Edited by Christopher Douce, Wednesday, 2 Oct 2024, 14:19
What follows is a set of notes from a professional development event by the library research support team, which took place on 8 Feb 2024 (which now feels like a long time ago).
This even was of interest for a number of reasons: I supervise some EdD research projects, I’ve been successful in gaining a small amount of seed funding, and I thought it might be useful in my role as an undergraduate project supervisor.
What is a data management plan?
A data management plan (DMP) is written at the start of the project, something that funders need to see. It describes what data you’re doing to collect, how data is going to be stored and secured, how will access be granted.
The exact requirements of a DMP may very between different funders. It is especially important if your research data is going to be uploaded into an archive. It is probably a good idea to write one even if one isn’t explicitly needed. Knowing how to do prepare a good DMP is an important research skill. Your plan can, of course, evolve as your project evolves.
Every project will have different data requirements. Will your project gather data from interviews, focus groups, or surveys? Different types of data may have different types of management requirements. What is the volume of the data, i.e. how much? How will data be collected? Also, where will your data come from? Will it come from other sources, such as databases or third parties? To help with the preparation of a plan, there is a tool called DMP online, provided by the library.
During this session we were led to an activity and asked the question: what do you think are your main data management challenges for your research project?
What follows are some headings which highlight what elements of data collection, storage and management which need to considered.
Storage and backup
Effective backups prevent accidental losses and deletions. Even if your data is backed up, you need to ensure that backups have integrity - in the sense that if you need to access or use them, you can do so without encountering difficulties or data loss.
When thinking storage and backup consider the size and complexity of your data, and where research is carried out. If you work in “the field” (amongst participants), consider the physical security of your data and find ways to backup your data. You also need to consider how to secure your data if you are working with others.
A practical suggestion for collaborative working was to make use of tools such as Teams or Sharepoint. For individual researchers, an alternative suggestion was to make use of OneDrive (which is a part of the university infrastructure). Keep a backup copy on an external device (and make sure it is encrypted).
Ethical and legal issues
Ethics permeate research. If you’re working with human research participants on research project within the boundary of the university, such as an EdD or PhD project, or a funded research project, you need to register your project with the university’s Human Research Ethics Committee (HREC). A part of this you will need to complete a risk checklist.
You must tell your participants what will happen with the data that is collected as a part of the research, not only during the research, but also after the research project. Specifically, you should tell participants where results may be published and whether dataset may be available afterwards.
Data protection is important. If you collect personal information as a part of your research, you must add details about your project to the university Information Asset Register (IAR).
Selection and preservation
An important question to be asked is: what data needs to be kept, and what data needs to be destroyed? The data protection legislation is important. You should ensure that any personal data that is collected is deleted at the end of a project. Some documents, such as consent forms, need to be maintained for a considerable amount of time after the project has ended (up to 10 years). How are these records going to be kept? The reason for maintaining these records is to ensure protection of both the participant and the researcher.
Data sharing
When a project has been completed, there may be a necessity to share the dataset with others. One of the reasons for wanting to do that is that fellow researchers might want to study your data to not only confirm your findings or to challenge your conclusions, but also to interrogate your dataset in different ways. The data that you collect (and share) might be useful for the study of different research questions.
Your data should be shared using a trusted repository that is “as open as possible, but as closed as necessary”. Sometimes, data can be shared through a research funder repository, a discipline specific repository, or an institutional repository. The OU has a repository called ORDO: OU’s Research Data repository.
An interesting resource that was mentioned was a site called re3data, which is short for Registry of Research Data Repositories. It’s also useful to note that repositories often make use of licences. Different repositories will have different licences.
Responsibilities and resources
Finally, there’s the important question of responsibilities. A key question is: who is responsible for the data management plan? In a plan, it would be useful to identify who is responsible for what data. Who, for example, be responsible for managing the upload of data to a repository.
Reflections
A key point that underpins this post is: do contact the library team for help and support.
I have two reflections to share. The first is that the way that research data is treated has significantly changed from when I started carrying out research, and this is a good thing. Whilst all this can be perceived as an annoying administrative burden, it necessarily helpful to spell out how data is used. In turn, this can open up possibilities in terms of how data can be used by other researchers. A detailed plan can also offer helpful reassurance to participants.
The second reflection relates to my role of a TM470 project tutor. Undergraduate projects sometime requires students to carry out research that involves people – for example, potential users of software systems. Since undergraduate projects sit outside the formal university (HREC) ethics processes, students don’t have to create a data management plan, there is benefit in considering how data is collected, used, and stored. The reason is, of course, these issues speak to the ethical issues that are important to every project. A practical recommendation for TM470 students is: if you collect data, create a short appendix (it could be only one or two pages in length) that summarises your data management plan.
Acknowledgements
Many thanks to the library research support team for running this event. The headings for this blog have been derived directly from their presentation.
