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RDF Schema (RDFS, [Hayes04]) is a natural extension of RDF that adds a number of modeling constructs and increases expressing power to form a lightweight ontological language. Many RDF applications actually use RDFS and in many cases, including W3C specifications, these two standards are discussed together. Formally, RDF Schema defines several vocabulary terms mostly connected with classes and offers a new kind of interpretation that takes these into account.

Basic typing: With the introduction of classes came several ones that can be used in any RDFS graph — rdfs:Resource is the class for all things in the universe; rdfs:Class contains all classes (it is therefore true that rdfs:Class rdf:type rdfs:Class.); rdfs:Literal denotes literal values from LV; and rdfs:Datatype contains all literal values in datatyped interpretations.

Domains and ranges: Properties are associated with classes by rdfs:domain and rdfs:range restrictions. The subject of every triple must be a member of the domain class specified for the predicate, and its object must be a member of the class given by its range restriction.

Subclassing: Multiple inheritance of classes is expressed using rdfs:subClassOf. The formal definition is one of a subset: all members of a subclass must be members of its superclass.

In many ontological languages, properties exist independent of classes and have their own inheritance hierarchy. In case of RDFS, this is accomplished with rdfs:subPropertyOf. Both of the specialization concepts are transitive.

Containers: RDFS has properties and classes that contain the RDF container vocabulary. Thus, rdfs:Container is a superclass of rdf:Bag, rdf:Seq and rdf:Alt. Properties like rdf:_1 are subproperties of rdfs:member and members of the rdfs:ContainerMembershipProperty class (which itself is a subclass of rdf:Property).

Other urirefs: These urirefs actually lack any formal model-theoretic definition. Their intended meaning is as follows: rdfs:comment is used to insert arbitrary notes into RDF documents;

rdfs:seeAlso may contain a link to another RDF document and rdfs:isDefinedBy suggests that a given Semantic Web as an Object-oriented Database 35 document may contain the definition of a given uriref. Finally, rdfs:label is used to designate human-readable labels for urirefs.

–  –  –

4.3 OWL Several standards for defining data models of object-oriented databases were overviewed in the previous chapter; however, complex data models can be found even within the scope of the Semantic Web in the form of ontological languages.

According to a common definition from [GO94], “ontology is a formal specification of a shared

conceptualization”. Compared to object models, there are at least two important distinguishing aspects:

Ontologies attempt to capture a shared model that can be used, specialized, and exchanged by multiple parties, whereas object models mostly aim at a specific application and its implementation.

Ontologies are meant to be used for defining semantics of information about the real world that can be used for automatic inference of facts, while object models mostly focus on defining how to store and structure data, not what the data means [Fensel01].

Despite these differences, ontologies and object models actually use many identical or similar concepts.

That is why this section describes the object model of an ontological language from the same point of view as OODB standards earlier in the thesis.


OWL (Ontology Web Language) recently became a W3C recommendation that evolved from DAML+OIL [CvHH01], the connection of American DAML Semantic Web as an Object-oriented Database 36 (DARPA Agent Markup Language) and European OIL (Ontology Inference Language). Ontologies and knowledge bases built with OWL consist of definitions of classes, properties, individuals and constraints, and have the form of RDF graphs. As a whole, OWL is actually a collection of three

languages with increasing complexity:

OWL Lite, a simple language that mainly supports class hierarchies and several simple constraints such as cardinality of 0 and 1.

OWL DL (corresponding to description logics) includes the whole OWL vocabulary and is interpreted under several minor constraints, primarily type separation — the sets of individuals, classes and properties must be pairwise disjoint. Thanks to these constraints, OWL DL entailments are decidable.

OWL Full has the same vocabulary as OWL DL, but interpreted more broadly — like in RDF, a class can simultaneously be an individual. This and other differences are primarily of interest to the advanced user.

4.3.2 OWL DATA MODEL Specifications and Implementations. As an ontological language, OWL does not include implementation details. No behavior is specified and the semantics of types end at the class level.

An example of this is the treatment of elementary data types — their semantics is neither given nor enforced by OWL. A property can have type xsd:integer from XML Schema Datatypes but the fact that integers are numbers is given by semantics outside and beyond the scope of OWL itself.

Object Types. Individuals (instances, objects) can be grouped into classes. An object may belong in zero or more classes. These classes are used for classification, and their instances do not need to conform to any structural requirements. OWL DL also introduces intensional class definitions where a class is automatically populated with all individuals that have a given value of some property, and classes given by direct enumeration of their members.

Complex Classes. OWL DL allows the definition of classes using set operators like intersection, union and even complement. A restriction may require a pair of classes to be disjoint.

Subtyping and Inheritance. OWL supports unlimited multiple inheritance relationships with semantics that require the extent of a subconcept to be a subset of the superconcept’s extent.

Inheritance hierarchies can be specified among classes and properties alike.

