during study experiences, e.g. at Bachelor, Master or PhD level. FAIRsFAIR will also ‘translate’ the competence framework into materials usable by Higher Education Institutions (HEIs); in this way the FAIR model courses and curricula will be refined and improved. 

The competence centre will comprise a central ‘core’, based on the human resources of the FAIRsFAIR project, plus tailored knowledge base, growing throughout the project and feeding into each other, focused on specific communities.


FAIRsFAIR Training activities

FAIRsFAIR training activities include mapping data science programmes at universities and integrating FAIR data skills into them. Creating synergies with existing competence frameworks for data scientists, data stewards and other relevant professions, developing a FAIR data competence framework which can be integrated into those on different education levels, developing education and training material (e.g. model courses and curricula) for university programmes, and capacity building for universities to apply the material (e.g. for instance in doctoral education) are also envisaged.


FAIRsFAIR contribution to CODATA/RDA Schools

FAIRsFAIR project is building on the successful CODATA/Research Data Alliance schools model, which provides early career researchers with foundational data science skills in an established and validated two-week curriculum. FAIRsFAIR is rolling out this model across Europe, propagating the skills by “training the trainers”, and supplying francised modules which can be tailored for a particular community. FAIRsFAIR is also exploring how this could be included as an element in core university provision and the potential for formal accreditation.

 


 

Browse FAIRsFAIR training events and activities

 

Training

2020 CODATA-RDA School of Research Data Science

Location: 
Virtual

This year the CODATA/RDA Summer School will be going online between 31 August and 11 September!  There will be no face-to-face School at Trieste in 2020. 

Training

CODATA-RDA Summer School for Research Data Science

Location: 
Trieste, Italy

Part of the FAIRsFAIR Initiative, the 2019’s edition of the CODATA-RDA Summer School was dedicated to data stewardship and was held in Trieste, Italy in August 2019.