FAIR Data 101 express
Welcome to the Australian Research Data Commons’ FAIR Data 101 express course v2! DOI: 10.5281/zenodo.4414980
The course is aimed at individuals working with or expecting to work with data as researchers, publishers, librarians, or in research support, especially those seeking to develop their skills in managing FAIR data in practice and to understand the tools that can support them in doing this.
Description
The second version of this online course was delivered from 7 September to 2 October 2020 and advertised through ARDC channels. Participant’s time commitment per week is designed to be three hours a week over four weeks (a total of 12 hours).
The course is divided into one week modules, for each of the four foundational FAIR principles:
It is also combined with one Q&A webinar per week with an expert panel from ARDC staff and partner organisations:
- FAIR Data 101 Express: Findable Q&A
- FAIR Data 101 Express: Accessible Q&A
- FAIR Data 101 Express: Interoperable Q&A
- FAIR Data 101 Express: Reusable Q&A
How to run this course
Each module ran for 1 week, and consisted of
- 2 pre-recorded webinars (hosted on ARDC’s YouTube channel)
- Activity sheet (hosted on GitHub website)
- Quiz (Survey Monkey)
- 1 live Q&A webinar with an expert panel (GoToWebinar)
- FAQ document built from questions arising in the post webinar survey.
The Slack workspace was used again; and was kept open for a further two weeks after the end of the course.
Each module should take around 3 hours to complete. Total of 12 hours spread in 4 weeks.
All individuals partaking in this course are encourage to follow the ARDC’s Course Code of Conduct, inspired by the Carpentries’ Code of Conduct.
Credits
- Liz Stokes
- Matthias Liffers
- Nichola Burton
- Natasha Simons
- Keith Russell
- Siobhann McCafferty
- Richard Ferrers
- Steve McEachern
- Melanie Barlow
- Catherine Brady
- Rowan Brownlee
- Tom Honeyman
- Maria del Mar Quiroga
- Asher Vennel
Licence
All content of the ARDC FAIR data 101 is licensed under the Creative Commons Attribution 4.0 International (CC BY 4.0) licence.
How to cite this work
Stokes, Liz, Liffers, Matthias, Burton, Nichola, Simons, Natasha, Russell, Keith, Siobhann McCafferty, … Vennel, Asher. (2020, November). ARDC FAIR data 101 virtual course training materials (Version v2.0). Zenodo. http://doi.org/10.5281/zenodo.4414980