Topicality in Logic-Based Ontologies

Vescovo, Chiara Del; Parsia, Bijan; Sattler, Ulrike

doi:10.1007/978-3-642-22688-5_14

Cited by 1 publication

(2 citation statements)

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“…Another scenario, called Topicality for Ontology Comprehension, is based on the assumption that, in order to enable the understanding of what the ontology deals with, we can search for its "topics" and their interrelations [4]. In this case, a good decomposition should provide a "bird's-eye" view of the topical structure of an ontology.…”

Section: Decomposability Of Bioportal Ontologiesmentioning

confidence: 99%

“…In contrast, in the Topicality for Ontology Comprehension scenario we observe that, when the number of atoms is comparable with the number of axioms, then atoms do not provide any summarization over axioms and we cannot hope that considering atoms can provide any summarization benefit. In this case, the atoms reflect only very fine-grained topics of an ontology [4]. However, the dependency structure reflects the logical dependency between atoms, and thus can be used to consider, e.g., dependent components which, in turn, may better reflect the topics of an ontology.…”

Section: Decomposability Of Bioportal Ontologiesmentioning

confidence: 99%

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Decomposition and Modular Structure of BioPortal Ontologies

Vescovo

Gessler

Klinov

et al. 2011

The Semantic Web – ISWC 2011

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We present the first large scale investigation into the modular structure of a substantial collection of state-of-the-art biomedical ontologies, namely those maintained in the NCBO BioPortal repository.1 Using the notion of Atomic Decomposition, we partition BioPortal ontologies into logically coherent subsets (atoms), which are related to each other by a notion of dependency. We analyze various aspects of the resulting structures, and discuss their implications on applications of ontologies. In particular, we describe and investigate the usage of these ontology decompositions to extract modules, for instance, to facilitate matchmaking of semantic Web services in SSWAP (Simple Semantic Web Architecture and Protocol). Descriptions of those services use terms from BioPortal so service discovery requires reasoning with respect to relevant fragments of ontologies (i.e., modules). We present a novel algorithm for extracting modules from decomposed BioPortal ontologies which is able to quickly identify atoms that need to be included in a module to ensure logically complete reasoning. Compared to existing module extraction algorithms, it has a number of benefits, including improved performance and the possibility to avoid loading the entire ontology into memory. The algorithm is also evaluated on BioPortal ontologies and the results are presented and discussed.

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Section: Decomposability Of Bioportal Ontologiesmentioning

confidence: 99%

Section: Decomposability Of Bioportal Ontologiesmentioning

confidence: 99%