Ontological Knowledge Base

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An ontological knowledge base is a machine-readable knowledge base with a formal semantic model.




  • (Wikipedia, 2011) ⇒ http://en.wikipedia.org/wiki/Ontology_(information_science)
    • In computer science and information science, an ontology formally represents knowledge as a set of concepts within a domain, and the relationships between those concepts. It can be used to reason about the entities within that domain, and may be used to describe the domain. In theory, an ontology is a "formal, explicit specification of a shared conceptualisation".[1] An ontology renders shared vocabulary and taxonomy, which models a domain — that is, the definition of objects and/or concepts, and their properties and relations.[2] Ontologies are the structural frameworks for organizing information and are used in artificial intelligence, the Semantic Web, systems engineering, software engineering, biomedical informatics, library science, enterprise bookmarking, and information architecture as a form of knowledge representation about the world or some part of it. The creation of domain ontologies is also fundamental to the definition and use of an enterprise architecture framework. ...
    • Contemporary ontologies share many structural similarities, regardless of the language in which they are expressed. As mentioned above, most ontologies describe individuals (instances), classes (concepts), attributes, and relations. In this section each of these components is discussed in turn. Common components of ontologies include:
      • Individuals: instances or objects (the basic or "ground level" objects)
      • Classes: sets, collections, concepts, classes in programming, types of objects, or kinds of things
      • Attributes: aspects, properties, features, characteristics, or parameters that objects (and classes) can have
      • Relations: ways in which classes and individuals can be related to one another
      • Function terms: complex structures formed from certain relations that can be used in place of an individual term in a statement
      • Restrictions: formally stated descriptions of what must be true in order for some assertion to be accepted as input
      • Rules: statements in the form of an if-then (antecedent-consequent) sentence that describe the logical inferences that can be drawn from an assertion in a particular form
      • Axioms: assertions (including rules) in a logical form that together comprise the overall theory that the ontology describes in its domain of application. This definition differs from that of "axioms" in generative grammar and formal logic. In those disciplines, axioms include only statements asserted as a priori knowledge. As used here, "axioms" also include the theory derived from axiomatic statements
      • Events: the changing of attributes or relations
    • Ontologies are commonly encoded using ontology languages.


  • http://code.google.com/p/semanticscience/wiki/ODP
    • The following set of basic principles must be followed by any Semantic Science ontology.
      1. The ontology must be represented and correctly adhere to the strict semantics of the Web Ontology Language (OWL).
      2. All ontologies must be licensed with Creative Commons - Attribution. This ensures that people are free to share and create derivative works with the sole condition that derivative works must acknowledge sources.
      3. Resources, whether ontologies or entities described within them, must be uniquely and persistently identified by International Resource Identifiers (IRI). These should be dereferenceable. OWL documents should be versioned. The IRI syntax is suggested to follow that of the Banff Manifesto.
      4. Resources should be described with brief English labels (rdfs:label) and human readable definitions (dc:description) that are as accurate as possible, while not adding superfluous information or imposing unnecessary constraints. For consistency, labels should be lower case (unless a formal name) and words separated by whitespace. More elaborate syntax rules can be found here.
      5. Resources should be (to the extent possible) described through axioms that match their human readable descriptions.
      6. The scope of the ontology should be clearly described and must be motivated by itemized requirements (e.g. use cases), for each it will be expected to satisfy. These requirements may be documented on a public document such as a web page, a white paper, or a published work.


  • (Wikipedia, 2009) ⇒ http://en.wikipedia.org/wiki/Ontology
    • In philosophy, ontology (from the Greek, genitive : of being (part. of : to be) and -λογία: science, study, theory) is the most fundamental branch rof metaphysics. Ontology is the study of being or existence and its basic categories and relationships. ...
  • (WordNet, 2009) ⇒ http://wordnetweb.princeton.edu/perl/webwn?s=ontology
    • S: (n) ontology ((computer science) a rigorous and exhaustive organization of some knowledge domain that is usually hierarchical and contains all the relevant entities and their relations)
    • S: (n) ontology (the metaphysical study of the nature of being and existence)

  • http://www.w3.org/TR/owl2-overview/ OWL 2 Web Ontology Language, Document Overview
    • Ontologies are formalized vocabularies of terms, often covering a specific domain and shared by a community of users. They specify the definitions of terms by describing their relationships with other terms in the ontology.

  • http://www.jfsowa.com/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.
    • An informal ontology may be specified by a catalog of types that are either undefined or defined only by statements in a natural language. A formal ontology is specified by a collection of names for concept and relation types organized in a partial ordering by the type-subtype relation. Formal ontologies are further distinguished by the way the subtypes are distinguished from their supertypes: an axiomatized ontology distinguishes subtypes by axioms and definitions stated in a formal language, such as logic or some computer-oriented notation that can be translated to logic; a prototype-based ontology distinguishes subtypes by a comparison with a typical member or prototype for each subtype. Large ontologies often use a mixture of definitional methods: formal axioms and definitions are used for the terms in mathematics, physics, and engineering; and prototypes are used for plants, animals, and common household items.

