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In 1989, Tim Berners-Lee wrote a proposal for an information management system at the CERN laboratory [BernersLee89]. This idea, which he called the Mesh, later became the World Wide Web. At its core was a set of graphs with (textual) objects connected by relationships that would serve as a central CERN library, help system, document repository, and reference manual. Depending on the type of graph, objects and relationships would represent different entities — people and subordination relationships, projects and dependence relationships, documents and reference relationships. This would enable automatic processing and reasoning with those graphs (see Figure 4.1).

Figure 4.1 An example from Tim Berners-Lee’s original WWW proposal [BernersLee89]

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humans, but without formal semantics — an information jungle that is hard to search, syndicate, organize, and machine-process. Even the area of Web Services struggles to express precise meaning1.

For a computer program, it is hard to tell that a HTML, or even an XML document is someone’s CV — in order to recognize it, text mining techniques dependent on specific vocabulary and language have to be employed. Web pages also lack formal machine-readable meaning, so it is almost impossible to automatically find out which of the numbers contained in the CV is the author’s date of birth, and which of the many links leads to the company where the person works, as opposed to links leading to their favorite e-shops.


The Semantic Web is a W3C (World Wide Web Consortium, http://www.w3.org/) activity that aims at extending the current World Wide Web with information that has well-defined meaning for both humans and computers. This would create an environment where "software agents roaming from page to page

can readily carry out sophisticated tasks for users" [BHL00]. The means to this end are in:

Presenting information in a structured and unambiguous way in contrast to today's Web pages that only define the form of their content, not its meaning.

Providing automatic inference abilities for software agents in order to enable intelligent reasoning, browsing, searching, and interconnecting the data.

A software agent was asked to set up an appointment with the doctor. Today the clinic's Web page might just contain keywords such as "treatment, medicine, physical, therapy", but the Semantic Web makes it possible to find out that Dr. Hartman works at this clinic on Mondays, Wednesdays and Fridays and that the appointment script takes a date range in yyyy-mm-dd format and returns appointment times. These semantics were encoded into the Web page using off-theshelf software along with standard terms listed on the Physical Therapy Association's site.

The agent “knows” that some of the terms are used by its calendar program so it sets up the appointment automatically. (Adapted from [BHL00]) At the core of the Semantic Web lies the RDF — Resource Description Framework that stores information in graphs where each edge represents a binary predicate. For uniqueness across the whole Web, both edges and nodes are labeled with URI references, or urirefs [BFM98]. RDF and RDFS (RDF Schema) also provide other features — see the following sections for more details. Semantics of new urirefs can be formally specified using existing sets of references, or model theory and RDF closures.


Most of the current Semantic Web research activities focus on the following areas:

Machine inference that selects relevant information, finds associations between facts, alerts to inconsistencies and uses rules to automatically draw conclusions — [PHH04], [Hayes04].

Web document annotation, intelligent searching and cataloguing — [DC03], [Karger04].

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Integration and communication of heterogeneous systems using ontologies — [Rohner04].

Creating an environment for intelligent autonomous agents — [CvHH01], [FIPA02].

4.2 MODEL–THEORETIC RDF SEMANTICS RDF (Resource Description Framework) is the foundational element of the Semantic Web. It provides a way of describing and connecting resources on the Web in graph form. On one hand, it is easy to understand, yet on the other, it has precise semantics that allow the possibility of automatic entailment between these graphs. The following explanation briefs the official W3C specifications, namely [Hayes04].

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4.2.1 BASIC RDF CONCEPTS RDF semantics is built on top of model theory based on stating facts (statements) about the world (or domain of discourse). In order to model what these statements mean, they need to be interpreted into the world. For every set of syntactic statements, there generally exists more than one interpretation that assigns a set of possible worlds to that set of statements. It is basically impossible to say everything about a world, describing it so there is no doubt about every possible detail within it; therefore, every elementary statement says something about the world, limiting the set of possible worlds that satisfy the model. To impose structure on the world we are describing, it is necessary to state enough facts to limit the set of possible worlds to those that satisfy our requirements.

In case of RDF, an elementary statement is a triple subject-predicate-object, where each of the three parts is assigned an identifier — a URI reference (for example http://www.w3.org/1999/02/22-rdf-syntax-ns#type).

Semantic Web as an Object-oriented Database 32

A statement that gives an e-mail address for a person might look like this:

http://www.fit.vutbr.cz/people/guttner http://www.w3.org/2000/10/swap/pim/contact#mailbox mailto:guttner@fit.vutbr.cz.

The notation used here is called N-Triples. The URI for the subject denotes a person here — not a document reachable through the http protocol. Name of the predicate is taken from a working W3C standard, and the e-mail address is standard mailto: URI reference.

