Ontology

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Ontology

• CS 630 Presentation
• By Christina Yau
• 03-27-2003

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What is an Ontology?

• Short answer An ontology is a specification of a
  conceptualization.
• In philosophy, ontology is the study of the kinds
  of things that exist, a systematic account of
  Existence.Aristotle's attempt to classify things
  in the world.
• Onto means existence, being

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What is an Ontology?

• "An ontology defines the basic terms and
  relations comprising the vocabulary of a topic
  area as well as the rules for combining terms and
  relations to define extensions to the
  vocabulary." Neches, Fikes, Finin, Gruber, etc
  1991
• An ontology is a description (like a formal
  specification of a program) of the concepts and
  relationships that can exist for an agent or a
  community of agents. This definition is
  consistent with the usage of ontology as
  set-of-concept-definitions, but more general. And
  it is certainly a different sense of the word
  than its use in philosophy. Gruber 1993-2

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What is an Ontology?

• "An ontology is an explicit specification of a
  conceptualization." Gruber 1993
• An ontology is a formal, explicit specification
  of a shared conceptualisation. Borst 1997
• "An ontology defines a common vocabulary for
  researchers who need to share information in a
  domain Noy McGuinness 2001

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What is an Ontology?

• Conceptualisation refers to an abstract model
  of some phenomenon in the world by having
  identified the relevant concepts of that
  phenomenon.
• Explicit means that the type of concepts used,
  and the constraints on their use are explicitly
  defined. (For example, in medical domains, the
  concepts are diseases and symptoms, the relations
  between them are causal and a constraint is that
  a disease cannot cause itself.)
• Formal refers to the fact that the ontology
  should be machine readable, which excludes
  natural language.
• Shared reflects the notion that an ontology
  captures consensual knowledge, that is, it is not
  private to some individual, but accepted by a
  group." Studer etc 1998

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What is an Ontology?

• (Working definition)
• "An ontology may take a variety of forms, but
  necessarily it will include a vocabulary of
  terms, and some specification of their meaning.
  This includes definitions and an indication of
  how concepts are inter-related which collectively
  impose a structure on the domain and constrain
  the possible interpretations of terms. An
  ontology is virtually always the manifestation of
  a shared understanding of a domain that is agreed
  between a number of agents. Such agreement
  facilitates accurate and effective communication
  of meaning, which in turn leads to other benefits
  such as inter-operability, reuse, and sharing."
  Uschold 1998

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What is an Ontology?

• "We consider ontologies to be domain theories
  that specify a domain-specific vocabulary of
  entities, classes, properties, predicates, and
  functions, and to be a set of relationships that
  necessarily hold among those vocabulary terms.
  Ontologies provide a vocabulary for representing
  knowledge about a domain and for describing
  specific situations in a domain." Fikes
  Farquhar 1999

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What is an Ontology?

• "In our case, the ontology primitives comprise
• a set of strings that describe lexical entries L
  for concepts and relations
• a set of concepts C
• a taxonomy of concepts with multiple inheritance
  (heterarchy) Hc
• a set of nontaxonomic relations R described by
  their domain and range restrictions
• a heterarchy of relations HR
• relation F and G that relate concepts and
  relations with their lexical entries
• a set of axioms A that describe additional
  constraints on the ontology and make implicit
  facts explicit. Maedche Staab 2001
• Ontology lexicon concepts relation axiom

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What is an Ontology?

• "The subject of ontology is the study of the
  categories of things that exist or may exist in
  some domain. The product of such a study, called
  an ontology, is a catalog of the types of things
  that are assumed to exist in a domain of interest
  D from the perspective of a person who uses a
  language L for the purpose of talking about D.
• The types in the ontology represent the
  predicates, word senses, or concept and relation
  types of the language L when used to discuss
  topics in the domain D.
• An uninterpreted logic, such as predicate
  calculus, conceptual graphs, or KIF, is
  ontologically neutral. It imposes no constraints
  on the subject matter or the way the subject may
  be characterized. By itself, logic says nothing
  about anything, but the combination of logic with
  an ontology provides a language that can express
  relationships about the entities in the domain of
  interest. Sowa

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Why develop an ontology?

• To share common understanding of the structure of
  information among people or software agents
• To enable reuse of domain knowledge
• To make domain assumptions explicit
• To separate domain knowledge from the operational
  knowledge
• To analyze domain knowledge

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General agreement between Ontologies

• There are objects in the world.
• Objects have properties or attributes that can
  take values.
• Objects can exist in various relations with each
  other.
• Properties and relations can change over time.
• There are events that occur at different time
  instants.
• There are processes in which objects participate
  and that occur over time.
• The world and its objects can be in different
  states.
• Events can cause other events or states as
  effects.
• Objects can have parts. Chandrasekaran, etc 1999

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General agreement between Ontologies

• Ontological Commitment
• An ontological commitment is an agreement to use
  a vocabulary (i.e., ask queries and make
  assertions) in a way that is consistent (but not
  complete) with respect to the theory specified by
  an ontology. We build agents that commit to
  ontologies. We design ontologies so we can share
  knowledge with and among these agents.

