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  9G. Falquet et al., Ontologies in Urban Development Projects ,   Advanced Information and Knowledge Processing 1, DOI 10.1007/978-0-85729-724-2_2, © Springer-Verlag London Limited 2011 2.1 Introduction In the last decades, the use of ontologies in information systems has become more and more popular in various fields, such as web technologies, database integration, multi agent systems, natural language processing, etc. Artificial intelligent researchers have initially borrowed the word “ontology” from Philosophy, then the word spread in many scientific domain and ontologies are now used in several developments. The main goal of this chapter is to answer generic questions about ontologies, such as: Which are the different kinds of ontologies? What is the purpose of the use of ontolo-gies in an application? Which methods can I use to build an ontology?There are several types of ontologies. The word “ontology” can designate different computer science objects depending on the context. For example, an ontology can be:a thesaurus in the field of information retrieval or–a model represented in OWL in the field of linked-data or–a XML schema in the context of databases–etc.– Chapter 2 An Introduction to Ontologies and Ontology Engineering Catherine Roussey, Francois Pinet, Myoung Ah Kang, and Oscar Corcho C. Roussey ( * ) LIRIS, Université de Lyon, Francee-mail: Catherine.Roussey@cemagref.frF. Pinet French Institute for Agricultural and Environmental Engineering, Clermont Ferrand, Francee-mail: Francois.Pinet@cemagref.frM.A. Kang Laboratory of Computer Science, Modelling and System Optimization, Blaise Pascal University, Clermont Ferrand, FranceO. Corcho Departamento de Inteligencia Artificial, Facultad de Informática, Universidad Politécnica de Madrid (UPM), Spaine-mail: ocorcho@fi.upm.es  10C. Roussey et al. It is important to distinguish these different forms of ontologies to clarify their content, their use and their goal. It is also needed to define precisely the vocabulary derived from the word ontology. For example what is the difference between a core ontology and a domain ontology? First, we introduce and define the different types of ontologies. Second, we present some methodologies to build ontologies. Some of the illustrative examples will be taken from project presentations made in the con-text of the COST UCE Action C21 (Urban Ontologies for an improved communica-tion in UCE projects TOWNTOLOGY) or, in general, in the area of Geographic Information Systems (GIS). 2.2 Ontology Classifications Several classifications of ontologies have been presented in the literature (Lassila and McGuinness 2001; Gomez-Perez et al. 2004; Borgo 2007, etc). Each of them focused on different dimensions in which ontologies can be classified. This section focuses on two of these classifications: the first one classifies ontologies according to the expressivity and formality of the languages used: natural language, formal language, etc.; the second one is based on the scope of the objects described by the ontology.  2.2.1 Classification Based on Language Expressivity  and Formality Depending on the expressivity of an ontology (or, in general, of a knowledge representation language), different kinds of ontology components can be defined (concepts, properties, instances, axioms, etc.). Figure 2.1 presents the set of com-ponents that we will use to provide our classification based on language expressivity. For example, if we focus on concepts, which are one of the main components of ontologies, the UML class diagram of Fig. 2.1 shows as that they can be defined in different (and complementary) ways:By their textual definitions: For example the concept “ ã  person ” is defined by the sentence “ an individual human being ”,By a set of properties: for example the concept “ ã  person ” has the property “ name ”, “ birth date ” and “ address ”; note that a property can be reused for several concepts.By a logical definition composed of several formulae: for example the concept ã “  person ” is defined by the formula “  LivingEntity ∩  MovingEntity ”.A concept can also be defined by the set of instances that belong to it. For example, “  Martin Luther King ” is an instance of the concept “  person ”. This last definition is called the extensional definition of a concept and the three former definitions are called intensional definitions of a concept.  112 An Introduction to Ontologies and Ontology Engineering Concepts, instances and properties are referenced by one or more symbols. Symbols are terms that humans can rapidly understand roughly by reading them. And finally all these ontology components are connected through relations. Semantic relations link only concepts together: for example the location relationship indicates that city concept is localized in a country concept. Instance relations connect only instances and instance relations are often instances of semantic relations, although it is not always the case. Some relations between instances can be contextual and cannot be generalized to all instances of their concept. An example of instance rela-tion is that the city instance named Paris is localized in the country instance named France. All cities are localized in a country. A contextual instance relation can be that the person instance named “John Travolta” is localized in the city instance named “Paris” at the point in time 31 January 2010. The terminological relations express the relationships that terms can have: for example the term “  person ” is syn-onym to the term “ human being ”According to the usage of these components, in the following sections we present four kinds of ontologies. In each section we explain which type of language is normally used to define the ontology and we provide some examples for illustra-tion purposes. The classification starts using the less formal languages to the more formal one. Fig. 2.1  UML class diagram representing ontology components and their relationships  12C. Roussey et al. 2.2.1.1 Information Ontologies Information ontologies are composed of diagrams and sketches used to clarify and organize the ideas of collaborators in the development of a project. These ontologies are only used by humans. The characteristics of information ontologies are:Easily modifiable and scalable ã Synthetic and schematic ã They are normally used during a design process of a project: for example, infor- ã mation ontology can be used during the conception phase of information system development project or during the design of floor plan in architectural construc-tion project.As shown in Fig. 2.2, information ontologies focus on concepts, instances and their relationships. Their goal is to propose an overview of a current project in order to express the state of this project. The grey color of the property elements means that properties are not always well defined by information ontologies.Information ontologies are normally described by means of visual languages, so that they can be easily understood by humans. A Mind Map is a good example of this type of visual language. For example the OnToKnowledge project about meth-odology for ontology design propose to add a Mind Map plug-in called Mind2Onto in their ontology editor called OntoEdit (Sure and Studer 1999). They notice that Brain Storming is a good method to quickly and intuitively start a project. Their Mind Map plug-in is a support for discussion about ontology structure. Mind Map descriptions will be followed by three examples of information ontologies: one example will be taken from urban planning project, another one come from archi-tectural design and the latter is used in a construction project. Fig. 2.2  UML schema of information ontology component and their relationships
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