Download OIL: An Ontology Infrastructure for the Semantic Web

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
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)
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 machineaccessible representation of the semantics of info
sources)
– future solution:
• semantic annotations
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
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
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
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
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
An ontology
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
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.
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