Institutional Data Management Blueprint (University of Southampton)

Summary

On the occasion of the tenth anniversary of the Open Archives Initiative, the University of Southampton launched a project drawing on a decade of open-access repository initiatives at Southampton, with the aim of developing a coherent set of actions to establish an institutional and interdisciplinary roadmap.

The Blueprint combines two approaches: a bottom-up approach, based on researchers’ needs and designed to enable them to adopt best practices; and a top-down approach, intended to provide the institutional infrastructure and policies needed for those practices to be effective.

Promoting organizations

The Institutional Data Management Blueprint (IDMB) was led by the University of Southampton, with leadership from Engineering Sciences and support from internal units such as Library and iSolutions. The project was funded by JISC (UK) under the Managing Research Data programme, managed by Simon Hodson.

It also received external input through its steering group, which included organisations such as the Digital Curation Centre, the University of Oxford, and the National Oceanography Centre Southampton.

Objectives

The ultimate goal of the Institutional Data Management Blueprint (IDMB) project was to create a practical and viable institutional framework for research data management, supporting digital research practice at national and international levels.

To this end, the project set out to develop a whole-institution framework for research data management, based on an analysis of data management requirements across a representative set of disciplines with a diverse range of data types.

Beneficiaries and stakeholders

Through the project, it aimed to add value to the institution and the research community by providing:

A coherent data management strategy for a single institution.
A change-management strategy for open access to data.
The development of a cross-cutting skills base for research data management, including training for postgraduate students.
The preservation and curation of research data at the institutional level.
Support for best practices in research data workflows and datasets.
An analysis of the cost–benefit relationship of implementing the framework proposed by the project.

In addition, the project’s final report includes recommendations addressed to the wider community and, in particular, to JISC (Joint Information Systems Committee), the project’s funding body.

Results

The project’s initial findings report concluded that there was no coherent approach to data management, and that the existing business model was neither scalable nor sustainable to meet current and potential demand in a way that would support the university’s strategic objective of delivering research excellence.

It stated that, at that time, the situation of data management at the University of Southampton was similar to the state of high-performance computing at Southampton a decade earlier.

Accordingly, the report identified the need to increase data management capacity to help researchers achieve the University’s strategic goals.

The final report also describes the project’s immediate impact, suggesting that the foundations were in place to drive a cultural change in researchers’ attitudes towards institutional engagement.

The same report refers to a growing awareness within the institution itself of the need to develop a data management framework, laying the groundwork for future work.

It also notes that this immediate impact was evident among the institution’s senior leadership as well.

Challenges

In the project’s initial findings report, the main challenges for adopting better metadata management are described as:

Encouraging data tagging.
Adopting metadata schemes that are not overly burdensome.
Using usable tools for metadata assignment and import.
Automating metadata assignment.

In addition, the project’s initial phase highlighted some of the data management challenges faced by the institution, such as the diversity of data to be managed, which in turn spanned a wide range of management requirements.

On the other hand, the project’s final report acknowledges the cost involved in achieving fully effective data management, noting that the research lifecycle model is complex and requires an approach that can only be applied effectively through cooperation.

Interest and transferability

The project focused on developing a long-term, fully specified and costed solution for a single institution, drawing on open standards and service-oriented approaches.

Among the main expected outcomes of the project were:

The development of a plan for an institutional data management strategy for the next decade.
The development of an institutional data management plan based on an analysis of data management requirements and best practices.
An extensible, service-oriented enterprise architecture model for data management.
A 10-year business model roadmap.
A gap analysis report on best practices.
The delivery of workshops, training courses, a website, and reports to disseminate best practices.

Building on the established policy and within a service-oriented computing framework, the project explored and evaluated a pilot implementation plan for a whole-institution data model.

This plan could be integrated into existing research workflows and expand the potential of existing data storage systems, including those linked to national shared-services initiatives.