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Dataset and Software for Abstraction Materialization Maintenance

<p>Abstraction Refinement is a technique which allows for reducing materialization of an ontology with a large ABox to materialization of a smaller (compressed) `abstraction&#39; of this ontology. The corresponding conference paper shows how Abstraction Refinement can be adopted for incremental ABox materialization by combining it with the well-known DRed algorithm for materialization maintenance. The combination is non-trivial and to preserve correctness, already Horn ALCHI requires more complex abstractions. Nevertheless, significant benefits can be obtained for synthetic and real-world ontologies. This data set contains the source code for the implementation as well as the used test data and test runners to reproduce the results reported in the paper.</p>

ShareScore

40/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship
8
Harmonization
8
Access
12
Reuse readiness
8
Engagement
4

Topics