The Data Governance Framework (DGF) has been developed by Helix to provide Monash researchers a framework with practical guidelines to better manage data in research activities and ensure it is translated into practice. It was endorsed by the Helix Steering Committee in November 2018.
What is Research Data Governance?
A Data Governance Framework is the articulation of how research data activities will be undertaken. Ethics, risk management, compliance and administration are all elements of governance.
Research data governance is a combination of systems and processes to protect and manage research data and broadly addresses the following questions:
- Who sets the rules
- What the rules are
- How rules are monitored
The DGF provides a value chain approach to research data management, with all the data activities required to answer the research question described in the seven value chain steps; from defining the purpose of the data through to reporting of the data.
Unlike other workflow models that describe “data management”, a value chain is not a linear, sequential aggregation of data activities, instead it recognises that there are often iterations and revisiting of many of these activities, particularly in longer studies. In this way a value chain describes what must be done, not the sequence in which it will be done.
Other key activities that cut across the value chain can also be included, like Data Sharing, Data Linkage, Data Transfer, Data Protection and Key Relationship Management.
The full paper is available on Monash Bridges: Data Governance Framework