Christos Strubulis

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Workflow systems can produce very large amounts of provenance information. In this paper we introduce provenance-based inference rules as a means to reduce the amount of provenance information that has to be stored, and to ease quality control (e.g., corrections). We motivate this kind of (provenance) inference and identify a number of basic inference rules(More)
Provenance information of digital objects maintained by digital libraries and archives is crucial for authenticity assessment, reproducibility and accountability. Such information is commonly stored on metadata placed in various Metadata Repositories (MRs) or Knowledge Bases (KBs). Nevertheless, in various settings it is prohibitive to store the provenance(More)
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