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Representing and reasoning with modular ontologies

Posted on:2008-10-25Degree:Ph.DType:Dissertation
University:Iowa State UniversityCandidate:Bao, JieFull Text:PDF
GTID:1448390005969007Subject:Artificial Intelligence
Abstract/Summary:
Realizing the full potential of the semantic web requires the large-scale adoption and use of ontology based approaches to sharing of information and resources. In such a setting, instead of a single, centralized ontology, it is much more natural to have multiple distributed ontologies that cover different, perhaps partially overlapping, domains. Such ontologies represent the local knowledge of the ontology designers, that is, knowledge that is applicable within a specific context. Hence, many application scenarios, such as collaborative construction and management of complex ontologies, distributed databases, and large knowledge base applications, present an urgent need for ontology languages that support localized and contextualized semantics, partial and selective reuse of ontology modules, flexible ways to limit the scope and visibility of knowledge (as needed for selective knowledge sharing), federated approaches to reasoning with distributed ontologies, and structured approaches to collaborative construction of large ontologies. Against this background, this dissertation develops a family of description logics based modular ontology languages, namely Package-based Description Logics (P-DL), to address the needs of such applications. The main contributions of this dissertation include: (1) The identification and theoretical characterization of the desiderata of modular ontology languages that can support selective sharing and reuse of knowledge across independently developed knowledge bases; (2) The development of a family of ontology languages called P-DL, which extend the classical description logics (DL) to support selective knowledge sharing through a novel semantic importing mechanism and the establishment of a minimal set of restrictions on the use of imported concepts and roles to support localized semantics, transitive propagation of imported knowledge, and different interpretations from the point of view of different ontology modules; (3) The development of a family of sound and complete tableau-based federated reasoning algorithms for distributed, autonomous, P-DL ontologies including ALCP and SHIQP , i.e., P-DL onologies where the individual modules are expressed in the P-DL counterpart of DL ALC and SHIQ respectively, that can be used to efficiently reason over a set of distributed, autonomous, ontology modules from the point of view of any specific module, that avoid the need to integrate ontologies using message exchanges between modules as needed; (4) The formulation of criteria for answering queries against a knowledge base using hidden or private knowledge, whenever it is feasible to do so without compromising hidden knowledge, and the development of privacy-preserving reasoning strategies for the case of the commonly used hierarchical ontologies and SHIQ ontologies, along with a theoretical characterization of the conditions under which they are guaranteed to be privacy-preserving; (5) The development of some prototype tools for collaborative development of large ontologies, including support for concurrent editing and partial loading of ontologies into memory.
Keywords/Search Tags:Ontologies, Ontology, Large, Reasoning, Development, Support, P-DL, Modular
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