Such statement can be modeled by an edge of a directed graph where a predicate labels the edge from a node denoted by the subject to the node denoted by the object. A set of statements forms a RDF graph. A set of possible worlds for such graph can be found by interpretation. Interpretation can either be a simple assignment of URI references to things in the domain of discourse, or, by defining additional semantic constraints on some of the URI labels, it can take into account some specific requirements. A set of urirefs that influences the semantics of a given interpretation is usually called a dictionary.

RDF also allows two extensions to the above-mentioned triple structure:

Both the subject and the object of a triple can be nodes that do not have an associated URI reference — blank nodes. Such nodes do not have any special meaning and the only requirement is that there exists an element in the domain of discourse that they can be mapped to (so all the statements in which they appear are consistent). In other words, blank nodes have the role of RDF existential quantifiers.

An object of a triple can also be a literal. This can either be an untyped string that denotes itself in any interpretation, or a typed literal — one example is "13"^^xsd:Integer. Typed literals are used in places where the meaning of a value can be unambiguously specified by a string (”13”) and a uriref (xsd:Integer). The semantics of these datatype urirefs is given by means external to RDF1.

4.2.2 A FORMAL DESCRIPTION Description of RDF semantics [Hayes04] states that for a set of URI references (a vocabulary) V that includes the RDF and RDFS vocabularies, and for a datatype theory T, a T-interpretation of V is a tuple I = IR, IP, IEXT, IS, IL, LV (elements of this tuple stand for Resources, Properties, Extensions, Semantic mapping, Literal mapping and Literal Values).

IR is called the universe and represents the world described by a RDF graph. It is a set of arbitrary elements that contains the denotations of urirefs from V. Another way to state this is that the semantics of URI references is given by elements in the universe that they map onto.

IP is a subset of IR and contains the denotations of all the properties from V. Properties are urirefs that are used to label the edges of RDF graphs, or predicates. In RDF interpretations, these are the extension of rdf:Property class.

IEXT is a mapping from IP, the set of properties, into 2IR×IR, and defines the extensions of properties. For every property in V, IEXT gives the set of all object-subject pairs that make this predicate true.

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IS is the foundational semantic mapping IS: V → IR that assigns denotations from the domain of discourse to URI references.

IL is the mapping from the set of typed literals to the set LV that is a superset of all untyped literals and a subset of IR.

The RDFS vocabulary interpretation also defines class extensions – for every c, it is the set ICEXT(c) = {x ∈

IR | x,c ∈ IEXT (IS(rdf:type))} and also the set of all classes IC = ICEXT(IS(rdfs:Class)). The rdf: and rdfs:

prefixes mean http://www.w3.org/1999/02/22-rdf-syntax-ns# and http://www.w3.org/2000/01/rdf-schema#, respectively. Such definitions are examples of special treatment of certain vocabulary terms.

Apart from these requirements, there are several more conditions that need to be true for every Tinterpretation — two examples are the requirement that extensions of all datatype classes must be subsets of LV and that IEXT(IS(rdfs:subClassOf)) is a transitive relation.

4.2.3 RDF/S VOCABULARIES The meaning of certain urirefs is fixed by the RDF and RDFS standards. For some of these, direct model-theoretic semantics are given to express their intended interpretation in a formal way, while others are described only informally (and therefore not used in subsequent chapters of this thesis).

This section presents a brief overview:


Semantic vocabulary: These urirefs must satisfy certain formal requirements that partially define their actual meaning — rdf:type is used for assigning individuals to their types, rdf:Property is a type of all urirefs used as predicates, rdf:nil and rdf:List serve as types for list structures, and rdf:XMLLiteral is for typing XML documents embedded in RDF graphs.

Reification vocabulary: RDF model theory is not expressive enough to be able to give formal background to this group of statements, although their meaning is quite clear. rdf:Statement is a type for individuals that represent or reify individual triples; rdf:subject, rdf:predicate and rdf:object are properties that denote the three elements of such triples.

Container vocabulary: Several types of containers can be constructed using standard RDF, but since this vocabulary is so limited, most “natural” assumptions concerning RDF containers are not formally sanctioned by the model theory. rdf:Seq is a type for ordered collections, rdf:Bag is used for unordered ones and rdf:Alt offers a choice among several alternatives. Members are connected to these containers with membership properties rdf:_1 rdf:_2 etc.

Collection vocabulary: RDF contains vocabulary for creating linked lists (of type rdf:List). Each node in such list contains an individual denoted by rdf:first and a connection to the rest of the list, rdf:rest. Lists are terminated by inserting an empty list at the end — rdf:nil. Note that in contrast to containers, linked lists can be constructed to only contain a given number of items. However, since this definition is only informal, a node that has several first and rest properties is still formally correct.

Semantic Web as an Object-oriented Database 34 my:library/shelf7

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rdf:value is intended to designate a single characteristic value when there is more than one possibility, but its precise meaning must be usually derived from the context.


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