Semantic Web

2.2.1 Semantic Web

University of the World Wide Web is its vital property. The concept of hypertext link implements that “anything can link to anything”. The Web has been developed most rapidly as a medium of documents for people rather than for data. People can understand what the document means over internet, but machines can’t. To let data be processed by machines automatically, we must enable machines understanding what documents mean over internet. The Semantic Web aims to make up for this problem [28].

“The first step is putting data on the Web in a form that machines can naturally understand, or converting it to that form. This creates what I call a Semantic Web-a web of data that can be processed directly or indirectly by machines,”by Tim Berners-Lee. The creator of Web, Tim Berners-Lee, has a two-part vision for the future of the web. The first part is to make the Web a more collaborative medium. The second part is to make the Web understandable, and thus processable, for machines.

Figure 2-6 shows Tim Burners-Lee’s diagram of his proposed vision to CERN (European Organization for Nuclear Research)[33].

Figure 2-3 Original Web Proposal to CERN[33]

In Figure 2-3, we see the relations like “includes,”“describes,”and “wrote”

between information items. Unfortunately, these relationships between resources are not currently defined on the Web. Tim Burners-Lee’s vision is to describe relationships between objects over the internet. Further, he proposed the concept of semantic web. The technology that captures such relationships is called the Resource Description Framework (RDF) described later.

For the consideration of data, usually, software is totally dependent on good data.

The computing experts realize that data is important and must be verified and protected. Therefore, with the Web, Extensible Markup Language (XML), and now the emerging Semantic Web, the power shifts from applications to data. This also gives us the key to realize the Semantic Web. The path to machine-processed data is to make the data smarter. The objective of Semantic Web is to enable machines to understand what data means because data is made smarter. Figure 2-4 displays the progression of data along a continuum of increasing intelligence.

Figure 2-4 The Smart Data Continuum[19]

In the first two stages, data isn’t smart in various domains. It is till the stage 3 that the relationship of data can be used to relate and combine data. Hence, data is smart now to be easily discovered and combined with other data. In stage 4, data can be inferred with existing data by following logical rules. Now data can be processed more intelligently and can build other relationship between data [19].

After the introduction of Semantic Web, we may wonder how to make Semantic Web. Semantic Web is generally built on syntaxes which use URIs to represent data, usually in triple-based structures. Many of URI data that is held in databases, or is interchanged on the World Wide Web uses a set of particular syntaxes developed especially for the task. These syntaxes are called “Resource Description Framework”

(RDF) syntaxes.

 URI-Uniform Resource Identifier

A URI is simply web identified: like the strings starting with “http:”or “ftp:”

that often are found on the World Wide Web. URI enable people or machines to know where the resource is located. In fact, the World Wide Web is such a thing: anything that has a URI is considered to be “on the Web”.

The syntax of URI is carefully governed by the IETF, who published RFC 2396 as the general URI specification. The W3C maintains a list of URI schemes [4].

 RDF

A triple can simply be described as three URIs. A language which utilizes three URIs in such a way is called RDF [4]. The Resource Description Framework (RDF) is an XML-based language to describe resources. Resource on the Web is usually accessed via a Uniform Resource Locator (URL). While the metadata is attached as the part of XML document, one use of RDF is to build metadata about the document as a standalone entity. In other words, instead of marking up the internals of a document, RDF apprehends metadata about the “externals”of a document, like the author, the creation date, and type [19].

Here is an example of XML RDF:

<rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"

xmlns:dc="http://purl.org/dc/elements/1.1/"

xmlns:foaf="http://xmlns.com/0.1/foaf/" >

<rdf:Description rdf:about="">

<dc:creator rdf:parseType="Resource">

<foaf:name>Sean B. Palmer</foaf:name>

</dc:creator>

<dc:title>The Semantic Web: An Introduction</dc:title>

</rdf:Description>

</rdf:RDF>

This piece of RDF means that this article has the title “The Semantic Web: An Introduction,”and was written by Sean B. Palmer. RDF produces the triples like the following [31]:

<> <http://purl.org/dc/elements/1.1/creator> _:x0 .

this <http://purl.org/dc/elements/1.1/title> "The Semantic Web: An Introduction" .

