Data Management

Data Management

Data management is the process of controlling data before, during, and after a research project. All researchers--faculty and students alike--should take steps to manage their data effectively. This ensures your research is safe, promotes the potential for data reuse, and assists in the compliance with federal guidelines.

There are many components to proper management of research data, and the Libraries provide several services and resources to assist you.

Data Management Plan Advising

  • Comply with the federal agencies proposal requirements
  • Describe how data will be maintained and what resources will be needed to preserve it
  • Have well described and organized data when posting a supplemental dataset with your publication
  • Prepare data for review before and/or after the article is accepted for publication, as required by some publishers, e.g. Nature and Science
  • Facilitate re-use of data sets, open access, and data sharing

Depending on the discipline, the nature of a project, and the funding agency, every data management plan is unique. The Libraries offer support to UNL researchers who need help creating data management plans through workshops and consultations.


The Libraries offer general workshops through the year on preparing data management plans to conform with granting agencies' policies on disseminating, preserving and sharing research results.

In addition, you can request a workshop for your department, laboratory, students, or project team. These 30-60 minute workshops can be tailored to your needs, and may cover a combination of the following data management topics:

  • Overview of what you need in order to effectively manage data
  • File formats and handling best practices
  • Where to get help for data storage, metadata, and archiving


You can also request an individual consultation for guidance on a data management plan for a specific grant proposal. The Libraries will provide a review of and comments on draft data management plans prior to proposal submission to help ensure the plan addresses the granting agency's criteria and is easy for proposal reviewers to understand.

Additional Resources

  • Data Management Plan Template: While every data management plan is unique, this template contains the 5 basic categories that we recommend you to use as you craft your plan. You are free to download this template and use it to guide you as you start writing your plan.
  • Data Management Guide: This Data Management Guide provides information on a wide array of data management topics. It includes a data management plan template, sample data management plans, funding agency specifications, and sample text that you can use as a starting point as you write your own data management plan.

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Data Storage & Preservation

Managing data does not end with your research project. What will you do with your data following project completion? To preserve your data, select a data repository that will suit your needs. This can either be an institutional repository, like the UNL Data Repository, or a domain-specific repository. During data management plan consultations, a librarian can help you decide which option is most appropriate for you and your data.

Institutional Data Repository

UNL Libraries hosts the UNL Data Repository (UNLDR), which is designed to provide researchers with a secure site for storage and long-term preservation of data collections that are no longer actively in use.

The UNLDR allows the researcher to stably retain data for future use and/or sharing with other interested parties and exists to manage data in a manner that facilitates research and scholarly activities, and that simplifies access to vital and unique research data.

The data and project information deposited by researchers maintains its value over time with information (known as metadata) that outlines its importance, its long-term usability, and the dedicated efforts of those who were involved. UNLDR includes back-ups, disaster recovery, and long-term support for managing data and access.

The Libraries offer UNL researchers 50 GB of free data storage in UNLDR.

Domain Data Repository

You may also choose to deposit your data in a repository that is specific to your research discipline. There are a wide array of domain repositories available. The following websites provide directories of repositories and are a great starting point for considering a domain repository.

Wherever you decide to deposit your data, it is important to account for these storage costs. If applying for a grant, proposers should include a line item in their project budget to cover the costs of data storage.

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Data Sharing & Discovery

The topic of sharing data is becoming increasingly significant when discussing research data. This stems from:

  • a desire among researchers to allow others to build upon their data, especially when this data cannot be reproduced (or only at great expense).
  • the necessity to ensure research integrity by supporting research publications with the underlying data.
  • recent policy changes requiring researchers to share data generated through a federally funded research project.

UNL Libraries supports data sharing and discovery through the UNL Data Repository:

  • Datasets deposited in UNL's Data Repository will be exposed to the web using open standards to maximize discoverability and scholarly reuse of data.
  • If you choose to deposit your data in another repository, e.g. a domain-specific repository, you can still register your data in UNLDR, increasing your data's visibility.
  • UNLDR provides for layered security that addresses privacy and confidentiality, intellectual property and copyright, and access and sharing of data.

In addition, UNL Libraries will assign a permanent URL to deposited datasets using a Digital Object Identifier (DOI) to allow for data citation and reference.

It is also important to consider your unique identification as a researcher. From Google Scholar Citations to researcher IDs (ResearchID, ORCID/SciVal), the Libraries have expertise to help you link your publications and datasets to yourself.

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