A data model and architecture for long-term preservation

Authors:
Greg Janée;Justin Mathena;James Frew
Affiliations:
University of California, Santa Barbara, Santa Barbara, CA, USA;University of California, Santa Barbara, Santa Barbara, CA, USA;University of California, Santa Barbara, Santa Barbara, CA, USA
Venue:
Proceedings of the 8th ACM/IEEE-CS joint conference on Digital libraries
Year:
2008

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Abstract

The National Geospatial Digital Archive, one of eight initial projects funded under the Library of Congress's NDIIPP program, has been researching how geospatial data can be preserved on a national scale and be made available to future generations. In this paper we describe an archive architecture that provides a minimal approach to the long-term preservation of digital objects based on co-archiving of object semantics, uniform representation of objects and semantics, explicit storage of all objects and semantics as files, and abstraction of the underlying storage system. This architecture ensures that digital objects can be easily migrated from archive to archive over time and that the objects can, in principle, be made usable again at any point in the future; its primary benefit is that it serves as a fallback strategy against, and as a foundation for, more sophisticated (and costly) preservation strategies. We describe an implementation of this architecture in a protoype archive running at UCSB that also incorporates a suite of ingest and access components.