Analysis of Ordinal Survey Data

The use of ontology for different purposes in the context of information retrieval is based on the nature of the ontology used. Ontologies are implemented in a great variety of languages. The most representative languages are XML which has been adopted as a standard language used to exchange information on the web and along with some other languages as shown in the Figure 2.3.

i. XML

eXtensible Markup Language (XML) is used as data exchange format in different domains. It allows different parties to exchange data by providing common understanding of the basic concepts in the domain. Shabo (2006) described the syntactic level of XML but this lacks support for reasoning (semantics). Thus, problems arise when it is necessary to manipulate and integrate different XML data sources; therefore, organisations are shifting from a syntactic to a semantic level.

Ontologies are necessary to express the semantics of the data. The data sources are heterogeneous in syntax, schema, or semantics thus making data communication a difficult task. Syntactic heterogeneity is caused by the use of different models or languages. Schematic heterogeneity results from structural differences and is caused by different meanings or interpretations of data in various contexts. In implementing ontology, several languages have been created based on XML. These are discussed below:

ii. URI and Unicode

The Semantic Web is generally built on syntaxes which use Uniform Resource Identifier (URI) to represent data, usually in triples-based structures, that is many triples of URI data that can be held in databases or interchanged on the World Wide Web using a set of particular syntaxes developed especially for the task. These syntaxes are called "Resource Description Framework" syntaxes. Unicode allows supporting the international text style standard.

UNIVERSITY OF IBADAN LIBRARY

19

Figure 2.3: Semantic Web Layer Data Representation Standards

Trust

Proof

Logic framework

Rules

Ontology

RDF Schema

RDF

Signature Encryption

Namespace XML

Unicode URI

UNIVERSITY OF IBADAN LIBRARY

20 iii. RDF (Resource Description Framework)

Bray (2004) described XML meta-language as a standard based on meaning to map the information directly and unambiguously to a model. For processing metadata (data about data), Lassila and Swick (1999) developed the concept of RDF model which is used in a standardised way. It uses metadata format that permits to reason about data. It is used to capture and state the conceptual structure of information offered in the Web.

The RDF assertions (triples) of URIs are viewed as a data model for describing machine processable semantics of data to build the infrastructure for that which Tim Berners-Lee, the creator of WWW space, called the Semantic Web (Berners-Lee et al., 2001). Gil et al., (2005) and Daconta et al., (2003) suggested that to gain benefit of the full potentials of the Semantic Web, the main idea is to publish data as RDF, a common data annotation and representation.

iv. SPARQL

Data are accessed in the form of RDF triples in ontological knowledge bases. The SPARQL syntax is similar to that of the SQL query language for relational databases as the SELECT and WHERE clauses are employed to query data from an RDF graph. SPARQL queries are similar to the triple-form of RDF statements, except that each subject, predicate or object in the SPARQL query may consist of a variable.

v. RDF Schema

Brickley and Guha, (2000) developed a simple data-typing model for RDF which is RDFS which can model simple ontologies. Web resources process class hierarchies and properties with ranges and domains. This allows the quickly building up of knowledge databases in RDF. RDFs also contain a set of properties for annotating schemata, providing comments and labels and making them easy to be understood.

vi. FLogic

Kifer et al., (1995) introduce Frame Logic (FLogic) which provides a semantically founded knowledge representation based on the frame-and-slot metaphor. Another formalism that fits well with the structure of RDF is Conceptual Graphs. Corcho

UNIVERSITY OF IBADAN LIBRARY

21

(2001) provided a visual metaphor for representing the conceptual structure, where languages receive the name “classic languages”. It follows a syntax based on LISP (to the exception of FLogic).

vii. Web Ontology Language (OWL)

Dean and Schreiber (2003) introduce a more recent Web Ontology Language (OWL) which has become a popular standard for data representation and exchange and it is the language recommended by the W3C. The OWL supports the representation of domain knowledge using classes, properties and instances of the use in a distributed environment as the World Wide Web. OWL includes three sub languages discussed below:

i. OWL-Lite: It supports those users who primarily need a classification hierarchy and simple constraint features. For example, while OWL Lite supports cardinality constraints, it only permits cardinality values of 0 or 1. It should be simpler to provide tool support for OWL Lite than its more expressive relatives, and provide a quick migration path for thesauri and other taxonomies.

ii. OWL-DL: OWL-Description logic (DLs) is the popular framework and it is the first order logic which aims at being expressive while retaining computational completeness. That is, all conclusions are guaranteed to be computed and decidable (all computations will finish in finite time). Baader et al. (2003) suggested OWL which influences quite a number of sources but its main representational facilities are directly based on Description Logics.

OWL-DL provides a compromise supported by reasonably efficient reasoners and a language that can express large classes of ontologies and knowledge.

Due to these advantages over others OWL language is used as language representation for the two domains in this research work.

iii. OWL Full: This is used by users who want maximum expressiveness and the syntactic freedom of RDF with no computational guarantees. For example, in OWL Full, a class is treated simultaneously as a collection of individuals and as an individual in its own right. Another significant difference between OWL-DL and OWL Full is that owl:DatatypeProperty is marked as an

UNIVERSITY OF IBADAN LIBRARY

22

owl:InverseFunctionalProperty. OWL Full allows an ontology to augment the meaning of the pre-defined RDF or OWL vocabulary. It is unlikely that any reasoning software will be able to support every feature of OWL Full.