Abstract
The current state of Web technology – the “first generation” or “syntactic” Web – gives rise to well-known, serious problems when trying to accomplish, in a non-trivial way, essential tasks like indexing, searching, extracting, maintaining, and generating information. These tasks would, in fact, require some sort of ‘deep understanding’ of the information dealt with: in a “syntactic” Web context, on the contrary, computers are only used as tools for posting and rendering information by brute force. Faced with this situation, Tim Berners- Lee first proposed a sort of “Semantic Web” where the access to information is based mainly on the processing of the semantic properties of this information: “… the Semantic Web is an extension of the current Web in which information is given well-defined meaning (emphasis added), better enabling computers and people to work in co-operation” (Berners-Lee et al., 2001: 35). The Semantic Web’s challenge consists of being able to access and retrieve information on the Web by “understanding” its proper semantic content (its meaning), and not simply by matching some keywords.
TopIntroduction
The current state of Web technology – the “first generation” or “syntactic” Web – gives rise to well-known, serious problems when trying to accomplish, in a non-trivial way, essential tasks like indexing, searching, extracting, maintaining, and generating information. These tasks would, in fact, require some sort of ‘deep understanding’ of the information dealt with: in a “syntactic” Web context, on the contrary, computers are only used as tools for posting and rendering information by brute force. Faced with this situation, Tim Berners-Lee first proposed a sort of “Semantic Web” where the access to information is based mainly on the processing of the semantic properties of this information: “… the Semantic Web is an extension of the current Web in which information is given well-defined meaning (emphasis added), better enabling computers and people to work in co-operation” (Berners-Lee et al., 2001: 35). The Semantic Web’s challenge consists of being able to access and retrieve information on the Web by “understanding” its proper semantic content (its meaning), and not simply by matching some keywords.
From a technical point of view, the Semantic Web vision is deeply rooted into an “ontological” approach, with some proper characteristics that differentiate it from the “classical” approach to the construction of ontologies based on a methodology of the frame” type (Chaudhri et al., 1998) and on the use of tools in the “standard” Protégé style (Noy, Fergerson and Musen, 2000). We will describe these characteristics in the following Sections.
Key Terms in this Chapter
Semantic Web Services: A Web service is a Web site that does not simply supply static information, but that allows also to execute automatically some ‘actions’ (services), like the sale of a product or the control of a physical device. To do this, Web services make use of XML-based standards like WSDL, a description protocol, and SOAP, a messaging protocol, characterized by a low level of semantic expressiveness. For example, WSDL can describe the interface of the different services, and how these services are deployed via SOAP, but it is very limited in its ability to express what the overall competences of this service are. Semantic Web Services are Web Services that can specify not only their interfaces, but also describe in full, under the form of OWL-based ontologies, their capabilities, and the prerequisites and consequences of their use. For example, OWL-S is a specification, in the form of an ontology, intended to describe different Semantic Web Services features, enabling then Web users and software agents to automatically discover, invoke, select, compose and monitor Web-based services.
RDF Schema (RDFS): provides a mechanism for constructing specialized RDF vocabularies through the description of domain-specific properties. This is obtained mainly by describing the properties in terms of the classes of resource to which they apply: for example, we could define the creator property saying that it has the resource document as ‘domain’ (document is the value or ‘object’ of this property) and the resource person as ‘range’ (this property must always be associated with a resource person, its ‘subject’). Other basic modelling primitives of RDFS allow setting up hierarchies (taxonomies), both hierarchies of concepts thanks to the use of class and subclass-of statements, and hierarchies of properties thanks to the use of property and subproperty-of statements. Instances of a specific class (concept) can be declared making use of the type statement.
RDF (Resource Description Framework): an example of ‘metadata’ language (metadata = data about data) used to describe generic ‘things’ (‘resources’, according to the RDF jargon) on the Web. An RDF document is a list of statements under the form of triples having the classical format: , where the elements of the triples can be URIs (Universal Resource Identifiers), literals (mainly, free text) and variables. RDF statements are normally written into XML format (the so-called ‘RDF/XML syntax’).
Semantic Web Rules: Still a ‘hot’ topic in a Semantic Web context. The present proposals (like RuleML, TRIPLE or SWRL) are based on an expansion of the classical ‘logic programming’ paradigm where the inferential properties of Prolog/Datalog are extended to deal with RDF/OWL knowledge bases. Examples of Semantic Web rules in RuleML are the ‘derivation rules’ (i.e., rules used to automatically defining derived concepts), the ‘reaction rules’ (for specifying the reactive behavior of a given system in response to specific events), the ‘transformation rules’ (used to implement translators between different versions of RuleML, and between RuleML and other rule languages like Jess), etc.
XML Schema: With respect to DTDs, a more complete way of specifying the semantics of a set of XML markup elements. XML Schema supplies a complete grammar for specifying the structure of the elements allowing, e.g., to define the cardinality of the offspring elements, default values, etc.
DTD (Document Type Description): A DTD is a formal description in XML Declaration Syntax of a particular type of document: it begins with a
Semantic Web Architecture: A layered architecture proposed by Berners-Lee for the Semantic Web applications. In this architecture, ontologies occupy a central place: they are built on the top of the RDF (Resource Description Framework) layer, which is in turn built on the top of the XML layer, see below. The XML/RDF base constraints the particular format ontologies assume in a Semantic Web context, inheriting, e.g., all the well-known XML ‘verbosity’.
XML (Extensible Markup Language): Has been created to overcome some difficulties proper to HTML (Hypertext Markup Language) that – developed as a means for instructing the Web browsers how to display a given Web page – is a ‘presentation-oriented’ markup tool. XML is called ‘extensible’ because, at the difference of HTML, is not characterized by a fixed format, but it lets the user design its own customized markup languages (a specific DTD, Document Type Description, see below) for limitless different types of documents; XML is then a ‘content-oriented’ markup tool.
OWL: The Web Ontology Language (OWL) is a semantic markup language for publishing and sharing ontologies on the World Wide Web. OWL is developed as a vocabulary extension of RDF and is derived from the DAML+OIL Web Ontology Language. An OWL ontology is an RDF graph, which is in turn a set of RDF triples. OWL includes three specific sub-languages, characterized by an increasing level of complexity and expressiveness, OWL Lite, OWL DL – DL(s) stands for Description Logics, a particular, logic-oriented, knowledge representation language introduced to supply a formal foundation for frame-based systems – and OWL Full.