Data visualizations tend to be a particular arrangement of one or more raw datasets. Data visualization formats can obscure parts of the underlying data that they are derived from. They may also be compiled or complex. All of these properties could potentially make the data difficult to open, validate, or comprehend in the future. To preserve a publication in which data visualizations are core intellectual components, request underlying raw data from the author. Request supporting documentation that would enable a future reader to retrace the author's steps from the raw data to the visualization. Images or videos of the visualization may also be helpful for recreating it. For both visualization and raw data formats, as with all supplements, ideally the files will be an open or broadly adopted format. The Library of Congress Recommended Formats Statement can help with selecting formats. In the case of vector data, for example, there is not a broadly adopted open format, but Shapefile, while proprietary, is broadly adopted and openly documented. There are a variety of tools that can read Shapefiles which increases the likelihood that it will continue to be supported in some form.
These guidelines may also be relevant when considering preservation of data visualizations:
11. Use non-proprietary, broadly supported and adopted open file formats
57. Use alternative approaches for features that require communication with a server
64. Use meaningful file names and field names in your data, supply documentation