23 (research data) Things
23 (research data) things is a set of training materials exploring research data management. Each of the 23 things offers a variety of learning opportunities with activities at three levels of complexity:
- Getting started
- Learn more
- Challenge me
All resources used in the program are online...
Keywords: research data management, training material
23 (research data) Things
https://zenodo.org/records/3955524
https://dresa.org.au/materials/23-research-data-things-793872d2-c221-4cd6-91be-11a313c74b78
23 (research data) things is a set of training materials exploring research data management. Each of the 23 things offers a variety of learning opportunities with activities at three levels of complexity:
* Getting started
* Learn more
* Challenge me
All resources used in the program are online and free to use and reuse under a Creative Commons Attribution 4.0 International licence. You could use all of them as a self-paced course, or choose components to integrate into your own course.
The 23 things are designed to build knowledge as the program progresses, so if you’re new to the world of research data management, we suggest you start with things 1-3 and then decide where you want to go from there.
These materials supported an international community-based training program delivered in 2016 by the Australian National Data Service.
This release migrates these materials to a GitHub repository for continued maintenance. Some updates were made to material that was outdated.
We welcome contributions and suggestions via GitHub Issue or Pull Request.
contact@ardc.edu.au
Liffers, Matthias (orcid: 0000-0002-3639-2080)
Stokes, Liz (orcid: 0000-0002-2973-5647)
Burton, Nichola (orcid: 0000-0003-4470-4846)
Kelly, Andrew (orcid: 0000-0002-5377-5526)
Honeyman, Tom (orcid: 0000-0001-9448-4023)
Brownlee, Rowan (orcid: 0000-0002-1955-1262)
Levett, Kerry (orcid: 0000-0001-5963-0195)
Brady, Catherine (orcid: 0000-0002-7919-7592)
research data management, 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
Principles Aligned Institutionally-Contextualised (PAI-C) RDM Training
This GitHub repository contains resources for an institution to contextualise a principles-based RDM training with its institution's research data management policies, processes and systems.
The adoption of PAI-C across institutions will contribute to a common baseline understanding of RDM...
Keywords: PAI-C, Training, Data Management
Principles Aligned Institutionally-Contextualised (PAI-C) RDM Training
https://github.com/Adrian-W-Chew/PAI-C-RDM-Training
https://dresa.org.au/materials/principles-aligned-institutionally-contextualised-pai-c-rdm-training
This GitHub repository contains resources for an institution to contextualise a principles-based RDM training with its institution's research data management policies, processes and systems.
The adoption of PAI-C across institutions will contribute to a common baseline understanding of RDM across institutions, which in turn will facilitate cross institutional management of data (e.g. when researchers move between institutions, and collaborate across institutions).
Dr Adrian W. Chew (w.l.chew@unsw.edu.au)
Dr Adrian W. Chew
Dr Adele Haythornthwaite
Brock Askey
Dr Jacky Cho
Dr Anesh Nair
Dr Kyle Hemming
Iftikhar Hayat
Joanna Dziedzic
Janice Chan
Kaitlyn Houston
Linlin Zhao
Caitlin Savage
Jessica Suna
Dr Emilia Decker
Sharron Stapleton
PAI-C, Training, Data Management