Following ongoing discussion as part of the RDCC and the ARDC's Institutional Underpinnings Project, four new projects were support by the IU Extension Project.
Two projects led by UNSW Sydney focussed on key challenges discussed as part of the RDCC namely;
Business reporting and intelligence, and;
Data retention and dispoal.
Business Intelligence and Reporting of Research Data
Modern research institutions have a growing data challenge, and a key step in addressing it is knowing what institutions hold. The ARDC-funded, Institutional Underpinnings Extension Project: RDM Business Intelligence and Reporting provides a case study on developing an approach to the systematic characterisation and reporting of research data properties to enable strategic decision-making.
Jung, D., Haythornthwaite, A., Mertin, A., Wilkinson, J. M., Burton, N., Soo, A.-L., Francis, R., Stevens, F., Cho, K. L. (Jacky) ., & Betbeder-Matibet, L. (2023). Business Intelligence and Reporting of Research Data. Zenodo. https://doi.org/10.5281/zenodo.10076883
Retention and Disposal of Research Data: from current to best practices
Modern research institutions are grappling with the indefinite retention of an uncontrolled expansion of uncurated digital content associated with research activities. To address that challenge, the Institutional Underpinnings Extension Project "The Retention and Disposal of Research Data - Confirming Obligations, Establishing Practice", has identified decision points related to the retention and disposal of data that arise while undertaking research and investigated the best practices around those decision opportunities. Decisions to retain or dispose of data depend on knowing the properties of the data.
Jung, D., Haythornthwaite, A., Mertin, A., Lynn, H., Wilkinson, J. M., Burton, N., Soo, A.-L., Francis, R., Stevens, F., Cho, K. L. (Jacky) ., & Betbeder-Matibet, L. (2023). Retention and Disposal of Research Data: from current to best practices. Zenodo. https://doi.org/10.5281/zenodo.10076891
An Australian Research Data Growth Rate
After the completion of the 2021 Macro View of Australia’s research data demonstrated that establishing growth rates based on historical data volumes from research organisations proved difficult, the Macro View 2022 was initiated. With the help of research organisations across Australia, the 2022 Macro View of Australia’s research data has estimated an average annual growth rate of ~22% across the sector.
A Macro View of Aotearoa New Zealand’s Research Data
Using the the 2021 Australian Macro View as an example, the National eScience Infrastructure (NeSI) adapted the methodology and characteristics of interest to engage research organisations across Aotearoa New Zealand. Their first every estimate of the volume research data in Aotearoa New Zealand is 45PB in Dec 2022.
Soo, Ai-Lin; Betbeder-Matibet, Luc; Francis, Rhys (2023). THETA Presentation A first Macro View of Australian Research Data (video). https://echo360.net.au/media/2e907d59-3263-401b-af97-8fc83fe4bc78/public
Soo, Ai-Lin; Betbeder-Matibet, Luc; Francis, Rhys (2023). THETA Presentation A first Macro View of Australian Research Data (video). https://echo360.net.au/media/2e907d59-3263-401b-af97-8fc83fe4bc78/public
Rye, Claire; Jones, Nick; Soo, Ai-Lin; Betbeder-Matibet, Luc; Francis, Rhys (2023). Can we characterise Aotearoa New Zealand's research data at scale. eResearch New Zealand.pptx. The University of Auckland. Presentation. https://doi.org/10.17608/k6.auckland.22696978
Soo, Ai-Lin; Quenette, Steve; Francis, Rhys (2022): Research Data Culture Conversation - A Macro View of Retained Australian Academic Research Data. Monash University. Report. https://doi.org/10.26180/20235570
Soo, Ai-Lin; Francis, Rhys; Wilkinson, Max; Betbeder-Matibet, Luc; Bonnington, Paul; Abramson, David; et al. (2022). Characterising Australia's Experience with Research Data at Scale. Monash University. Presentation. https://doi.org/10.26180/21454719
Soo, Ai-Lin; Burton, Nichola (2022): The Macro-View: Research Data and Researcher Files. Monash University. Presentation. https://doi.org/10.26180/21454716
Soo, Ai-Lin; Francis, Rhys; Quenette, Steve; Wilkinson, Max; Kemp, Carina; Walsh, Carmel; et al. (2022): eRA 2021 BoF - Supporting data life cycles at the macro scale. Monash University. Presentation. https://doi.org/10.26180/21068719
Soo, Ai-Lin; Francis, Rhys; Quenette, Steve; Betbeder-Matibet, Luc; GIUGNI, STEPHEN; Abramson, David; et al. (2022): RDA Poster - Developing an Effective Research Data Culture (RDCC). Monash University. Poster. https://doi.org/10.26180/21068620
In response to these discussion, the Australian Research Data Commons (funded under Australia’s National Collaborative Research Infrastructure Strategy) has established a program of work. This new program, working through 2021 and 2022, aims to develop a joint framework between Australian Universities addressing the issues set out here.
On June of 2020, the RDCC published two papers on an effective and affordable research data culture.
Research Data Culture Conversation - Paper 1: “A Summary of the Challenges”
Soo, Ai-Lin, Janke, Andrew, Betbeder-Matibet, Luc, Francis, Rhys, Giugni, Stephen, & Quenette, Steve. (2020). Research Data Culture Conversation - Paper 1 "A Summary of the Challenge". Zenodo. https://doi.org/10.5281/zenodo.3887434
Research Data Culture Conversation - Paper 2: “A Development Response”
Soo, Ai-Lin, Janke, Andrew, Betbeder-Matibet, Luc, Francis, Rhys, Giugni, Stephen, & Quenette, Steve. (2020). Research Data Culture Conversation - Paper 2 "A Development Response". Zenodo. https://doi.org/10.5281/zenodo.3887399
Soo, Ai-Lin; Francis, Rhys; Quenette, Steve (2022): eResearch Australasia 2019 An Effective and Affordable Research Data Culture. Monash University. Presentation. https://doi.org/10.26180/20782624
Soo, Ai-Lin; Francis, Rhys; Quenette, Steve (2022): 2019 eResearch Australasia Data Summit RDCC Institutional Directions. Monash University. Presentation. https://doi.org/10.26180/18516236
Francis, Rhys; Winton, Lyle; WEATHERBURN, JAYE; Connell, David; Ennor, Sandra (2022): eRA 2018 TURNING BIG SHIPS (DATA) ON A DIME CHANGE MANAGEMENT AND DATA SENTENCING. Monash University. Presentation. https://doi.org/10.26180/20780728