Semantic Web, Ontology Mapping Fall 2005 1 Ontology Mapping Elham Paikari paikari@ce.sharif.edu Sharif University Of Technology Computer Engineering Department

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  • Slide 1
  • Semantic Web, Ontology Mapping Fall 2005 1 Ontology Mapping Elham Paikari paikari@ce.sharif.edu Sharif University Of Technology Computer Engineering Department
  • Slide 2
  • Semantic Web, Ontology Mapping Fall 2005 2 Agenda The Role of Ontology Ontology Integration About the Problem Ontology Mismatch Language Level Mismatches Ontology Level Mismatches Conceptualization Mismatch Components Of Mapping Similarity Calculation Further Refinements Path Length Measurement Equivalence Interoperability
  • Slide 3
  • Semantic Web, Ontology Mapping Fall 2005 3 The Role of Ontology The word ontology comes from the Greek ontos for being. It is a relatively new term in the long history of philosophy, introduced by the 19th century German philosophers to distinguish the study of being. In information systems, a more pragmatic view to ontology is taken, where ontology is considered as a kind of agreement on a domain representation: ontology is an explicit account or representation of a conceptualization. This conceptualization includes a set of concepts, their definitions and their inter-relationships.
  • Slide 4
  • Semantic Web, Ontology Mapping Fall 2005 4 Ontology Integration Many works on ontology comparison has been motivated by ontology integration: given a set of independently developed ontologies, construct a single global ontology. The first step in integrating the ontologies is: Many works on ontology comparison has been motivated by ontology integration: given a set of independently developed ontologies, construct a single global ontology. The first step in integrating the ontologies is: Identify and characterize inter- ontology correspondences.
  • Slide 5
  • Semantic Web, Ontology Mapping Fall 2005 5 Ontology Integration The starting point for comparing and mapping heterogeneous semantics in ontology mapping is to semantically enrich the ontologies. Semantic enrichment facilitates ontology mapping by making explicit different kinds of hidden information concerning the semantics of the modeled objects. The underlying assumption is that the more semantics that are explicitly specified about the ontologies, the more feasible their comparison becomes.
  • Slide 6
  • Semantic Web, Ontology Mapping Fall 2005 6 Classification Of Ontology Specification Language
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  • Semantic Web, Ontology Mapping Fall 2005 7 Life Cycle Of An Ontology
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  • Semantic Web, Ontology Mapping Fall 2005 8 A Generic Architecture Of Ontology-Based Applications
  • Slide 9
  • Semantic Web, Ontology Mapping Fall 2005 9 Beneficial Applications Semantic Web Knowledge Management Information Retrieval Service Retrieval
  • Slide 10
  • Semantic Web, Ontology Mapping Fall 2005 10 About the Problem The Semantic Web proposes to standardize a semantic markup method for: Uniform formalism, XML Organization of knowledge into ontologies The scientific difficulties are linked to Exact definition of the formalisms Impossibility of maintaining a worldwide centralization of the ontologies Other challenges concern Robustness Scalability of these techniques
  • Slide 11
  • Semantic Web, Ontology Mapping Fall 2005 11 Survey We start with an introduction to the problem of ontology heterogeneity, which is characterized by different kinds of mismatches between ontologies. This kind of heterogeneity hampered us from a combined usage of multiple ontologies, which is needed in many applications. To solve the heterogeneity problem, the mismatches need to be reconciled. This means that we need to map and align different ontologies.
  • Slide 12
  • Semantic Web, Ontology Mapping Fall 2005 12 Ontology Mismatch Differences between ontologies are called mismatches, Issues: Practical problems Ontologies Versioning The main concern here is mismatches between ontologies. They are further divided into language level and ontology level. The former conforms to the syntactic layer, and the latter to the semantic layer. The main concern here is mismatches between ontologies. They are further divided into language level and ontology level. The former conforms to the syntactic layer, and the latter to the semantic layer.