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Type/Terminology of Ontology

• Common (or generic or commonsense) Ontologies
• ( Upper Ontology or top-level ontology ??)
• Domain Ontologies
• Terminology Ontologies
• Formal Ontology
• Mixed ontology
• Representational ontologies
• Task and Method Ontologies
• Regional ontology

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Common Ontologies

• capture general knowledge about the world
• provide basic notations and concepts for things
  like time, space, state, event etc
• as a consequence, they are valid across several
  domains
• e.g ontology about mereology (part-of relations)
• (Upper Ontology or top-level ontology -- general
  level descriptive terms)

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Domain Ontologies

• capture the knowledge related with a specific
  domain
• e.g. electronic, medical, mechanic, digital
  domain

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Terminology Ontologies

• An ontology whose categories need not be fully
  specified by axioms and definitions.
• An example of a terminological ontology is
  WordNet, whose categories are partially specified
  by relations such as subtype-supertype or
  part-whole, which determine the relative
  positions of the concepts with respect to one
  another but do not completely define them.
• Most fields of science, engineering, business,
  and law have evolved systems of terminology or
  nomenclature for naming, classifying, and
  standardizing their concepts. Axiomatizing all
  the concepts in any such field is a Herculean
  task, but subsets of the terminology can be used
  as starting points for formalization.
  Unfortunately, the axioms developed from
  different starting points are often incompatible
  with one another.

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Formal ontology

• A terminological ontology whose categories are
  distinguished by axioms and definitions stated in
  logic or in some computer-oriented language that
  could be automatically translated to logic.
• There is no restriction on the complexity of the
  logic that may be used to state the axioms and
  definitions. The distinction between
  terminological and formal ontologies is one of
  degree rather than kind. Formal ontologies tend
  to be smaller than terminological ontologies, but
  their axioms and definitions can support more
  complex inferences and computations.
• Examples of formal ontologies include theories in
  science and mathematics, the collections of rules
  and frames in an expert system, and specification
  of a database schema in SQL.

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Mixed ontology

• An ontology in which some subtypes are
  distinguished by axioms and definitions, but
  other subtypes are distinguished by prototypes.
  The top levels of a mixed ontology would normally
  be distinguished by formal definitions, but some
  of the lower branches might be distinguished by
  prototypes.

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Representational Ontologies

• provide representational entities without stating
  what should be represented.
• A well-known representational ontology is the
  Frame Ontology, which defines concepts such as
  frames, slots and slot constraints allowing the
  expression in an object-oriented or frame-based
  way.

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Task and Method Ontologies

• provide a reasoning point of view on domain
  knowledge
• task ontologies
• provide terms specific for particular task
• e.g. "hypothesis" belongs to the diagnosis task
  ontology
• method ontologies
• provide terms specific to particular PSMs
• e.g. "correct state" belongs to the
  Propose-and-Revise method ontology.

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Type/Terminology of Ontology

• For task seems to be domain specific, knowledge
  representation might call for an ontology that
  describes knowledge at higher levels of
  generality.

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Upper Ontology and Domain Ontology in IFF
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General Concepts
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Ontology range

• Ontology range in abstraction (very general terms
  that form the foundation for knowledge
  representation in all domains) to domain specific
  terms (i.e. terms that are restricted to specific
  knowledge domains).
• E.g. space, time, parts, and subparts -- all
  domains
• mulfunction -- engineering or biological
  domain
• hepatitis -- medicine

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References

• Borst 1997 Engineering Ontologies. Borst, P.,
  Akkermans, H. and Top, J. International Journal
  of Human-Computer Studies, (46)365-406, 1997.
• Chandrasekaran, etc 1999 What are ontologies,
  and why do we need them? Chandrasekaran, B.
  Josephson, J.R. Benjamins, V.R. IEEE Intelligent
  Systems, 14(1)20-26, 1999.
• Fikes Farquhar 1999 Distributed Repositories
  of Highly Expressive Reusable Ontologies. Fikes,
  R., Farquhar, A. IEEE Intelligent Systems,
  14(2)73-79, 1999.
• Gruber 1993 A Translation Approach to Portable
  Ontology Specifications. Thomas R. Gruber.
  Knowledge Acquisition 5(2)199-220, 1993.

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References

• Gruber 1993-2 What is an Ontology?
  http//www-ksl.stanford.edu/kst/what-is-an-ontolog
  y.html
• Maedche Staab 2001 Ontology Learning for the
  Semantic Web. Alexander Maedche and Steffen
  Staab. IEEE Intelligent Systems, 16(2)72-79,
  2001.
• Neches, Fikes, Finin, Gruber, etc 1991 Enabling
  Technology For Knowledge Sharing. Robert Neches,
  Richard Fikes, Tim Finin, Thomas Gruber, Ramesh
  Patil, Ted Senator, and William R. Swartout. AI
  Magazine, Volume 12, No. 3, Fall 1991.
• Noy, etc 2001 Ontology Development 101 A Guide
  to Creating Your First Ontology. Natalya F. Noy
  and Deborah L. McGuinness. Stanford Knowledge
  Systems Laboratory Technical Report KSL-01-05 and
  Stanford Medical Informatics Technical Report
  SMI-2001-0880, March 2001.

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References

• Sowa Ontology. http//www.jfsowa.com/ontology
• Studer, Benjamins, Fensel 1998 Knowledge
  Engineering Principles and Methods. Rudi Studer,
  V. Richard Benjamins, and Dieter Fensel. Data and
  Knowledge Engineering, 25(102)161-197, 1998.
• Uschold 1998 Knowledge level modelling
  concepts and terminology. The knowledge
  Engineering Review, 13(1)5-29, 1998.
• Information Flow Framework (IFF)
  http//suo.ieee.org/IFF/version/20021205.htm