Archiving Digital Projects

Not all of the data that is created for or forms the basis of a digital project is necessary accessible through an HTML interface. In addition, some readers will want to build on your dataset, making it important to share that data in easily reusable formats.

For projects built primarily in Content Management Systems (CMS) such as Omeka, WordPress, or Scalar, most of the data will be contained in the project database. This can be exported and saved as an XML file, a RDF file, or a SQL file from a database “dump”.

• These export files generally do not contain any media files, such as images, video, or sound files. These will need to be saved separately in their own zipped folder.

For data that is used primarily for computational purposes, such as network data, statistical data, or geospatial data, follow the data management best practices (http://infoguides.gmu.edu/data-management) to document and organize your data in ways to enable others to understand, evaluate, and use it.

Upload the data files to either DSpace or Dataverse, depending on the format and state of the data. Work with Data & Digital Scholarship Services to determine the best platform for your data files.

For advice on formatting data that was created outside of a CMS for the purposes of archiving and sharing, visit Data & Digital Scholarship Services (DDSS) at the George Mason University Libraries or email datahelp@gmu.edu.

For advice determining the copyright status of your data items and you ability to archive them, contact Emilie Algenio in Mason Publishing.

Copyright: Not all data can be shared equally and if you do not have the right to share the data, respect the copyright holder as much as possible. In the case that datasets or media elements are under copyright or are restricted in some way, identify the copyright holder and document, as far as possible, the process by which a future visitor could gain access to those same materials.

File Size: Some data sets may be large and better served by a subject specific repository, rather than the institutional repository. Talk to Data & Digital Scholarship Services about which data repositories best fit your project and goals.