Principles Aligned Institutionally-Contextualised (PAI-C) Research Data Management Training
This 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).
The University of New South Wales (UNSW) designed, developed and rolled out a Research Data Management (RDM) online training for Higher Degree Research (HDR) candidates in 2019. Overall, the majority of the 643 candidates who completed the online training were satisfied with its quality and found it helpful – For more information, see Chew et al. (2022).
Spring boarding off UNSW’s RDM training experiences, Bond University, UNSW and the University of Sydney undertook a joint project to develop and pilot test an RDM introductory educational/training experience for HDR candidates that targeted minimum RDM training outcomes/competencies, and contains the respective university’s materials/information on policies, processes and systems. For details of the PAI-C design and development process, see PAI-C Design and Development Approach.pdf
The principles-based introductory RDM training was developed using the minimum RDM competencies identified in the Institutional Underpinnings (IU) Framework (Support, Training and Guidance Element) - see https://ardc.edu.au/program/institutional-underpinnings/
Given that the PAI-C experience is built upon the jointly-agreed IU RDM framework principles, it holds the potential to function as an Australian-wide baseline RDM training. However, a baseline is always tentative, and must respond to changes in the RDM landscape (e.g., changes in legislation, technology, institutional risks/priorities, and researchers’ learning needs). Therefore, a gap identified in the original IU PAI-C project is on the maintenance/sustainability of this PAI-C Introductory/Baseline RDM training for the sector, including facilitating the adoption of the PAI-C training by new universities. As such, the IU PAI-C project was extended to 30 November 2023 to determine:
a. the scalability and replicability of the PAI-C RDM Training design and development process and;
b. a framework for sustaining an Australian-wide baseline RDM training.
The PA-C RDM Training design and development process outlines a 9-phase process from contextualisation to pilot testing to deployment on a university’s Learning Management System (LMS) see PAI-C Design and Development Approach.pdf). This process was adopted by five new universities (i.e., University of Canberra; Charles Darwin University; Curtin University; Deakin University; and Griffith University).
As of 30 November 2023, each of the five universities has an interactive contextualised PAI-C RDM training that they can deploy on their university LMS (e.g. Canvas, or Blackboard). Additionally, the feedback (n = 139), in terms of RDM knowledge gained and end-user experience, from pilot testing the interactive contextualised PAI-C were excellent. These outcomes achieved speaks to the scalability and replicability of the PAI-C RDM Training design and development process.
At the end of both project phases, eight universities across NSW, NT, QLD, VIC, and WA reviewed the PAI-C RDM content in detail through (1) internal stakeholder consultations at their universities, and (2) pilot testing of their interactive contextualised PAI-C RDM training with end-users. All universities agree that the content is sound and can be contextualised for their universities. This means that the PAI-C RDM content can function as a baseline RDM knowledge domain for the sector. All universities also agree that the process of contextualising the PAI-C content allowed them to see how overarching RDM principles are applicable to different universities, and to assist in the alignment of their respective policies, processes and systems in relation to RDM best practices.
Please contact Dr Adrian W. Chew (w.l.chew@unsw.edu.au) if you have any questions.
Dr Adrian W. Chew (w.l.chew@unsw.edu.au)
Dr Adele Haythornthwaite (adele.haythornthwaite@sydney.edu.au)
Brock Askey (baskey@bond.edu.au)
Dr Jacky Cho (k.cho@unsw.edu.au)
Dr Anesh Nair (anesh.nair@canberra.edu.au)
Dr Kyle Hemming (kyle.hemming@canberra.edu.au)
Iftikhar Hayat (iftikhar.hayat@cdu.edu.au)
Joanna Dziedzic (joanna.dziedzic@cdu.edu.au)
Janice Chan (janice.chan@curtin.edu.au)
Kaitlyn Houston (kaitlyn.houston@curtin.edu.au)
Linlin Zhao (l.zhao@deakin.edu.au)
Caitlin Savage (caitlin.savage@deakin.edu.au)
Jessica Suna (j.suna@griffith.edu.au)
Dr Emilia Decker (e.decker@griffith.edu.au)
Sharron Stapleton (s.stapleton@griffith.edu.au)
The top Yellow row for each section shows how the Principles version (bottom Green row) was contextualised for use at UNSW.
Click on this PAI-C Storyboard Link to access the storyboard. The content in the Principles version (bottom Green row) can be used/adapted (under the License) to create an introductory RDM training on a platform/medium that suits your needs.
Please note that the PAI-C storyboard is designed primarily for developing an online asynchronous training that can be deployed at scale.
This provides a 'look and feel' of the translation of the PAI-C Storyboard into an online module. This interactive version can be deployed on most Learning Management Systems (i.e. Blackboard, Canvas and Moodle).
Link to an example of an interactive PAI-C Section 1. Please note that UNSW reserves all rights to the images used in this example.
The Principles Aligned Institutionally-Contextualised (PAI-C) Research Data Management Training project received funding from ARDC Institutional Underpinnings Program.