Why?

Institutional issues

Research data management challenges | Researchers' requirements | Role of IT services

Subject-specific guidance

Humanities | Social sciences | Structural science | Engineering | Life sciences | Freshwater biology | Bio-imaging | Palaeoclimatic studies | 'Big science'

The effective management of research data is a core part of good research practice and can bring significant benefits in terms of more efficiently conducted research and avoiding the costly risk of data loss.

JISC have produced a number of requirement analyses to help clarify the reasons for improving the management of research data and the manner in which this needs to be achieved. Some take a broad view of institutional issues whilst others focused on subject-specific guidance for research data management.

JISC infoNet also have a range of generic resources which may be of use in helping develop the business case for investment in this area.

How?

Strategy and planning tools

Data management planning tool | Data management and curation strategy development tools | Data management recommendations | Draft data management plan

Research data management platforms

A two tier platform providing both local data management support and a route for archiving data
Platform for research data curation and sharing in freshwater biology
ICAT Lite compliant information model for both end user data management and archiving
Prototype research data management platform for life-science researchers
Database as a service platform for humanities researchers

A useful starting point when planning to improve the management of research data is to consider the requirements of relevant external bodies such as funders.

A number of toolkits exist designed to guide you through many of the required stages of forming and implementing a research data management project. These strategy and planning tools cover such areas as clarifying goals, assessing institutional assets and the creation of appropriate data management plans. These 'self-help' tools are augmented by a range of model data management plans and guidance for you to draw upon.

You can also draw upon the experiences of institutions who have developed a range of research data management platforms and software to help researchers manage their data.

Who?

Institutional guidance for researchers

University of Cambridge | University of Oxford | University of Glasgow | University of Edinburgh

'How to' guides

Best practice guide for researchers | How to appraise and select research data | How to licence research data | Review of the state of the art of the digital curation of research data

Subject-specific training materials

Humanities | Performance and visual arts | Archaeology and social anthropology | Health studies | Psychological studies | Social science, clinical psychology and geosciences | Biological imaging

As will be already evident, much of the emphasis of research data management is to provide the researcher themselves with the tools and techniques to manage their own data.

In support of this 'self-help' ethos a range of institutional guidance is available which researchers may well find useful, especially if new to the area.

Sector agencies and bodies such as the UK Data Archive and Digital Curation Centre have also produced extremely useful 'how to' guides to aide people in research or support posts but who may be new to data management and curation. A number of JISC projects have produced subject-specific training materials which are available for reuse and adaptation.

How much?

Costing

Fact sheet and user guide | Activity Model 'Lite' | Activity Model 'Detailed' | Activity-based costing tool for researchers in social sciences

Understanding how to model the full cost of research data management is a challenging area and one where best practice is still emerging. However, there are some sources of guidance focused around activity-based costing along with associated cost models which may prove useful.