Skip to Main Content
It looks like you're using Internet Explorer 11 or older. This website works best with modern browsers such as the latest versions of Chrome, Firefox, Safari, and Edge. If you continue with this browser, you may see unexpected results.
Publishing data means making it discoverable and reusable by others, with or without access controls.
Data Services Offered
NEW! Computational Support
Meet one-on-one with an expert in Python, R, ArcGIS, data visualization, and many other data science/programming packages.
Data Skill Consultations
For more information or to set up an appointment, contact the Research Data Management Librarian.
Need assistance with study design or data manipulation/analysis? The Statistical Consulting Center may be able to help.
Are you looking for massive parallel computing power? Consider the High Performance Computing Cluster.
How to Publish Data
There are several ways to publish data:
- In a trusted repository (preferred)
Placing data in a certified repository preserves the information while providing access. Datasets in repositories are assigned stable digital identifiers and indexed by search tools, facilitating discovery and reuse. Repositories may be either generalist or subject/community specific. Use the Registry of Research Data Repositories or the Directory of Open Access Repositories to find a suitable repository, or contact the library to set up a consultation.
- As supplemental material in a journal article
Many journals allow the publication of data and other documentation as supplements alongside the original article. This ensures that data are clearly linked to the article. There are also data journals that exist specifically to publish datasets. Journal policies vary widely with regards to the type and amount of supplemental information they will publish, as well as whether supplements are subject to peer-review. Contact the journal editorial staff prior to submitting a manuscript for more information on the journal's practices regarding supplemental information.
- On a custom website
In general, publishing data to a personal website is not recommended, but there may be times when a custom solution is appropriate. For data that is of interest to a highly specific group, is only relevant for a limited period of time, or requires fine-grained access control, dedicating a specific website to distribution may be a good option. Contact your department's IT or Auburn OIT to discuss available resources.
What about providing data to colleagues by request?
Sharing data by request is a well-established scholarly practice. Data sharing is not the same as data publication, because data that is shared directly between researchers cannot be cited as easily and will not be indexed by search tools. Some repositories formally publish data but also implement access controls (ICPSR is a good example). Thus, data publication should not be confused with allowing unrestricted public access to that data. However, data publication is not appropriate in every case. Informal data exchange among colleagues is and will continue to be an important form of data sharing.
A major benefit to publishing data is that it can increase the impact of your research. Datasets can and should be cited like any other scholarly source. In order to ensure research is cited properly, data providers need to associate datasets with a stable URL and assign a permanent identifier like a DOI. Good research repositories do this automatically at the time of deposit.
Suggested data citation style:
Author 1, Author 2, (etc.). Year. Dataset title. Data repository/archive. Version (if applicable). Permanent identifier.
When publishing data, check that you have provided enough information for others to generate a complete citation. Some repositories provide the suggested citation alongside the dataset so that it can be copied by users. For more information, see data citation best practices.
Selected Data Repositories