**3.5 Swrl built-ins**

224 Semantics – Advances in Theories and Mathematical Models

datatype); there must be at least certain specific values; and there must be at least or at most

An inference process consists of applying logic in order to derive a conclusion based on observations and hypothesis. In computer science, interferences are applied through inference engines. These inference engines are basically computer applications which derive answers from a knowledge base. These engines depend on the logics through logic programming. The horn logic more commonly known Horn clause is a clause with at most one positive literal. It has been used as the base of logic programming and Prolog languages (Sterling, et al., 2009) for years. These languages allow the description of knowledge with predicates. Extensional knowledge is expressed as facts, while intentional knowledge is defined through rules (Spaccapietra, et al., 2004). These rules are used through different Rule Languages to enhance the knowledge possess in ontology. The Horn logic has given a platform to define Horn-like rules through sub languages of RuleML (Boley, et al., 2009). There have been different rule languages that have emerged in last few years. Some of these languages that have been evolving rapidly are Semantic Web Rule Language (SWRL) and Jena Rule. Both have their own built-ins to support the rules. With the actual work, SWRL language is used to rich the target concepts but it could be applied to others rule language

Semantic Web Rule Language (Valiente-Rocha, et al., 2010) is a rule language based on the combination of the OWL-DL with Unary/Binary Datalog RuleML which is a sublanguage of the Rule Markup Language. One restriction on SWRL called DL-safe rules was designed in order to keep the decidability of deduction algorithms. This restriction is not about the component of the language but on its interaction. SWRL includes a high-level abstract syntax for Horn-like rules. The SWRL as the form, *antecedent*→*consequent*, where both antecedent and consequent are conjunctions of atoms written a1 ... an. Atoms in rules can be of the form *C*(x), *P*(x,y), *Q*(x,z), *sameAs*(x,y), *differentFrom*(x,y), or *builtIn*(*pred*, z1, …, zn), where *C* is an OWL description, *P* is an OWL individual-valued property, *Q* is an OWL data-valued property, *pred* is a datatype predicate URI ref, x and y are either individualvalued variables or OWL individuals, and z, z1, … zn are either data-valued variables or OWL data literals. An OWL data literal is either a typed literal or a plain literal. Variables are indicated by using the standard convention of prefixing them with a question mark (e.g., ?x). URI references (URI refs) are used to identify ontology elements such as classes, individual-valued properties and data-valued properties. For instance, the following rule, equation 1, asserts that one's parents' brothers are one's uncles where parent, brother and

The set of built-ins for SWRL is motivated by a modular approach that will allow further extensions in future releases within a hierarchical taxonomy. SWRL's built-ins approach is also based on the reuse of existing built-ins in XQuery and XPath, which are themselves based on XML Schema by using the Datatypes. This system of built-ins should also help in the interoperation of SWRL with other Web formalisms by providing an extensible, modular built-ins infrastructure for Semantic Web Languages, Web Services, and Web applications

Parent(?x, ?p) ^ Brother(?p, ?u) →Uncle(?x, ?u) (1)

a certain number of distinct values.

based on Horn clauses.

uncle are all individual-valued properties.

(OConnor, et al., 2008).

**3.4 Semantic Web Rule Language (SWRL)** 

These built-ins are keys for any external integration. They help in the interoperation of SWRL with other formalism and provide an extensible infrastructure knowledge based applications. Actually, *Comparisons Built-Ins, Math Built-Ins and Built-Ins for Strings* are already implemented within lots of platform for ontology management like protégé. In the actual work, new processing and topological built-in for the integration of 3D processing and topological knowledge are integrated respectively.
