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The Dataverse Research Data Repository at Texas State University: Publication Checklist

Guide to using Dataverse to manage and share data

Preparing Data for Submission

Group your files into meaningful datasets

Decide on how you want to structure your data. A submission should consist of a set of files (up to 4GB per file) that make up a complete dataset that are explicitly labeled. If your submission contains data from multiple, unrelated projects, consider grouping your items into separate submissions.

More repository policies:

Ensure future usability:

To facilitate others opening and using your data files in the future, please make sure that your files are in appropriate, open-source formats to assist with long-term preservation. If your data is dependent on proprietary software formats, options for preserving the data long-term may be limited.


Preparing Data Documentation

Include documentation describing your data

Collect any documentation that gives information about what data is included in your data set and how it is structured. Some examples of what to include in your documentation are:

  • Descriptions of any acronyms or abbreviations used (e.g., column headings, variable names, etc.)
  • The methodology used to collect and analyze the data
  • Citations to journal articles based on the data
  • Explanation of file-naming conventions
  • The names and contact information of any contributors
  • Descriptions of what is found in each file

This document should describe what data is included in your dataset and any special instructions for understanding your data files. It should give context to your data and ensure that future users of your data will be able to easily understand what is included.

Not sure where to start? Try using our README file template with your dataset: 

Data Permissions and Rights

Ensure that you have the right to share the data

Make sure that you have all necessary rights to deposit the data into Dataverse. If other individuals maintain rights to the data, you must obtain permission from them to deposit your dataset.

De-identify any personally identifiable information (PII)

Ensure that you have removed any data that could be used to identify subjects of your research. For detailed explanation for what constitutes PII, check here:

Consider using an open license to share your data

An open license allows others to use your data for other purposes. You may impose constraints on the data’s future use through the use of an appropriate license. Dataserve offers the option of open licensure under Creative Commons. An explanation of the different Creative Commons licenses that are available can be found at:


Is your data right for Dataverse?

Does your dataset meet the requirement for submission?

  • Authored by at least one Texas State University researcher
  • Does NOT contain any private, confidential, or other legally protected information
  • Ready for public access and reuse?

Data Preparation

Plan your organization of files and datasets

  • Would it make sense to break your data into multiple submissions?
  • Are your data files grouped in a meaningful way?
  • Is your data labeled consistently (e.g., data headers, file naming, etc.)?
  • Have you avoided using proprietary software wherever possible?

Data Documentation

Do you have documentation for your data? 

  • If not, have you prepared a README file to describe the dataset?
  • Are all acronyms/abbreviations spelled out in the documentation?
  • Is your data collection methodology included in the documentation?
  • Would someone else be able to understand your dataset using the documentation?

Deposit Rights

Do you have all the necessary copyright permissions to make the data available on Dataverse?

  • Have all collaborators, advisors, or other interested parties agreed on sharing publicly via Dataverse?
  • Are you aware of the rights you are granting Dataverse by depositing your data?


Sharing Permissions

Have you considered the questions around sharing?

  • Do you have any specific data sharing requirements (e.g., from funding agencies)?
  • Is the data anonymized to protect any personally identifiable information?
  • Do you wish to manage access to your data (e.g., place an embargo)?
  • Have you made note of any special software that would be required to access your data?
  • Watch this video from Texas Data Repository on how to restrict access to certain files as a means of managing permissions:




  • Have you considered applying an open license to your dataset? Dataverse applies a CC0 license by default - have you considered if a different license would work better?
  • What constraints, if any, would you like to add to the license (e.g., non-commercial use only, attribution required, etc.)?