This repository contains the material developed for the Australian Research Data Commons' FAIR Data 101 virtual course which was run twice in 2020. This material now stand as self-guided from version 3, last updated in June 2021.
FAIR stands for Findable, Accessible, Interoperable and Reusable.
Making research data more FAIR provides a range of benefits to the wider research community by enabling future researchers to publish, share, cite and reuse research data. The FAIR Principles put specific emphasis on enhancing the ability of machines to automatically find and use the data, in addition to supporting its reuse by individuals. The FAIR Principles are aspirational and generic.
The third version of this online course stands as a self-guided material. The total time commitment for participants is minimum 6 hours, only activities and quizzes, and optional 12 extra hours to watch presentation and Q&A discussions. Read the short description of contents and how the course can be run in the FAIR-101-v3.
The second version of this online course was delivered between 7 September to 2 October 2020. The total time commitment for participants was 12 hours over 4 weeks. Read the short description of contents and how the course can be run in FAIR-101-v2.
The first version of this online course was delivered between 11 May to 26 June 2020. The total time commitment for participants was 16 hours over 8 weeks. Read the short description of contents and how the course can be run in FAIR-101-v1.
- 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
The FAIR Data 101 materials are stored in au-research/FAIR-data-101-training GitHub repository. Every effort is made to ensure things and activities remain current, so please check out how to contribute if you have any suggestions or corrections to submit.
All individuals partaking in this course are encouraged to follow the ARDC's Course Code of Conduct, inspired by the Carpentries' Code of Conduct.
All content of the ARDC FAIR data 101 is licensed under the Creative Commons Attribution 4.0 International (CC BY 4.0) licence.