What is a data management plan?

A data management plan is a document that clearly sets out out how you will collect, store, use, govern, and exploit data for a project, process, or activity.

Who is this canvas for?

This data management canvas has been developed based on experience working with projects in the PFER programme. As such, it is tailored to energy system use cases and uses those use cases to form the examples, but the principles are industry agnostic and could be applied across multiple sectors.

Why do I need this canvas?

A data management plan is used to manage your data like you would an asset. If managed correctly, data can be a valuable asset, delivering fascinating and useful insights. Manage it incorrectly, and data can be confusing, contradictory, or more trouble than it’s worth. Data management plans are used to make sure data collection, use, and publication is as efficient and robust as possible to get the maximum value for your project.

How should I use this canvas?

Read it through first and familiarise yourself with its content. Find a group of people in your project that will need to be involved in either developing or reviewing the data management plan. Sometimes it will be helpful to deviate from the process that we have set out. The key thing is to think carefully and critically about your data, using the process and questions here as a starting point. It is quite normal, and expected, that you will approach the task iteratively, adding more detail and advancing your thinking each time.

Why did you develop this canvas?

Some of the common challenges ESC has identified are:

• Multi-party consortia will be less able to understand and benefit from their research if they don’t have a unified approach to data management.
• Questions such as what data, where to store it, how it’s kept up to date, and how it’s governed are all simple questions that don’t start out with common answers.
• Not having common answers to data questions leads to data silos, which inhibits the use and dissemination of the data – in a research context this can impair learning and potentially the delivery of the product or service that is the subject of the research.
• GDPR challenges become unmanageable as the ‘right to be forgotten’ is not implementable in a systematic way.

Most projects involve multiple partners. Your data management plan will need buy-in from all of them, especially where partners must co-operate to derive value from the data that is available. It can help to involve all those stakeholders in your discussions – either initially, or as you iterate.

What can I use this canvas for?

Using this data management canvas, you can tackle all the above issues in a way that your stakeholders can see and support. You may also be able to use it to prove further value of your project. Following this process will help you to identify important aspects of your plan, and to work with data in a way that meets your overall project aims and objectives. By recording your thinking Energy Data Management Canvas as you go and the answers to key questions, you will find that documenting your data management plan is easier too.

Why should I use this canvas in particular?

You don’t have to stick to just this canvas! There are other guidelines that will help you to develop a data management plan to support a project proposal or request for funding. However, this data management canvas covers the whole lifecycle of the project and goes into detail about often overlooked factors such as the value of data, stakeholder needs and detailed governance principles.

What should I do after I’ve completed my data management plan?

Once you have produced a data management plan, it is recommended that you consult the Energy Data Best Practice guide to understand how you can leverage the value of your data across the wider energy industry, and beyond, by applying the Energy Data Taskforce principles and following its recommendations.

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