OECD Report - Building digital workforce capacity and skills for data-intensive science (2020)
As a lead contributor to the OECD's Building Digital Workforce Capacity and Skills for Data-Intensive Science (2020) report, Dr Michelle Barker outlines in this presentation the goal of the report, i.e. to make recommendations to policy makers on how to facilitate the digital workforce...
Keywords: international skills initiatives, skills, training, OECD, EOSC, Capability building, Skills uplift, skills development, digital skilled workforce, training material
OECD Report - Building digital workforce capacity and skills for data-intensive science (2020)
https://zenodo.org/records/4289356
https://dresa.org.au/materials/oecd-report-building-digital-workforce-capacity-and-skills-for-data-intensive-science-2020-a456ae97-9241-4fc6-b7f9-57c201479317
As a lead contributor to the OECD's Building Digital Workforce Capacity and Skills for Data-Intensive Science (2020) report, Dr Michelle Barker outlines in this presentation the goal of the report, i.e. to make recommendations to policy makers on how to facilitate the digital workforce capacity needed for data-intensive science, based on analysis of best practice.
The presentation highlights:
- Digital workforce capacity and COVID19: the importance of digital skills, the need for shared access to open data, software and code, and the shortfall in skills to enable a comprehensive response to such emergencies
- The ongoing need for a digital skilled workforce for data-intensive science
- Five focus areas in the report include:
1. Enablers for digital workforce capacity development
2. Defining needs: digital skills, frameworks and roles
3. Provision of training
4. Community development
5. Career paths and reward structures - Recommendations for actors incl. universities, national or regional governments
contact@ardc.edu.au
Barker, Michelle (orcid: 0000-0002-3623-172X)
international skills initiatives, skills, training, OECD, EOSC, Capability building, Skills uplift, skills development, digital skilled workforce, training material
ARDC FAIR Data 101 self-guided
FAIR Data 101 v3.0 is a self-guided course covering the FAIR Data principles
The FAIR Data 101 virtual course was designed and delivered by the ARDC Skilled Workforce Program twice in 2020 and has now been reworked as a self-guided course.
The course structure was based on 'FAIR Data in the...
Keywords: training material, FAIR data, video, webinar, activities, quiz, FAIR, research data management
ARDC FAIR Data 101 self-guided
https://zenodo.org/records/5094034
https://dresa.org.au/materials/ardc-fair-data-101-self-guided-2d794a84-f0ff-4e11-a39c-fa8ea481e097
FAIR Data 101 v3.0 is a self-guided course covering the FAIR Data principles
The FAIR Data 101 virtual course was designed and delivered by the ARDC Skilled Workforce Program twice in 2020 and has now been reworked as a self-guided course.
The course structure was based on 'FAIR Data in the Scholarly Communications Lifecycle', run by Natasha Simons at the FORCE11 Scholarly Communications Institute. These training materials are hosted on GitHub.
contact@ardc.edu.au
Stokes, Liz (orcid: 0000-0002-2973-5647)
Liffers, Matthias (orcid: 0000-0002-3639-2080)
Burton, Nichola (orcid: 0000-0003-4470-4846)
Martinez, Paula A. (orcid: 0000-0002-8990-1985)
Simons, Natasha (orcid: 0000-0003-0635-1998)
Russell, Keith (orcid: 0000-0001-5390-2719)
McCafferty, Siobhann (orcid: 0000-0002-2491-0995)
Ferrers, Richard (orcid: 0000-0002-2923-9889)
McEachern, Steve (orcid: 0000-0001-7848-4912)
Barlow, Melanie (orcid: 0000-0002-3956-5784)
Brady, Catherine (orcid: 0000-0002-7919-7592)
Brownlee, Rowan (orcid: 0000-0002-1955-1262)
Honeyman, Tom (orcid: 0000-0001-9448-4023)
Quiroga, Maria del Mar (orcid: 0000-0002-8943-2808)
training material, FAIR data, video, webinar, activities, quiz, FAIR, research data management