Collaborative Assessment of Research Data Infrastructure and Objectives (CARDIO)
The Collaborative Assessment of Research Data Infrastructure and Objectives (CARDIO) tool was developed through the JISC-funded Integrated Data Management Planning (IDMP) Toolkit and Support project.
CARDIO is a benchmarking tool for data management strategy development, typically applied at the departmental or research group level. The tool blends key aspects of the Cornell three-legged stool model, DAF, AIDA, DRAMBORA, and DMP and draws upon the legacy data within these tools to provide users with practical recommendations for improvement based on real-life examples.
CARDIO enables you to:
- collaboratively assess data management requirements, activity, and capacity at your institution
- build consensus between data creators, information managers and service providers
- identify practical goals for improvement in data management provision and support;
- identify operational inefficiencies and opportunities for cost saving;
- make a compelling case to senior managers for investment in data management support
Get involved!
If you'd like to test the CARDIO tool at your institution, please get in touch with us at info@dcc.ac.uk. We welcome your feedback and comments on the tool via cardio@dcc.ac.uk.
CARDIO does not aim to replace the individual toolkits – we firmly believe that each methodology and toolkit is valuable in its own right. CARDIO simply takes key aspects of these tools and repurposes their legacy data to make them more useful for this middle layer of strategic planning. Ultimately, CARDIO will help to ensure that there is greater understanding of researcher requirements and greater cohesion between institutional policies, departmental strategy, and actual research practice.
Support, integrated tools for improved data management
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SCARP Synthesis Study
SCARP Synthesis Study
Shedding light upon the diversity of scientific research is this DCC-commissioned report, based on SCARP and other case studies. Attitudes and approaches to data deposit, sharing, reuse, curation and preservation are investigated across a range of research fields and disciplines.
