Christoph F. Eick

1
Shared Ontologies

• Christoph F. Eick
• www.cs.uh.edu/ceick/ceick.html
• University of Houston
• Organization
• 1. What are Ontologies?
• 2. What are they good for?
• 3. Ontologies and Brokering
• 4. Critical Problems with Respect to Shared
  Ontologies

2
What are Ontologies?

• Ontologies are content theories about sorts of
  objects, properties of objects, and relationship
  between objects that are possible in a specified
  domain of knowledge (Chandrasekaran)
• We consider ontologies to be domain theories
  that specify a domain-specific vocabulary of
  entities, classes, properties, predicates, and
  functions, and a set of relationships that
  necessarily hold among those vocabulary items
  (Fikes)
• Shared ontologies form the basis for domain
  specific knowledge representation languages
  (Chandrasekaran)
• If we could develop ontologies that could be
  used as the basis of multiple systems, they would
  share a common terminology that would facilitate
  sharing and reuse (W. Swartout)
• Ontologies play an important role for the
  standardization of terminology in medicine (e.g.
  UMLS) and other domains
• Ontologies can serve as the glue between
  knowledge that is represented at different,
  usually heterogeneous information sources.

3
What are Ontologies good for?

• As a shared conceptual model of a particular
  application domain that describes the semantics
  of the objects that are part of the domain, and
  captures knowledge that is inherent to the
  particular domain --- idea knowledge base .
• Ontologies provide a vocabulary for representing
  knowledge about a domain and for describing
  specific situations in a domain (tool for
  defining and describing domain-specific
  vocabularies) --- idea language for
  communication
• For data/knowledge translation and transformation
  (provide a solution to the translation problem
  between different terminologies) for fusion and
  refinement of existing knowledge --- idea
  interoperation
• For matchmaking between users, agents, and
  information resources in agent-based systems ---
  idea collaboration, brokering focus of
  next slides
• As reusable building blocks to build systems that
  solve particular problems in the application
  domain --- idea model reuse
• Summary Ontologies can be used as building
  block components of knowledge bases, object
  schema for object-oriented systems, conceptual
  schema for data bases, structured glossaries for
  human collaborations, vocabularies for
  communication between agents, class definitions
  for conventional software system, etc. (Fikes)

4
Key Ideas Agent-based Technologies

• Agents operate independently and anticipate user
  needs (P. Maes)
• Agent help users suffering from information
  overload (O. Etzioni) rather to mimic human
  intelligence
• Agents are important because the allow users to
  interoperate with modern applications such as
  electronic commerce and information retrieval.
  Most of these applications assume that components
  are added dynamically and that they will be
  autonomous (serve different users and providers
  to fill different goals) and heterogeneous. (M.
  Singh)
• Essentially, agent-based architectures are
  characterized by three key features autonomy,
  adaptation, and cooperation. Agent-based systems
  are computational systems in which several agents
  interact for their own good and for the good of
  the overall system.
• In an agent-based architecture services are
  provided in the context of a community of loosely
  coupled agents of various types in a distributed
  environment.
• Agents are aware of their environment and
  capable of communicating with other agents that
  belong to the same agent community.

5
Ontologies and Brokering

• Service providers describe their capabilities in
  terms of a domain (or task) ontology
• Agents that seek services describe their needs in
  terms of a domain (or task) ontology
• Broker agents server as matchmakers between
  service providers and service seekers by finding
  suitable agents and by evaluating the extent to
  which they can provide those services relying on
  a semantic brokering approach.
• Various languages have been advocated in the
  recent years to specify ontologies OKBC,
  CKML/OML, ONTOLINGUA, XML, UMLS, SNOMED, GALEN...

6
Service Provider Agents
End User Agents
A Traditional Approach
Search Engine
Specify keywords with respect to the documents
they are looking for
Clinical Trial Report
Abstract Clinical Trial Report
Summary
Semantic Brokering Approach
Service Provider Agents
End User Agents
Semantic Brokering
Specify subset of ontology
Clinical Trial Report
Subset of an Ontology
Summary
matchmaking
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Example Semantic Brokering
Data Analysts Information Requirement
Patient
Result Semantic Brokering ((DataCollection1 nil
((missing slot weight)
(contradictory ( age 40))
(DataCollection2 t) (DataCollection3 t (( age
60)( weight 300)))
Age40
weight
Intensive-Care- Patient
Hours-in-intensive-care
Data Collection1
Data Collection2
Data Collection3
Patient
Patient
Patient
Ageage
Age60
weight
Weight300
Intensive-Care- Patient
Intensive-Care- Patient
Intensive-Care- Patient
Hours-in-intensive-care
Hours-in-intensive-care
Hours-in-intensive-care
8
Critical Problems with Respect to Shared
Ontologies

• Scientific communities have to agree on
  ontologies otherwise, the whole approach is
  flawed.
• Development of ontologies for a particular domain
  is a difficult task (see Digital Anatomist
  project at UW, development of UMLS). The
  development of user friendly, and intelligent
  knowledge acquisition tools is very important for
  the successful development of shared ontologies.
• Expressiveness of languages that are used to
  define ontologies limits what can be done with
  domain ontologies.
• Reasoning capabilities are important for systems
  that use shared ontologies (we need a language to
  specify ontologies and an inference engine that
  can reason with the given ontologies)
• finding inconsistencies in knowledge bases, for
  finding errors at data entry
• semantic brokering
• more intelligent mappings between terms
• ...

9
References

• WWW-Links
• http//ksl-web.stanford.edu/Reusable-ontol/P001.ht
  ml (Richard Fikes (Stanford University) Slide
  Show on Reusable Ontologies
• http//www.cs.cmu.edu/softagents/ (CMU
  Intelligent Software Agents Page)
• Papers
• Special Issue IEEE Intelligent Systems on Coming
  to Terms with Ontologies, Jan./Feb. 1999.