Best practices for handling of data-images include retaining the original captured image, along with capture and post-processing steps in metadata. Creating that storage space for a myriad of data-types is challenging for research institutions which can only archive some of their data. At a recent conference on data management at the University of Virginia, librarians discussed the cost of data storage and the lack of consistent formats for data and metadata.
In the past, storage costs have led some stakeholders to think that since science is supposed to be replicable, storing data is redundant, and only the research paper with its methods section should be necessary to replicate the data. During the conference James Hilton, CIO for the university, noted that while some data is easily replicable and does not need archival space, there are also bodies of data for which replication is too expensive or not possible such as observational data, and therefore archival storage space should be provided.
Data types and metadata standards are not always uniform even within a field, creating additional barriers in developing effective institutional repositories. Consistent retention of image-capture and post-processing steps as metadata are not yet built into the research process. As research institutions grapple with storage issues, standardization of metadata must become part of the best practices for managing data-image management.