Components of The Semantic Web

The semantic web is a term coined by Sir Timothy Berners-Lee which refers to a set of standards that enables data to be shared and reused easily across applications (Wikipedia n.d) It is an extension of the world wide web that gives information well-defined meaning and enables people and computers to work cooperatively (Berners Lee et al., 2001). The semantic web promotes the use of standardized formats and protocols to create and exchange data across multiple programs. (Antoniou et al 2008) regarded semantic web as an approach that would enable web content to be represented in a form that is easily machine-processable. Representing content in this format enables computers to process, store, manage and retrieve information based on meaning, importance and logical relations (Ontotext n.d) These enables Contents stored and accessible on the web are presented in a format that is easy for humans to read, process and understand. The vision of the semantic web is to allow the effective sharing of data that can be processed and consumed by tools manually or automatically (Saraf, 2008). The semantic web consists of key components that form the building blocks for the system to run effectively i.e. SPARQL, RDF, URI, UNICODE, XML that would be explained in detail.

Components of the Semantic Web

Unicode: The Unicode is a standardized format for encoding and manipulating computer text regardless of language to make it compatible with all types of software. The latest version of UNICODE consists of over 136,000 characters from 139 contemporary and historic scripts.

Uniform resource identifier (URI): This is a string of characters used to identify and locate resources. They provide the basis of finding web pages across the internet.

Resource Description Framework (RDF): RDF is a general model for data exchange on the web. While the Extensible Markup Language (XML) enables users to add subjective structure to their documents but does not define what the structure means, the RDF aims to define what these structures mean. It makes web data more versatile and can be compared to do what catalogue cards do for library books, this makes data retrieval faster and more accurate (Bosak et al, 1999). The standard determines how information is described or modelled within the web (Hayes, 2004).

The RDF consists of three Key Concepts which are regarded as the RDF triple.

• Resources: This can refer to a specific item or resource that is being discussed. This could be something like a specific laptop
• Properties: This describes the relationship between resources. This could be the laptop “is a” Windows.
• Statements: This provides the value of the resources. An example is the laptop is “14-inch screen size”.

RDF Schema (RDFS): This is a basic type of modelling language that describes different classes of properties that can apply to different types of resources in the basic RDF model. It gives a simple structure to derive different types of resources.

Simple Protocol and RDF Query Language (SPARQL): Pronounced as “sparkle” is a querying language for RDF. It is designed to specifically query data across multiple platforms and to retrieve and process data which is stored in RDF format (Ontotext n.d)

Extensible markup language (XML): This term can simply be termed as language for marking messages and documents with tags to make machines easily analyse data (Pollock 2009). XML is a mark-up language that supports Unicode which provides a standardized format for storing text based data in a human and machine-readable format (Dykes et al, 2005). Conolly et al (2010) regarded XML as a metalanguage (a language used for the description of other languages), which provides a better functionality than HTML.

XML is one of the tools used in the provision of syntax for expressing data models in semantic web technologies. Other tools can be used to provide syntax which doesn’t make XML an essential part of semantic web technologies, but it leverages itself on the design goal which emphasizes general usability and simplicity across the internet. This simplicity makes XML a popular choice. Conolly et al (2010) echoed this sentiment by stating that “Some analysts believe that it will become the language in which most documents are created and stored, both on and off the Internet” (Connolly et al 2010: 1138). XML allows data to be stored comfortably, searched easily and sent around corresponding networks efficiently.

Software AG, a vendor of XML tools stated the benefits of XML and why companies are adopting and using XML

• Simplicity: Information coded using XML is processed easily by computers and very easy for humans to read and understand.
• Openness: XML is endorsed by industry market leaders because it is a W3C standard
• Extensibility: XML has no fixed set of tags which allows users to create new tags to suit specific requirements
• Adoption Rate: XML has been adopted by top companies such IBM, Microsoft, SAP
• Embedding Existing Data Structures or relational database is simple and fast using XML
• Reuse: XML tags can be repurposed multiple times.
• Support for Metatags and Metadata: XML contains information which helps in describing its own data, this makes it easier for computer systems to use and comprehend the data

Ontology: In Semantic web and information architecture, knowledge representation about a domain of information in electronic form is achieved using ontologies (Harpring, 2010). Ontologies can also be described as a formal and explicit description of a shared concept (Gruber, 1993).

Ontology Web Language (OWL) “allows for defining classes hierarchies, relations between classes and subclasses, properties, associations between classes, properties domain and range, class instances; equivalent classes and properties; restrictions, and so on”. (Gladun et al., 2009). Ontology was designed to reduce lexical misunderstandings that occurs to specific domains. This is done by characterizing and defining a set of concepts that compromises a domain and explaining the relationship between the concepts (Ta et al 2015).

An Ontology composes of multiple components but they key concepts would be stated below:

• Classes: This describes the concept in a domain. A class in an ontology created for the company could be called ‘Laptops’. A class named ‘Laptops’ would represent all the laptop in the company’s inventory.
• Individuals/Instance: This are specific objects within classes. An example would be ‘windows’ being an Instance of the ‘Laptop’ class. ’14-inch screen size’ would be an instance of ‘windows’.
• Taxonomic Hierarchy: This is making appropriate classes and sub classes. I.E ‘Laptop’ class has a subclass called ‘windows’. This means every instance of ‘windows’ would be a subclass of ‘tools’