_:x0 <http://xmlns.com/0.1/foaf/name> "Sean B. Palmer"

Hence,theRDF modelisoften called a “triple” becauseithasthreeparts.Those three components are described in terms of the grammatical parts of one sentence:

subject, predicate, and object. Figure 2-5 displays the elements of triple model.

Figure 2-5 RDF Triple[9]

Subject: Subject of the sentence tells us what the sentence is about. In logic, this is the term about which something is asserted. In RDF, this is the resource that is described by the ensuring predicate and object.

Predicate: In one sentence, predicate tells us something about the subject. In logic, a predicate is a function from individuals to truth-values with an entity based on the number of arguments it has. In RDF, a predicate is like a relation between the subject and the object.

Object: With logic, an object is acted upon by the predicate. In RDF, an object is either a resource referred to by the predicate or a literal value.

 RDF Schema

RDF schema is the language layered on top of RDF. The stack of Semantic Web is shown in figure 2-6. The bases of the stack are URI and Unicode. Above those concepts, we layer the XML syntax and namespaces to prevent vocabulary conflicts.

On top of XML are the RDF and syntax discussed in the previous section. If we want to use the triple to denote a class, class property, and value, we can build class hierarchies for the classification and description of objects. This is the goal of RDF schema.

Figure 2-6 Semantic Web Stack[10]

RDF Schema is a simple set of standard RDF resources and properties to enable people to create their own RDF vocabularies. RDF Schema allows you to create classes of data. A class is defined as a group of things with common characteristics.

An object is one instance of a class [19]. It also allows classes to inherit characteristics and behaviors from a parent class.

Otherwise, the concept of an RDF property is view as a relation between subject resource and object resource.

Table 2-1 presents an overview of the vocabulary of RDF, drawing together vocabulary originally defined in the RDF Model and Syntax specification with classes and properties that originate with RDF Schema [4].

Table 2-1 RDF Classes

Class name comment

rdfs:Resource The class resource, everything.

rdfs:Literal The class of literal values, e.g. textual strings and integers.

rdf:XMLLiteral The class of XML literals values.

rdfs:Class The class of classes.

rdf:Property The class of RDF properties.

rdfs:Datatype The class of RDF datatypes.

rdf:Statement The class of RDF statements.

rdf:Bag The class of unordered containers.

rdf:Seq The class of ordered containers.

rdf:Alt The class of containers of alternatives.

rdfs:Container The class of RDF containers.

rdfs:ContainerMembershipProperty

The class of container membership properties, rdf:_1, rdf:_2, ..., all of which are sub-properties of 'member'.

rdf:List The class of RDF Lists.

Table 2-2 RDF Properties

Property name comment domain range

rdf:type The subject is an instance of

a class. rdfs:Resource rdfs:Class

rdfs:subClassOf The subject is a subclass of

a class. rdfs:Class rdfs:Class

rdfs:subPropertyOf The subject is a subproperty

of a property. rdf:Property rdf:Property rdfs:domain A domain of the subject

property. rdf:Property rdfs:Class

rdfs:range A range of the subject

property. rdf:Property rdfs:Class

rdfs:label A human-readable name for

the subject. rdfs:Resource rdfs:Literal rdfs:comment A description of the subject

resource. rdfs:Resource rdfs:Literal

rdfs:member A member of the subject

resource. rdfs:Resource rdfs:Resource

rdf:first The first item in the subject

RDF list. rdf:List rdfs:Resource

rdf:rest The rest of the subject RDF rdf:List rdf:List

list after the first item.

rdfs:seeAlso Further information about

the subject resource. rdfs:Resource rdfs:Resource rdfs:isDefinedBy The definition of the subject

resource. rdfs:Resource rdfs:Resource

rdf:value

Idiomatic property used for structured values (see the RDF Primer for an example of its usage).

rdfs:Resource rdfs:Resource

rdf:subject The subject of the subject

RDF statement. rdf:Statement rdfs:Resource rdf:predicate The predicate of the subject

