Data Management

Increase your research impact
Making your data available to other researchers can impact discovery and relevance of your research.

Save time
Planning ahead for your data management needs will save you time and resources.

Preserve your data
Depositing your data in a repository safeguards your investment of time and resources while preserving your research contribution for you and others to use.

Maintain data integrity
Managing and documenting your data throughout its life cycle will allow you and others to understand and use your data in the future.

Meet grant requirements
Many funding agencies now require that researchers deposit data collected as part of a research project.

Promote new discoveries
Sharing your data with other researchers can lead to new and unanticipated discoveries and provide research material for those with little or no funding.

The Texas Tech University Libraries' Data Management Team is here to help faculty members in preparing data management plans for inclusion in research grants and other funding opportunities. 

This libguide contains three sections of information which faculty and staff can access for the development of their data management plans in coordination with the library or by using resources for independent creation.

The Texas Tech University Libraries data management team offers to researchers individual consultations. This can allow the researcher to talk with data management experts to help him or her prepare individual data management plans. You can contact Matt McEniry for a consultation using the email below:

matthew.mceniry@ttu.edu

• What type of data will be produced?

Gather a clear picture of what your data will look like. Is it, for example, numerical data, image data, text sequences or modeling data? Knowing exactly what kind of data you have will inform many decisions you need to make about storage, backups and more. Image data requires a lot of storage space, so you'll want to decide which of your images, if not all, you want to retain, and where such large datasets can be housed. As for backing up your data, your research center or university may have the ability to help you. On the other hand, if you are storing images, you may quickly exceed your institution's limit for backing up individual laboratories or groups.

• How much of it, and at what growth rate?

Once you know what kind of data you're producing, you'll be able to assess the growth rate. For example, are you gathering data by hand or using sophisticated instrumentation that is able to capture a lot of data at once? Will there be more data as time goes on? If so, you will need to plan for the growth. What amounts to enough storage this year may not be sufficient for next year.

• Will it change frequently?

The answer to this question impacts how you organize the data as well as the level of versioning you will need to undertake. Keeping track of rapidly changing datasets can be a challenge, so it's imperative you begin with a plan that will carry you through the data management process.

• Who is it for?

Who is your audience for the data? How will they use the data? The answer to this question will tell you how to structure the data and where to distribute it, among other things.

• Who controls it (PI, student, lab, TTU, funder, co-owners)?

Before you spend a lot of time figuring out how you're going to store the data, name it, etc. you need to know if you have the authority to control it.

• How long should it be retained? (e.g. 3-5 years, 10-20 years, permanently)

Not all data needs to be retained indefinitely. Figure out what's important to keep and make sure your plan for those datasets is solid.

Thank you and credit to Tufts University Library for permission to use and adapt their pages.