Writing successful data management plans
What follows is a set of notes from a professional development event by the library research support team, which took place on 8 Feb 2024 (which now feels like a long time ago).
This even was of interest for a number of reasons: I supervise some EdD research projects, I’ve been successful in gaining a small amount of seed funding, and I thought it might be useful in my role as an undergraduate project supervisor.
What is a data management plan?
A data management plan (DMP) is written at the start of the project, something that funders need to see. It describes what data you’re doing to collect, how data is going to be stored and secured, how will access be granted.
The exact requirements of a DMP may very between different funders. It is especially important if your research data is going to be uploaded into an archive. It is probably a good idea to write one even if one isn’t explicitly needed. Knowing how to do prepare a good DMP is an important research skill. Your plan can, of course, evolve as your project evolves.
Every project will have different data requirements. Will your project gather data from interviews, focus groups, or surveys? Different types of data may have different types of management requirements. What is the volume of the data, i.e. how much? How will data be collected? Also, where will your data come from? Will it come from other sources, such as databases or third parties? To help with the preparation of a plan, there is a tool called DMP online, provided by the library.
During this session we were led to an activity and asked the question: what do you think are your main data management challenges for your research project?
What follows are some headings which highlight what elements of data collection, storage and management which need to considered.
Storage and backup
Effective backups prevent accidental losses and deletions. Even if your data is backed up, you need to ensure that backups have integrity - in the sense that if you need to access or use them, you can do so without encountering difficulties or data loss.
When thinking storage and backup consider the size and complexity of your data, and where research is carried out. If you work in “the field” (amongst participants), consider the physical security of your data and find ways to backup your data. You also need to consider how to secure your data if you are working with others.
A practical suggestion for collaborative working was to make use of tools such as Teams or Sharepoint. For individual researchers, an alternative suggestion was to make use of OneDrive (which is a part of the university infrastructure). Keep a backup copy on an external device (and make sure it is encrypted).
Ethical and legal issues
Ethics permeate research. If you’re working with human research participants on research project within the boundary of the university, such as an EdD or PhD project, or a funded research project, you need to register your project with the university’s Human Research Ethics Committee (HREC). A part of this you will need to complete a risk checklist.
You must tell your participants what will happen with the data that is collected as a part of the research, not only during the research, but also after the research project. Specifically, you should tell participants where results may be published and whether dataset may be available afterwards.
Data protection is important. If you collect personal information as a part of your research, you must add details about your project to the university Information Asset Register (IAR).
Selection and preservation
An important question to be asked is: what data needs to be kept, and what data needs to be destroyed? The data protection legislation is important. You should ensure that any personal data that is collected is deleted at the end of a project. Some documents, such as consent forms, need to be maintained for a considerable amount of time after the project has ended (up to 10 years). How are these records going to be kept? The reason for maintaining these records is to ensure protection of both the participant and the researcher.
Data sharing
When a project has been completed, there may be a necessity to share the dataset with others. One of the reasons for wanting to do that is that fellow researchers might want to study your data to not only confirm your findings or to challenge your conclusions, but also to interrogate your dataset in different ways. The data that you collect (and share) might be useful for the study of different research questions.
Your data should be shared using a trusted repository that is “as open as possible, but as closed as necessary”. Sometimes, data can be shared through a research funder repository, a discipline specific repository, or an institutional repository. The OU has a repository called ORDO: OU’s Research Data repository.
An interesting resource that was mentioned was a site called re3data, which is short for Registry of Research Data Repositories. It’s also useful to note that repositories often make use of licences. Different repositories will have different licences.
Responsibilities and resources
Finally, there’s the important question of responsibilities. A key question is: who is responsible for the data management plan? In a plan, it would be useful to identify who is responsible for what data. Who, for example, be responsible for managing the upload of data to a repository.
Reflections
A key point that underpins this post is: do contact the library team for help and support.
I have two reflections to share. The first is that the way that research data is treated has significantly changed from when I started carrying out research, and this is a good thing. Whilst all this can be perceived as an annoying administrative burden, it necessarily helpful to spell out how data is used. In turn, this can open up possibilities in terms of how data can be used by other researchers. A detailed plan can also offer helpful reassurance to participants.
The second reflection relates to my role of a TM470 project tutor. Undergraduate projects sometime requires students to carry out research that involves people – for example, potential users of software systems. Since undergraduate projects sit outside the formal university (HREC) ethics processes, students don’t have to create a data management plan, there is benefit in considering how data is collected, used, and stored. The reason is, of course, these issues speak to the ethical issues that are important to every project. A practical recommendation for TM470 students is: if you collect data, create a short appendix (it could be only one or two pages in length) that summarises your data management plan.
Acknowledgements
Many thanks to the library research support team for running this event. The headings for this blog have been derived directly from their presentation.