RDF statement. rdf:Statement rdfs:Resource rdf:object The object of the subject

RDF statement. rdf:Statement rdfs:Resource [Fromhttp://www.w3.org/TR/rdf-schema/]

2.2.2 Ontology

In philosophy, ontology is a theory of thing existence [28]. For AI systems, what

“exists”is that which can be represented. When the knowledge of a domain is represented in a declarative formalism, the set of objects that can be represented is called the universe of discourse. This set of objects, and the describable relationships among them, are reflected in the representational vocabulary with which a knowledge-based program represents knowledge. In the context of knowledge sharing, ontology means a specification of conceptualization [32].

The Artificial-Intelligence literature contains many definitions of ontology;

many of these contradict one another [23]. For the purposes of this guide an ontology is a formal explicit description of concepts in a domain of discourse (classes), properties of each concept describing various features and attributes of the concept (slots), and restrictions on slots (facets). An ontology together with a set of individual instances of classes constitutes a knowledge base. In reality, there is a fine line where the ontology ends and the knowledge base begins.

The important feature of ontology is the inference facility. Machines usually

don’t realize any of information, but it can deal with the terms through ontology and reason rules. There are many applications to use ontology to enhance the functioning of the Web. More advanced applications use ontology to relate the information on one page and retrieve more knowledge via inference rules.

2.2.3 OWL

The Semantic Web is the future of the Web. It gives data meaning and enables machines to automatically process data. The Semantic Web will build on XML’s ability to define customized tagging schemes and RDF’s flexible way to presenting data. The first level above RDF is an ontology language that can represent the meaning of terminology in Web document. To lat machines to perform useful reasoning tasks on these documents, the language must go beyond the basic semantics of RDF schema.

OWL is one language of ontology and is intended to be used when information contained in documents needs to be processed by applications. OWL has more power than XML, RDF, and RDF-S to express meaning and semantics. OWL can be used to explicitly represent the meaning of terms in vocabularies and the relationships between those terms. OWL is a revision of the DAML+OIL web ontology language incorporating lessons learned from the design and application of DAML+OIL.

2.2.4 OWL-S

OWL-S (formerly DAML-S) is an OWL-based Web service ontology that supplies web service providers with a core set of markup language constructs for describing the properties and capabilities of their Web services in unambiguous, computer-interpretable form. The latest 0.9 draft release is expected to be the last one built on DAML+OIL, and the later releases will be based on OWL.

OWL-S, the ontology of Web services, is to provide three essential types of knowledge about one web service (Shown in Figure 2-7).

Figure 2-7 The Components of OWL-S[6]

The class “Service”is viewed as an organizational point of reference for declaring Web services; for different published service, one instance of Service will exist. The subclasses of one web service are Service Profile, Service Model, and Service Grounding. Each instance of Web service will present a descendant class of Service Profile, be describedBy a descendant class of Service Model, and supports a descendant class of Service Grounding. The details of profiles, models, and groundings are different each other. But those three components provide the essential type of information about Web service, as described latter.

A service profile tells“whattheservicedoes”;it provides types of information that are needed by matchmaking agents to determine which service meets their requirements. Otherwise, service profile also can represent the requirement the matchmaking agent needs. Therefore, service profile is the dual-purpose representation for the matchmaking process.

A servicemodeltells“how theservice works”;thatis,itdescribeswhathappens when the service is carried out. For nontrivial services (those composed of several steps over time), this description may be used by a service-seeking agent in at least four different ways: (1) to perform a more in-depth analysis of whether the service meets its needs; (2) to compose service descriptions from multiple services to perform

a specific task; (3) during the course of the service enactment, to coordinate the activities of the different participants; and (4) to monitor the execution of Web service.

Service grounding defines the details of how to access a service. The definition usually includes a communication protocol, message formats, and other service-specific details like port numbers for contacting the service. Otherwise, the service grounding must specify the precise way of exchanging data elements of the type with the service [6].

In other words, Service Profile contains essential information for matchmaking agent to discover Web services. Service Model and the Service Grounding are associated with a Web service to provide enough information for making use of a service.