1. OIL: An Ontology Infrastructure for the Semantic Web D. Fensel, F. van Harmelen, I. Horrocks, D. L. McGuinness, P. F. Patel-Schneider Presenter: Cristina Nicolae

2. Ontologies “An ontology is a formal, explicit specification of a shared conceptualization.” –conceptualization: abstract model of some phenomenon in the world that identifies that phenomenon’s relevant concepts –explicit: the type of concepts used and the constraints on their use are explicitly defined –formal: the ontology should be machine understandable –shared: an ontology captures consensual knowledge (accepted by a group)

3. Applications of ontology technology (1/3) Knowledge management –acquiring, maintaining and accessing an organization’s knowledge –weaknesses: searching information (irrelevant word in other context) extracting information (lack commonsense knowledge) maintaining (large sources) automatic document generation (require a machine- accessible representation of the semantics of info sources) –future solution: semantic annotations

4. Applications of ontology technology (2/3) Web commerce –online stores, shopping agents, online marketplaces, auction houses –get information from several stores through wrappers – which use keyword search to find product info –limitations: effort (writing wrapper for each online store is time-consuming + changes in store) quality (info extracted is limited, error-prone and incomplete) –future solution: software agents to understand product information

5. Applications of ontology technology (3/3) Electronic business –e-commerce in business-to-business field –protocol (standard): the UN Edifact –shortcomings: procedural and cumbersome standard programming of business transactions expensive and error-prone large maintenance efforts an isolated standard –future solution: using the Internet’s infrastructure for business exchange

6. OIL HTML: initial, simplistic XML: provides serialized syntax for trees RDF: defines a syntactical convention and a simple data model – triples: object/property/value RDF Schema: introduces basic ontological primitives into the Web – classes, subclasses, subproperties, restrictions.. OIL: based on RDFS, enriched into a full-fledged Web-based ontology language

7. Criteria that OIL matches We need an advanced ontology language to express and represent ontologies. Must be: –highly intuitive to the human: OIL  frame-based –central modeling primitives are classes (frames) with attributes –well-defined formal semantics (completeness, correctness and efficiency) OIL  description logics –knowledge is described in terms of concepts and role restrictions –proper link to existing Web languages (XML, RDF) OIL  syntax in XML, based on RDF –a standardized syntax for writing ontologies and a standard set of modeling primitives

8. OIL’s layered architecture Each layer adds functionality and complexity to the previous one Core OIL: coincides with RDFS except reification features Standard OIL: specifying the semantics and making complete inferences viable Instance OIL: full-fledged database capability Heavy OIL: will include additional representational and reasoning capabilities

9. An ontology

10. OIL tools Ontology editors –build new ontologies OntoEdit (U. Karlsruhe), OILed (U. Manchester), Protégé (Stanford) Ontology-based annotation tools –we can derive an XML DTD and an XML Schema definition from an ontology in OIL –we can derive an RDF and RDFS definition for instances from OIL Reasoning with ontologies –reason about an ontology’s instances and schema definition FaCT

11. Applications of OIL Swiss Life: Organizational memory –an intranet-based front end to an organizational memory British Telecom: Call centers –call center agents use a variety of electronic sources for information when interacting with customers  OIL provides front end tool EnerSearch: Virtual enterprise –is a virtual organization researching new IT-based business strategies and customer services in deregulated energy markets  OIL toolkit enhances knowledge transfer.

12. Conclusions on OIL is properly grounded in Web languages (XML Schemas & RDFS) inner layers enable efficient reasoning support based on FaCT has a well-defined formal semantics