By Shanda Hunt

The process of managing data is becoming an increasingly important skill set for researchers and a prominent topic in academic circles.

This dates back to a 2013 White House memo on increased access to the results of federally funded research.

One outcome of this memo is that federal funders now require researchers to develop a data management plan for submission with their grant applications.

Additionally, funders and publishers alike are more frequently requiring that the underlying data that supports publications be made available to the public.

This Research Byte is intended to introduce some of the tools and resources that you can apply to support your own data management work.

About data management

Data management is a set of practices across the research lifecycle that ensure the integrity of files and data, facilitate replication, protect the security of data, and enhance the efficiency and reliability of research.

It means that you start early — even before research begins — to create a plan for file naming, folder structures, documentation, metadata, storage, backup, security, data sharing, and preservation.

Good data management is important because data sharing increases the transparency of research and supports the reuse of data, which can ultimately accelerate research and reduce costs associated with data collection.

Getting started

Whether the practice of data management is familiar or new, take a look at the University Libraries’ Managing Your Data webpage for data management tools and strategies — before, during, and after your research.

You can also request personalized data management training for your department, research group, or course (data@umn.edu), or a consultation with a data curator on how to share your data (datarepo@umn.edu).

If you are conducting or sharing research, look to the Data Repository for the University of Minnesota (DRUM) to access or preserve datasets.

What you need to know

Below are key resources and timely news about data management principles and the outcomes of good data management.  

• In 2014, the FAIR Guiding Principles were established. They came from the belief that all research data should be Findable, Accessible, Interoperable, and Reusable.
• A 2018 article by Ippoliti et al. shows that academic libraries are well positioned to support researchers in data management due to their expertise in managing, curating, and preserving digital information. Remember that here at the University of Minnesota, you can contact your subject librarian for individualized support for your research or department.
• The journal Nature just reported on the importance of sharing data to support open science and cultivate funding. The University Libraries extends upon the work noted in this report as it also curates individual datasets — along with many other data management tasks — in their efforts to support researchers.

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About the author

Shanda Hunt, M.P.H., is an Assistant Librarian and serves as Liaison & Data Curation Specialist to the School of Public Health. In this role, she has participated in Data Management Bootcamps to help graduate students from across disciplines integrate data management best practices into their research. She has also coordinated Research Sprints, an intensive week-long program where teams of librarians and archivists help researchers complete projects.

Hunt shares one critical message for anyone working with data — start early. Careful data management has many benefits and can ultimately lead to more funding.

She welcomes you to contact her at hunt0081@umn.edu.