Abstract
The preservation of digital objects is a topic of prominent importance for archives and digital libraries. This paper focuses on the problem of preserving the performability of tasks on digital objects. It formalizes the problem in terms of Horn Rules and details the required inference services. The proposed framework and methodology is more expressive and flexible than previous attempts as it allows expressing the various properties of dependencies (e.g. transitivity, symmetry) straightforwardly. Finally, the paper describes how the proposed approach can be implemented using various technologies.
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Tzitzikas, Y., Marketakis, Y., Antoniou, G. (2010). Task-Based Dependency Management for the Preservation of Digital Objects Using Rules. In: Konstantopoulos, S., Perantonis, S., Karkaletsis, V., Spyropoulos, C.D., Vouros, G. (eds) Artificial Intelligence: Theories, Models and Applications. SETN 2010. Lecture Notes in Computer Science(), vol 6040. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12842-4_30
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DOI: https://doi.org/10.1007/978-3-642-12842-4_30
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