Rising to the Occasion: Learnings from 9 RDM Self-Evaluation Workshops

Dr Nichola Burton1, Mr Keith Russell2

1Australian Research Data Commons, Perth, Australia
2Australian Research Data Commons, Melbourne, Australia

Effective research data management (RDM) requires coordination across multiple research-supporting units in an institution. These units often have different focus and goals, and organisational structure can make coordination difficult.

The DCC’s Research Infrastructure Self-Evaluation (RISE) framework provides a model for assessing the maturity of an institution’s RDM policies, procedures and services across the entire research data lifecycle. ARDC has used this framework (adapted to the Australian context) to run self-evaluation workshops at nine Australian research institutions which brought together representatives from all research-supporting units and academics. We provided each institution with a report reflecting the self-assessed maturity of the institution across the RISE indicators, as well as discussion notes capturing issues and points of agreement and disagreement within the institution.

Participating institutions found the exercise useful in promoting intra-institutional collaboration and identifying service gaps, with several incorporating the reports into the development of their RDM strategies. The aggregated self-assessments and common issues and discussion points give a picture of current RDM capability across the participating institutions.


Bio to come

Walk Before You Run: Research Data Maturity Experiences

Ms Yvette Wharton1, Mrs Laura Armstrong1, Dr Dharani Sontam1, Professor Mark Gahegan1, Mr Sasenka Abeysooriya3, Keith Russell2

1University Of Auckland, Auckland, New Zealand
2Australian Research Data Commons, Melbourne, Australia
3The University of Queensland, Brisbane, Australia

Research data is a valuable asset and there is an increasing awareness of the need to enable researchers and institutions to manage and share their research data across the research data lifecycle and align with international best practice, including Findable, Accessible, Interoperable, Reusable (FAIR) and Collective Benefit, Authority to Control, Responsibility, Ethics (CARE) data principles. However, many institutions are struggling with the ‘growing pains’ of increasing their research data management maturity.

This 60 minute BoF will include a series of short presentations in which we will offer highlights and insights from our experiences (at different stages on the journey) in our respective organisations, assessing current maturity, understanding the target future state, and planning an incremental path forward.

We will then facilitate an open discussion to draw input from the audience regarding the wider experiences  including maturity models and frameworks, methodologies for gathering data, and thoughts on engaging  researchers and organisations to enable shared growth on the data maturity journey.

This BoF is targeted at all those interested and involved in managing research data, and assessing data governance, processes, tools and policies, including researchers, research data stewards, research support staff, institutional administrators, enterprise architects, eResearch directors, and academic engagement or research librarians.


Yvette Wharton is the eResearch Solutions Lead at the Centre for eResearch, University of Auckland. https://orcid.org/0000-0002-6689-8840

Laura Armstrong is a Senior eResearch Engagement Specialist at the Centre for eResearch, University of Auckland  https://orcid.org/0000-0003-2370-3924

Dharani Sontam is an eResearch Engagement Specialist at the Centre for eResearch, University of Auckland. https://orcid.org/0000-0001-7616-5088

Mark Gahegan is director of the Centre for eResearch at the University of Auckland. https://orcid.org/0000-0001-7209-8156

Sasenka Abeysooriya is a Senior Strategic Adviser for Data Strategy and Governance at The University of Queensland (UQ) https://orcid.org/0000-0003-2344-458X

Keith Russell is Engagements manager at the Australian Research Data Commons https://orcid.org/0000-0001-5390-2719

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