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An Ontology Design Pattern for Representing Relevance in OWL

An Ontology Design Pattern for Representing Relevance in OWL. Juan Gómez-Romero, Fernando Bobillo, Miguel Delgado University of Granada Department of Computer Science and A.I. ISWC2007. outline. Information overload Ontology design pattern Reasoning Related work Future work.

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An Ontology Design Pattern for Representing Relevance in OWL

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  1. An Ontology Design Pattern for Representing Relevance in OWL Juan Gómez-Romero, Fernando Bobillo, Miguel Delgado University of GranadaDepartment of Computer Science and A.I. ISWC2007

  2. outline • Information overload • Ontology design pattern • Reasoning • Related work • Future work

  3. information overload • In general: People get more information than understandable • In Information Systems: Users get overwhelmed by information provided by the system • In Mobile Systems: Easier to be “overloaded” with information

  4. example • A doctor is attending to a patient outside the hospital (e.g.: emergency units, primary healthcare in remote areas) • The doctor uses a portable device to connect to the Hospital Information System (HIS) • He gets a bunch of Electronic Health Records (EHRs) about the patient in order to suggest a treatment • He filters the results manually and grasps interesting information (if he has enough time and knowledge) • Overload!

  5. relevance of information • Solution: To provide only “relevant” information • But… what is relevant? • It depends on: • User preferences • User environment • User previous actions • … • Context (in a wide sense!) • “The interrelated conditions in which something exists or occurs” (Merryam-Webster)

  6. example • A doctor is attending to a patient outside the hospital (e.g.: emergency units, primary healthcare in remote areas) • He is interested only in some pieces of advice related with the patient situation • For instance, • If the patient is “slightly unconscious” and has an “hemorrhagic laceration”… • information about if he has been diagnosed of “bad reactions to procaine” should be taken into account

  7. representation of relevance • We need to represent “relevance” (which depend on context) in ontologies • “Desirable”: Standard OWL language and tools must be used • Identify common problems and provide some suggestions to solve them → An ontology design pattern

  8. CDR pattern (i) • Context-Domain Relevance (CDR, pronounced “cider”) pattern • A pattern to build an OWL ontology which represents relevance relations • Context ontology: vocabulary to describe scenarios/circumstances/etc. • Domain ontology: knowledge about the problem to be solved • Profile ontology: Links among complex contexts and domains

  9. CDR pattern (ii)

  10. inference • Restricted domain I of a scenario S • To get the domain information which is relevant in a given context • Algorithm • Get the complex contexts Cn more general than S • Get the profiles Pn,m involving Cn • Get the complex domains Dminvolved in Pn,m • Get the concepts I of the domain more specific than Dm

  11. CDR plug-in for Protégé

  12. features • Reusability (pattern and ontologies) • Standardization (basic requirement) • Formalization (formal semantics of the relevance ontology and the inference) • Modularization (promotes ontology modularization) • Expressivity (enough to represent relevance) • Complexity (bounded by context and domain expressions)

  13. related work • Ontology design patterns • Svátek, V.(2004). Design Patterns for Semantic Web Ontologies: Motivation and Dicussion • Gangemi , A. (2005). Ontology Design Patterns for Semantic Web Content • Context/environment representation in Pervasive Computing • Chen, H., Finin, T., Joshi, A. (2005). The SOUPA Ontology for Pervasive Computing • Gu, T., Pung, H., Zhang, D. (2005). A service-oriented middleware for building context-aware services • Lassila, O. , Khushraj, D. (2005). Contextualizing applications via semantic middleware • Contextualization of ontologies • Guha, R., McCool, R., Fikes, R. (2004). Contexts for the Semantic Web • Bouquet, P., Giunchiglia, F., van Harmelen, F., Serafini, L., Stuckenschmidt, H. (2004). Contextualizing ontologies • Stuckenschmidt, H. (2006). Toward Multi-viewpoint Reasoning with OWL Ontologies

  14. future work • Promote pattern (and good practices) specifications for ontology development • Study and solve issues with owl:import • Enhancing and supporting Protégé plug-in • Fuzzy extension of the relevance ontology for representing partial context inclusion and ranking of relevance relations

  15. end questions? comments? thank you! 감사합니다

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