Ontology-based technology

In the context of computer science, ontologies are the formal representation of knowledge including the concepts within a domain and the relationships between those concepts (Genesereth & Nilsson, 1987; Gruber, 1993). In more detail, ontologies are explicit, formalised and shared specification of the conceptualisation. By “explicit” it means that the concepts used and the restrictions applied to them are clearly defined. By “formalised” it means that a machine can process it. By “shared” it means that the knowledge acquired is a consensus of experts in the field. Conceptualisation is understood to be an abstract and simplified version of the world to be represented: a representation of knowledge based on objects, concepts and entities existing within the studied area, as well as the relationships existing among them, being in this research the domain of web accessibility for autistic users (Ruiz & Hilera, 2006). An ontology defines a common vocabulary to share information in a domain (Noy & McGuinness, 2001). It includes machine-interpretable definitions of basic concepts in the domain and relations between them. Ontologies support the annotation and integration of scientific data, allowing semantic integrations. The ability to exchange information between different applications means that the information may be made available to applications other than those for which it was originally created (W3C, 2014). An ontology must be able to answer natural language sentences, with “natural language” meaning day-to-day human language within a domain of expertise. These sentences are expressed as competency questions which are typical queries that an expert might want to submit to a knowledge base of a target domain (Gangemi & Presutti, 2009; Grüninger & Fox, 1995).

The resources described by ontologies are “individuals” (instances), “classes” (concepts), attributes and relations (Allemang & Hendler, 2011). Those resources can be anything from real word entities to abstract concepts (W3C, 2014). Ontology Web Language (OWL) is the family of representational languages that describe an ontology. It is the official language for defining ontologies on the web. OWL is a vocabulary extension of the Resource Description Framework (RDF) to model knowledge (Bechhofer, 2009). RDF is intended for situations in which information on the Web needs to be processed by applications, rather than being only displayed to people (W3C, 2014).

Resource Description Framework statements

The RDF statement is a triple set of resource (subject), property (predicate) and value (object), where the predicate expresses the relationship between the subject and the object. The relationship is phrased in a directional way (from subject to object) and is called in RDF a property. A simple expression is:

<Claudia><is-a><Person>

The resources ‘Claudia’ and ‘Person’ have a relation of ‘is-a’.

Each resource must be unique and use a Uniform Resource Indicator (URI), which is a generalisation of the Uniform Resource Locator (URL) – its global name on the Web. Continuing the example expressed with the use of Internationalized Resource Identifiers (IRIs), it will be:

<http://example.com/Claudia> <http://example.com/is-a> <http://example.com/Person>

An RDF graph is a mental model for RDF statements. Following the previous example, the graph would be as presented as follows in Figure 2.3.

Prefixes are used to allow the domain name of an IRI to be abbreviated for better readability. For example, if the URL http://example.com/ is abbreviated to ‘ex’, any resource with that URI can be abbreviated with that prefix. For example, http://example.com/Claudia can be abbreviated to ex:Claudia).

The programming language RDF Schema uses the notion of class to specific categories that can be used to classify resources. A class can have subclasses that represent concepts that are more specific (Noy & McGuinness, 2001). The relation between an instance and its class is stated through the type property. With RDF Schema one can create hierarchies of classes and sub-classes and of properties and sub-properties. Type restrictions on the subjects and objects of particular triples can be defined through domain and range restrictions (W3C, 2014).

Namespaces

A namespace is a unique URI. The World Wide Web Consortium W3C has defined a number of standard namespaces for use with Web technologies providing vocabulary definitions of terms used to express resources (Allemang & Hendler, 2011):

rdf: indicates identifiers used in RDF. The set of identifiers defined in the standard is used to define types and properties in RDF. The global URI for the rdf namespace is http://

www.w3.org/1999/02/22-rdf-syntax-ns#

rdfs: indicates identifiers used for the RDF Schema language, RDFS. The global URI for the rdfs namespace is http://www.w3.org/2000/01/rdf-schema#

owl: Indicates identifiers used for the Web Ontology Language, OWL. The global URI for the owl namespace is http://www.w3.org/2002/07/owl#

Expressing RDF data

Different syntax and file formats can be found in the market to express RDF data. The most common are N-Triples (.nt), Turtle (.ttl), JSON-LD (.json) or RDF/XML (.rdf), and all are supported by the main RDF libraries and triplestores. The personal preference of the author is the Turtle (ttl) format as it is commonly used between developers, and it is outlined in relevant books for programming the semantic web and has plenty of online support.

The ttl syntax provides for a compact representation of triple data. It begins with the first triple in subject/predicate/object order terminating with a period for single triple or a

semicolon to indicate that another triple with the same subject follows. For that triple, only the predicate and object need to be specified (since it is the same subject as before). These examples are created and further explained by (Allemang & Hendler, 2011).

Single triple in Turtle ttl:

Prefix mfg:

<http://www.WorkingOntologist.com/Examples/Chapter3/Manufacturing#> @prefix rdf: http://www.w3.org/1999/02/22-rdf-syntax-ns#

mfg:Product1 rdf:type mfg:Product .

Multiple triple in ttl:

mfg:Product1 rdf:type mfg:Product;

mfg:Product_Division “Manufacturing support”; mfg:Product_ID “1”;

mfg:Product_Available “23” . mfg:Product2 rdf:type mfg:Product;

mfg:Product_Division “Manufacturing support”; mfg:Product_ID “2”;

mfg:Product_Available “4” .

Turtle provides a compact way to express several triples that share both subject and predicate. Turtle uses a comma (,) to separate the objects. So the fact that Shakespeare had three children named Susanna, Judith and Hamnet can be expressed as follows:

lit:Shakespeare b:hasChild b:Susanna, b:Judith, b:Hamnet.

Commonly used vocabularies

One of the first RDF vocabularies used worldwide was the "Friend of a Friend" (FOAF) vocabulary for describing social networks. Other examples of RDF vocabularies are Dublin Core, schema.org and SKOS (Allemang & Hendler, 2011).

Dublin Core

The Dublin Core Metadata Initiative (Dublin Core Metadata Initiative DCMI, 2019) maintains a metadata element set for describing a wide range of resources. The vocabulary provides properties such as "creator", "publisher" and "title".

schema.org

Schema.org (Schema.com, 2019) is a vocabulary developed by a group of major search providers. The idea is that webmasters can use these terms to mark-up web pages so that search engines understand what the pages are about.

SKOS

SKOS is a vocabulary for publishing classification schemes such as terminologies and thesauri on the Web. SKOS has been recommended by W3C since 2009 and is widely used in the library world.

Query and rules-language

The predominant query language for RDF graphs is SPARQL. SPARQL is a set of specifications that provide languages and protocols to query and manipulate RDF graph content on the Web or in an RDF store. The Semantic Web Rule Language (SWRL) is a proposed language for the Semantic Web that can be used to express rules as well as logic (Horrocks et al., 2004).