Skip to 0 minutes and 0 secondsIn this lecture, we're looking at creating a data management plan. Now, your organisation should probably have some sort of formal documentation around data management policy or procedure that would be cascaded down from your digital or your information governance teams. So in order to create a data management plan we need to consider these organisational principles for data management first before you then go on to make a data management plan. So your organisational principles are likely to include elements such as an information asset register, how you deal with the sharing of data, and how you look to process or use that data, and obviously how you can keep it secure and safe.
Skip to 0 minutes and 49 secondsSo let's think of an example from the communications directorate, which looks at the directory of businesses. We'll want to look at the directory of businesses, the people involved in those businesses, and the directory of staff that's involved with them. You need to make sure that certain types of information are secure, and other types of information are shared, so that the directory has value, but you're not compromising personal integrity. So now we want to create a data management plan. You probably use a data management plan when you're specifically looking at a project or piece of work. And so it will be framed by the governance and strategies we just talked about.
Skip to 1 minute and 29 secondsAnd we'll want to make sure that our data management plan works for that project. And it will generally comprise six different elements. The first being data collection. Then we have the documentation of the data and the metadata, the ethics and legal compliance, how you plan to store and back up your data, your data curation and your open access to data, and any responsibilities and resources that form part of your data management plan. So, firstly, looking at data collection. You need to think about how you will get access to data. Are you creating new data for the purposes of the project itself? Or will you be taking data from other sources?
Skip to 2 minutes and 13 secondsSo how do you plan to get access to that data? How do you physically get the data from one system to another? Are you taking it in files, or are you going to download it over the internet, for example? And then you want to think about how you use that data, once it's collected, to move onto the rest of the project. And in thinking about how you're going to use data in the project, you'll look at elements such as versioning of that data, so that you can make sure that you understand how data works in different versions, and you can keep integrity of your data throughout.
Skip to 2 minutes and 51 secondsLooking at documentation and metadata, it's really important to make sure that you understand what the data is that you're using, and that you can describe it in a positive way. So you need to document all the data that's available, and look at areas, for example, of metadata-- and metadata means describing the data that you have. So it will be very important to clearly set out the data that you have, for example, what time period does it cover, or what geographical area does it cover. All these are vital components of metadata. From an ethics and legal compliance perspective, we need to make sure that we've got data that we're allowed to have.
Skip to 3 minutes and 29 secondsSo we need to have sign-off of that data once it's in the project and we're working with it, and we need to then understand how to keep that data secure, so that we do not lose personal data, because that's a big risk. Step four is around storage and backup of data. We need to know where we're going to keep our data, how we're going to store it. Are we going to store it, for example, on the cloud? How do we keep that secure? How long are we going to store the data for, after the end of the project as well? We need to be clear on that. And who has access to that data once it's stored?
Skip to 4 minutes and 5 secondsStep five is looking at data curation and access to the data. So what data must we retain in the course of the project, so we have contractual legal and regulatory purposes followed? And how we decide what other data to keep after the end of the project? Will you make some of your findings-- some of your data-- openly available so that other people can access it? And how will you make that data available so other people can access it? Will you put it on platforms online, such as open data portals? And finally, in a data management plan, we want to look at responsibilities and resources.
Skip to 4 minutes and 38 secondsWho is responsible for implementing the plan at each stage and ensuring it is reviewed and revised accurately? A data management plan is only as good as the policing of that plan, and making sure it's on track as originally set out.
Skip to 4 minutes and 57 secondsSo to end this, you need to make sure each partner is responsible for different elements, and people comply with that responsibility. Central to a data management plan is this idea of cultural buy-in. So everybody involved in the project needs to buy into the data management plan and buy into the ethos of managing data appropriately and securely. This will often mean there's a requirement for trading on, for example, data literacy, or specific components, such as dealing with personal data as well. This is to help us ensure we're getting the value throughout the project, but we're keeping our data safe and secure and used appropriately. So in this lecture, we looked at creating a data management plan.
Skip to 5 minutes and 40 secondsWe talked about the importance of having some sort of an organisational lead in this, so data management policies, and that is then reflected in the six steps of our data management plan.
Creating a data management plan
In this presentation, Steve discusses the process of creating a data management plan.
A template data management plan should be a core part of any organisation and have been cascaded down from the digital or information governance documentation.
The data management plan could be considered more specific and will consider the data management principles you have as an organisation. It will cover:
1. Data Collection
- How will you collect or generate data?
- How will you structure and name your folders and files?
- How will you handle versioning?
- What quality assurance processes will you adopt?
2. Documentation and metadata
- What information is needed for the data to be to be read and interpreted in the future?
- How will you capture / create this documentation and metadata?
3. Ethics and legal compliance
- Have you gained consent for data preservation and sharing?
- How will you protect the identity of participants if required? e.g. via anonymization
- How will sensitive data be handled to ensure it is stored and transferred securely?
4. Storage and Backup
- Will data be stored on the University network?
- How will data be transferred to the University network if it originates from another location?
- How will you ensure that collaborators, supervisors, or participants can access your data securely?
- Will data be stored on H:drive, i:drive, StrathCloud, or elsewhere?
5. Data Curation and Open Access to Data
- What data must be retained/destroyed for contractual, legal, or regulatory purposes?
- How will you decide what other data to keep?
- What data will be shared openly?
- When will you make the data available?
- How will data be preserved and shared?
- How will completed datasets be organised?
6. Responsibilities and Resources
- Who is responsible for implementing the plan, and ensuring it is reviewed and revised?
- Who will be responsible for each data management activity?
- How will responsibilities be split across partner sites in collaborative research projects?
- Will data ownership and responsibilities for RDM be part of any consortium agreement or contract agreed between partners?
© University of Strathclyde