UNF Digital Commons, DC Data, and Faculty Profiles

Digital Commons Data - A Generalist Data Repository

About Digital Commons Data (DCD)

Digital Commons Data (DCD), offered by the University of North Florida’s Thomas G. Carpenter Library, is a generalist data repository for datasets and their supporting files that facilitates sharing in compliance with funder and publisher policies. It provides a means through which faculty researchers and administrators may store, collaborate on, manage, publish, and preserve datasets.

  • Researchers may collaborate on data with internal and external collaborators and apply access controls.
  • When datasets are uploaded on DCD, a DataCite DOI is reserved and will become active upon publication of the dataset.

To learn more, please reach out to lib-digital@unf.edu.


Advanced Searches in DC Data

Depositing Data - Format and Metadata Requirements


Many file and data types may be deposited, including text, structured and tabular data files, audio-visual media and image files, geospatial data, 3D data files, and more. We're happy to discuss your particular project needs and answer any questions.

Currently, each dataset may be a maximum of 100GB, but a project may contain more than one dataset.

Let us know at lib-digital@unf.edu if you have questions!


  • Every dataset can be annotated with a comprehensive set of metadata fields, including title, general description, description of each file, steps to reproduce the analyses, license, and administrative metadata such as institution and category.
  • Researchers may request additional custom metadata fields as needed.
  • Links can be created to further associated research outputs, such as datasets, software or articles.
  • To facilitate discovery and reuse of data, dataset metadata is available in the Dublin Core format and Schema.org format, conforming to the Google Dataset standard.
  • Dataset metadata is also made available for harvesting via OAI-PMH endpoints.

Deposited datasets should have:

  • Title
  • Description
  • Dates of data collection or compilation
  • Creator(s) and contributors
  • Any collaborating institutions in addition to the default of UNF

Additionally, it is optimal to include the following when applicable: 

  • Geographic location
  • Grant or other funding information
  • Links or citations for related publications or related datasets




Deposited datasets should not contain any copyrighted or sensitive data.
Deposited datasets should be unique to this repository, not duplicative of datasets already deposited elsewhere, and should not already have a DOI.