  • Slide 13
  • Semantic Web, Ontology Mapping Fall 2005 13 Ontology Heterogeneity
  • Slide 14
  • Semantic Web, Ontology Mapping Fall 2005 14 Language Level Mismatches Mismatches at the language level occur when ontologies written in different ontology languages are combined. Four types of mismatches are identified. Syntax. Different ontology languages often use different syntaxes. For example, to define the class of car in RDF Schema, one uses. In LOOM, the expression (defconcept Car) is used to define the same class. Logical representation. A slightly more complicated mismatch at this level is the difference in representation of logic notions. For example, in some languages, it is possible to state explicitly that two classes are disjoint (e.g. disjoint A B), whereas it is necessary to use negation in subclass statements in other languages (e.g. A subclassof (NOT B), B subclass- of (Not A))
  • Slide 15
  • Semantic Web, Ontology Mapping Fall 2005 15 Language Level Mismatches Semantics of primitives. A more subtle possible difference at the language level is the semantics of language constructs. Despite the fact that sometimes the same name is used for a language construct in two languages, the semantics may differ, e.g., there are several interpretation of A equalTo B. Language expressivity. The mismatch at the language level with the most impact is the difference in expressivity between two languages. This difference implies that some languages are able to express things that are not expressible in other languages. For example, some languages have constructs to negation, whereas others have not.
  • Slide 16
  • Semantic Web, Ontology Mapping Fall 2005 16 Ontology Level Mismatches Mismatches at the ontology level happen when two or more ontologies that describe partly overlapping domains are combined. In the same language, or different languages. conceptualization mismatch is a difference in the way a domain is interpreted. divided into model coverage and concept scope (granularity). Explication mismatch is a difference in the way the conceptualization is specified.
  • Slide 17
  • Semantic Web, Ontology Mapping Fall 2005 17 Conceptualization Mismatch Scope. Two classes seem to represent the same concept, but do not have the same instances, although they may intersect. The classical example is the class employee, where several administrations use slightly different concepts of employee. Model coverage and granularity. This is a mismatch in the part of the domain that is covered by the ontology, or the level of detail to which that domain is modeled. the example of an ontology about cars: one ontology might model cars but not trucks. Another one might represent trucks but only classify them into a few categories, while a third ontology might make very finegrained distinctions between types of trucks based on their physical structure, weight, purpose, etc.
  • Slide 18
  • Semantic Web, Ontology Mapping Fall 2005 18 Explication Mismatches Two types of differences can be classified as terminological mismatches. Synonym terms. Concepts are represented by different names. One example is the use of term car in one ontology and the term automobile in another ontology. Homonym terms. The meaning of the same term is different in different context. For example, the term conductor has a different meaning in a music domain than it has in an electric engineering domain.
  • Slide 19
  • Semantic Web, Ontology Mapping Fall 2005 19 Explication Mismatches Modeling style is related to the paradigm and conventions taken by the developers. Paradigm. Different paradigms can be used to represent concepts such as time, action, plans, causality, propositional attitudes, etc. For example, one model might use temporal representations based on interval logic while another might use a representation based on point. Concept description. This type of differences are called modeling conventions. Several choices can be made for the modeling of concepts in the ontologies. For example, a distinction between two classes can be modeled using a qualifying attribute or by introducing separate class. Encoding mismatches are differences in value formats, like measuring distance in miles or in kilometers.
  • Slide 20
  • Semantic Web, Ontology Mapping Fall 2005 20 Approaches and Techniques The focus of this work is on ontology level mismatch (semantic mismatch). There are also approaches to tackle syntactic mismatches. We will briefly describe some of those in order to give a complete picture of the state. the state.
  • Slide 21
  • Semantic Web, Ontology Mapping Fall 2005 21 Solving Language Mismatches Four approaches to enable interoperability between different ontologies at the language level have been identified. Aligning the metamodel. The constructs in the language are formally specified in a general model. Layered interoperability. Aspects of the language are split up in clearly defined layers, and interoperability is to be resolved layer by layer.
  • Slide 22
  • Semantic Web, Ontology Mapping Fall 2005 22 Solving Language Mismatches Transformation rules. The relation between two specific constructs in differe

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