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Ontology Management

Ontology Management. Service-Oriented Computing: Semantics, Processes, Agents – Munindar P. Singh and Michael N. Huhns, Wiley, 2005. Highlights of this Section. Motivation Standard Ontologies Consensus Ontologies. Motivation.

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Ontology Management

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  1. Ontology Management Service-Oriented Computing: Semantics, Processes, Agents– Munindar P. Singh and Michael N. Huhns, Wiley, 2005

  2. Highlights of this Section • Motivation • Standard Ontologies • Consensus Ontologies Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

  3. Motivation • Descriptions of services are improved through the use of ontologies • But how do we ensure the parties involved agree upon the ontologies? • Traditional approach: standardize the ontologies via a formal process • Emerging approach: • Be more like the Web • Figure out the “correct” ontology via consensus Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

  4. Standard Ontologies Standardization is more a sociopolitical than a technical process • IEEE Standard Upper Ontology • Common Logic (language and upper-level ontology) • Process Specification Language • Space and time ontologies • Domain-specific ontologies, such as health care, taxation, shipping, … Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

  5. An Example Upper Ontology Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

  6. OASIS Universal Business Language (UBL) Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

  7. Standardization Pros • Where standards exist and are agreed upon, they (even if imperfect) • Save time and improve effectiveness • Enable specialized tools where appropriate • Improve longevity of solution over time and space • Suggest directions for improvement Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

  8. Standardization Cons • Standardization of domain-specific ontologies is • Cumbersome • Often out of date by the time completed • Difficult to maintain • Often violated for competitive reasons Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

  9. Standardization: Proposed Approach • Always use standard languages (XML, RDF, OWL, …) • Take high-level concepts from standard models: • Domain experts are not good at KR • Lot of work in the best of cases • Work toward consensus in chosen domain Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

  10. Inducing Common Ontologies • Instead of beginning with a standard, develop consensus to induce common ontologies • Assumptions: • No global ontology • Individual sources have local ontologies • Which are heterogeneous and inconsistent • Motivation: Exploit richness of variety in ontologies • To see where they reinforce each other • To make indirect connections (next page) Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

  11. Alternative Approaches We may construct large ontologies by • Inducing classes from large numbers of instances using data-mining techniques • Building small specialized ontologies and merging them (Ontolingua) • Top-down construction from first principles (Cyc and IEEE SUO) Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

  12. Aside: Categorizing Information Consensus is driven by practical considerations • Should service providers classify information where it • Belongs in the “correct” scientific sense? • Where users will look for it? • Case in point: If most people think a whale is a kind of fish, then should you put information about whales in the fish or in the mammal category? Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

  13. Section Summary • For large-scale systems development, agreeing upon acceptable ontologies is nontrivial • Standardization helps, but suffers from key limitations • Consensus approaches seek to figure out acceptable ontologies based on available small ontologies • Should always use standards for representation languages Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

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