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.

DOI: 10.5281/zenodo.4414979

Licence: Creative Commons Attribution 4.0 lower case

Contact: ARDC Contact us: https://ardc.edu.au/contact-us/

Keywords: training material, FAIR data, research data, data management, FAIR


Additional information

Target audience: PhD student, Post-doc / Fellow, Academic, Professional (research-related)

Resource type: Presentation, Quiz, Learning Activity

Version: 3

Status: Active

Subsets: https://github.com/au-research/FAIR-data-101-training/tree/v3.0

Learning objectives:

*Discuss the concept of FAIR data and its application in research
*Articulate drivers, barriers, challenges and opportunities for enabling FAIR data
*Refer to hands-on experience with techniques, services and tools (particularly those offered by ARDC) for making data FAIR
*Identify best-practice examples and benefits of FAIR data management

Date created: 2021-07-01

Date published: 2021-07-13

Authors: Liz Stokes, Matthias Liffers, Nichola Burton, Paula A. Martinez, Natasha Simons, Keith Russell, Siobhann McCafferty, Richard Ferrers, Steve McEachern, Melanie Barlow, Tom Honeyman, Maria del Mar Quiroga

ARDC FAIR Data 101 self-guided https://dresa.org.au/materials/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. ARDC Contact us: https://ardc.edu.au/contact-us/ training material, FAIR data, research data, data management, FAIR phd ecr researcher support