Literals. Most objects or individuals are identified using a unique ID and assigned to a class, but datatypes with meaning specified outside of OWL can be used to represent property ranges like strings, numbers or evaluation types. A common set of datatypes is defined by XSD [BM00] — for example 123^^xsd:Integer in XSD denotes a number.

Metadata. In OWL, there is no difference between defining individuals and classes. Furthermore, OWL Full does not require data and metadata to be disjoint. Some metadata can also be stated about the whole ontology — its version, URI and the list of ontologies it imports (and extends).

Attributes and Relationships. These are called properties in OWL. Properties are defined independent of classes, although the domain and range of each property can be given or inherited by a subproperty, and property ranges for individual classes can be restricted. Properties can also have specific cardinality constraints or be an inverseOf another property.

Semantic Web as an Object-oriented Database 37 There are four kinds of properties in OWL — datatype properties correspond to attributes with elementary values, object properties correspond to relationships between objects, i.e. things with a unique ID. Annotation properties are used to attach arbitrary notes to things, and ontology properties connect and describe the ontology as a whole.

Furthermore, properties can have additional characteristics typical for ontologies. A transitive property denotes a transitive binary relation between individuals and the same is true of symmetric and functional (or inverseFunctional) ones.

Object Identity. Urirefs are used as unique IDs for objects, properties and individuals, same as in RDF. When serializing OWL into RDF, the following namespace is used: http://www.w3.org /2002/07/owl#. Restrictions are defined using anonymous classes, properties with specific simple features (like minimum cardinality), and named restrictions then inherit from these.

Object Equivalence. Since ontologies are meant to contain consensual information intended for sharing, reuse and extending, OWL provides the means to define that a pair of classes, properties or individuals with different urirefs has ientical (or different) semantics.

Object Lifetimes. OWL has no semantics for changing or updating ontologies; however, a versioning tag is provided in every OWL ontology as a hook for version control applications.

4.3.3 EXAMPLE OF FORMAL SEMANTICS As an ontological language, OWL has direct model-theoretic semantics. However, it also uses the RDF/S vocabulary and has RDF-compatible model-theoretic semantics, which enables it to function

as an extension of the RDF/S framework. These are shown in the following example:

The following account gives the semantics for the complementOf vocabulary term.

The triple xxx owl:complementOf yyy. is interpreted as follows:

∀xxx, yyy: IS(xxx),IS(yyy) ∈ IEXT(IS(owl:complementOf)) ⇒ {IS(xxx),IS(yyy)} ⊆ ICEXT(IS(rdf:Class) ∧ ICEXT(IS(xxx)) = IR − ICEXT(IS(yyy))


In 2001, DAML+OIL was submitted to the W3C as a basis for creating OWL, and a WebOnt working group was founded. After several drafts, the OWL specification reached the final stage and became a W3C recommendation in February 2004. A suite of tests for determining the (in)correctness of a number of OWL entailments was also released and its results for existing OWL implementations are dynamically updated in RDF online form. A month later, the OWL working group was dismissed with the claim that its goals have been accomplished.

At the same time, OWL is being implemented in a number of academic and commercial projects.

These include plugins for ontology design tools (such as Protégé), editors, support tools APIs and ontology suites. The W3C website mentions 13 existing reasoners in different stages of maturity with support for all three versions of OWL. Other developments can be found among syntax checkers, parsers, and complete ontologies (such as NCI cancer data).

4.3.5 SOURCES The official OWL Semantics document is [PHH04], and its creator, the WebOnt Working Group (now closed), can be found at http://www.w3.org/2001/sw/WebOnt/, where the other components of the official Semantic Web as an Object-oriented Database 38 OWL standard can be accessed. A new page dedicated to OWL adoption and implementations was established by W3C at http://www.w3.org/2004/OWL.

4.4 SOME RDF APPLICATIONS This section contains an overview of several applications for the Semantic Web based on RDF. Some of these are used in section 6.4 to demonstrate the model presented in this thesis on an example, and others are interesting because they work with RDF from the database perspective. Several other applications, which are only interesting if the reader wants to find out about how the Semantic Web was adopted by the industry, can be found in Appendix B.

4.4.1 CUSTOM RDF VOCABULARIES One of the main objections to the Semantic Web is that it has not gained wide adoption by the industry and there is no motivation for companies to publish RDF data. This section gives examples of several RDF vocabularies that are gaining wide acceptance as of the time of writing.


The Dublin Core Metadata Initiative (DCMI, http://www.dublincore.org/) is a set of "elements" (properties) for describing information resources (and hence, for recording metadata). It is now a NISO standard that has become widely used in documenting Internet resources, partly because it is very simple (the standard itself is about 3 pages long). Many new RDF vocabularies use or extend Dublin Core properties, which can be seen in the sections below.

The most recent set of Dublin Core elements is defined in [DC03]. Element definitions include recommendations for unambiguous typing of their values (in parentheses), which provides the elements with clear semantics.

Dublin Core contains definitions for the following properties:

Title, Identifier: A formal name of the resource and a unique identifier for the resource within its context (URI, URL, DOI, ISBN).

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