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Collection Governance: Code of Practice

Please note, the Collection Governance pages are still available for your reference but the consultation has now been closed. Please refer to the Codes of practice in the Data Landscape Steering Group for the most up-to-date information on data governance.


The Code of Practice for HE data collections (from hereon in referred to as the supply-side code of practice) was first issued to providers in 2014. It was created by the four UK HE funding bodies and HESA and it drew heavily on the National Statistics Code of Practice.

The supply-side code of practice is the source material for creating two new artefacts: an overarching set of data governance goals and principles and the code of practice for data collectors. This approach ensures consistent coverage of all those involved in the production, processing and consumption of data in the HE sector.

Data governance goals and principles

The data governance goals and principles are designed to operate in a consensual data governance environment. They have been formed by merging existing principles from published guidance with best practice activities sourced from both the HE and other sectors and the outputs of the Higher Education Data and Information Improvement Programme (HEDIIP) ‘New Landscape’ project. All parties within the scope of the data governance goals and principles are considered as either demand (‘customers’ of the data) or supply (‘providers’ of the data’).

In practice, some organisations will occupy demand- and supply-side roles at different times and for different reasons. However, for pragmatic purposes most organisations will predominantly fall into one of the two categories.

These goals and principles are an encapsulation of what it means to be a responsible organisation operating with data in the HE sector. There are benefits to the individual organisation – be that on the demand- or supply-side – and to the sector as a whole in pursuit of the goals of harmonisation, rationalisation and a determination to minimise burden.


The data governance goals and principles covers the best practice for the management of data production, processing, and consumption, in a complex landscape.

They are monitored and bounded by:

  • The Data Landscape Steering Group (DLSG) acting as an oversight body to ensure the data governance goals and principles are well defined in the individual codes of practices, monitoring adherence to these goals and acting as an arbitration body in the case of a breach.
  • Data and other relevant regulations for those participating in the production, processing and consumption of that data.
  • Best practice data management and data governance.
  • The sector governance process which manages change to shared data.

Goals for sector-wide data governance

These goals and principles are designed to encourage demand- and supply-side to work together in collecting data at the minimal level of possible burden to achieve the right level of quality, measured by fitness for purpose.

Together, they set out, for all parties, the outcomes of a sector-wide consensual data governance approach.

Enable better outcomes with data

What does this mean: The right data, at the right time and at the right quality, in support of well stated outcomes understood by all parties.

Improve operational efficiency

What does this mean: Well governed data reduces confusion about how data needs to be produced and reduces time-consuming manual intervention.

Minimise burden

What does this mean: Requirements are clearly specified. Rigorous impact analysis and different solution options mitigate the risk of unneeded burden. Net burden considers both the cost and value of any change.

Rationalise and harmonise the landscape through best practice.

What does this mean: The governance process is founded on shared processes, models, definitions and guidance. It fairly addresses all parties’ needs to ensure data collections are managed in the most efficient and simple way possible.

Visibly demonstrate adherence to sector-wide consensual governance

What does this mean:  All data stakeholders will participate in a fair, transparent and informed manner to ensure shared understanding of requirements and outcomes

Principles for sector-wide data governance

To support these goals, three principles – sourced from supply-side code of practice – should be consistently applied by all parties. While the individual codes of practice may differ for demand and supply, the principles inform and bound this best practice.

These principles are the responsibilities of all involved in sector data participating in a consensual governance process.


To be clear on the source, meaning and use of data, the necessary quality expectations for that data and the transparent production, processing and consumption of that data.

Transparency of use case and processing is vital to ensure data is subjected to the necessary level of quality assurance during collection and supply, and that the onward uses of the data can be subject to sufficient levels of scrutiny.


To engage in the sector-wide governance process without organisational, political or personal interest in the production, processing and consumption of that data


To demonstrate robust and repeatable processes in the production, processing and consumption of that data so that it is auditable and defensible.