  • (Vossen, ??) ⇒ Piek Vossen. (??) "Building Wordnets." http://www.globalwordnet.org/gwa/BuildingWordnets.ppt
    • Conceptual ontology:
      • A particular level or structuring may be required to achieve a better control or performance, or a more compact and coherent structure.
      • Introduce artificial levels for concepts which are not lexicalized in a language (e.g. instrumentality, hand tool),
      • Neglect levels which are lexicalized but not relevant for the purpose of the ontology (e.g. tableware, silverware, merchandise).
      • What properties can we infer for spoons?
        • spoon -> container; artifact; hand tool; object; made rof metal or plastic; for eating, pouring or cooking
    • Linguistic ontology:
      • Exactly reflects the relations between all the lexicalized words and expressions in a language.
      • Valuable information about the lexical capacity of languages: what is the available fund of words and expressions in a language.
      • What words can be used to name spoons?
        • spoon -> object, tableware, silverware, merchandise, cutlery,




Depending on the scope of the ontology, ontology may be classified as follows (see also figure above):
  • upper, generic, top-level ontology - describing general knowledge, such as what is time and what is space
  • domain ontology - describing a domain, such as medical domain or electrical engineering domain, or narrower domains, such as personal computers domain
  • task - ontology suitable for a specific task, such as assembling parts together
  • application - ontology developed for a specific application, such as assembling personal computers


  • (Obitko, 2007) ⇒ Marek Obitko. (2007). “Translations between Ontologies in Multi-Agent Systems", Ph.D. dissertation, Faculty of Electrical Engineering, Czech Technical University in Prague. http://obitko.com/tutorials/ontologies-semantic-web/ontologies.html
    • The term "ontology" can be defined as an explicit specification of conceptualization. Ontologies capture the structure of the domain, i.e. conceptualization. This includes the model of the domain with possible restrictions. The conceptualization describes knowledge about the domain, not about the particular state of affairs in the domain. In other words, the conceptualization is not changing, or is changing very rarely. Ontology is then specification of this conceptualization - the conceptualization is specified by using particular modeling language and particular terms. Formal specification is required in order to be able to process ontologies and operate on ontologies automatically.

      Ontology describes a domain, while a knowledge base (based on an ontology) describes particular state of affairs. Each knowledge based system or agent has its own knowledge base, and only what can be expressed using an ontology can be stored and used in the knowledge base. When an agent wants to communicate to another agent, he uses the constructs from some ontology. In order to understand in communication, ontologies must be shared between agents.





  • (Kalfoglou & Schorlemmer, 2003) ⇒ Yannis Kalfoglou, and Marco Schorlemmer. (2003). “Ontology mapping: the State of the Art.” In: The Knowledge Engineering Review.
    • QUOTE: We shall adopt an algebraic approach and present ontologies as logical theories. An ontology is then a pair O = (S,A), where [math]S[/math] is the (ontological) signature describing the vocabulary — and [math]A[/math] is a set of (ontological) axioms — specifying the intended interpretation of the vocabulary in some domain of discourse. Typically, an ontological signature will be modelled by some mathematical structure. For instance, it could consist of a hierarchy of concept or class symbols modelled as a partial ordered set (poset), together with a set of relations symbols whose arguments are defined over the concepts of the concept hierarchy. The relations themselves might also be structured into a poset. For the purposes of this survey we shall not commit to any particular definition of ontological signature; we refer to the definitions of ‘ontology’, ‘core ontology’, or ‘ontology signature’ in (Kalfoglou and Schorlemmer 2002; Stumme and Maedche 2001; Bench-Capon and Malcolm 1999), respectively, for some examples of what we consider here an ontological signature. In addition to the signature specification, ontological axioms are usually restricted to a particular sort or class of axioms, depending on the kind of ontology.




  • (Guarino & Giaretta, 1995) ⇒ Nicola Guarino, and Pierdaniele Giaretta. (1995). “Ontologies and Knowledge Bases: Towards a Terminological Clarification.” In: "Towards Very Large Knowledge Bases". N.J.L. Mars. (editor). IOS Press. ISBN:78-90-5199-217-5
    • QUOTE: Figure 1: Possible interpretations of the term “ontology".
    • The interpretation 1 is radically different from all the others, and its implications are discussed in the next section. The current debate regards the interpretations 2-7: 2 and 3 conceive an ontology as a conceptual "semantic" entity, either formal or informal, while according to the interpretations 5-7 an ontology is a specific "syntactic" object. The interpretation 4, which has been recently proposed as a definition of what an ontology is for the AI community [4, 5], is one of the more problematic, and it will be discussed in detail in the present paper. It may be classified as "syntactic" but its precise meaning depends on the understanding of the terms "specification" and "conceptualization".