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Creating a data management framework


Creating a data management plan Guide

This comprehensive guide is for research institutions which are intending to assess the capability maturity of their current infrastructure supporting the management of institutional research data assets.

This Guide covers:

An overview of what elements institutions need to consider when planning for an institutional approach to data management. It also has an in depth analysis of the Capability Maturity Model which can be used to develop an institutional Data Management Framework:

  • five elements of data management capability: Policies and procedures, IT infrastructure; support services, managing metadata, managing research data
  • assessed across 5 levels of maturity: initial, development, defined, managed, optimised
  • practical checklists for assessing capability maturity:

Key messages:

  • Effective data management is best achieved through teamwork and collaboration between all areas of the institution which are involved in research data management.
  • Each organisation should determine where on the model it wants to be: not all organisations will seek to attain Level 5 (Optimised) in any, or all, of the 5 elements.
  • The Data Management Framework Capability Maturity Model (CMM) used in the Guide can act as gap analysis:
    • assessing current levels of data management capability and
    • identifying areas to enhance and extend data management capability.
  • There is the expectation that for a framework to be successful there will be:
    • appropriately defined roles and responsibilities
    • defined and promulgated standards
    • adequate resources – financial, staffing and equipment
    • appropriate skills across all staffing groups.

Creating a data management plan Guide