**3.1 Representation of declarative knowledge**

At the beginning, the principle of seeing a simplified world was considered an abstraction of the real world to be modeled. Usually, the E-R principal is to be chosen.

The process of conceptualization has stabilized during the development of the means of modeling reality onto the well-established world view as a set of entities with certain characteristics and mutual relationships.

Now at first a generally recognized and application-proven way of using a formal language is given for the sake of building a formal description of concepts and their properties based on the basic (conceptual) level of the E-R model world abstraction [14]. Conceptualization is partially subordinated to the expected formal language syntax. The semantics of the language of knowledge represented in this way of seeing the world ought to be derived from declarative descriptions of the properties and relationships of the entities of the given reference world. They are then formally represented according to the rules applicable in the reference world. From anchoring corresponding concepts on the web or the semantic web, the current state of development has to choose the use of the principle of RDF modeling [15]. Using the RDF [15] data model representation gives a possibility of graphic representation of RDF triples [16] as vectors expressing corresponding knowledge elements (see **Figure 1**): <subject><property><object>.

RDF describes the resource (as a subject), which has some property with a corresponding value (object). The RDF model is based on associative (semantic) networks [17, 18].

In the following figure (**Figure 1**) we can see the conversion of the sentence "Marek teaches the subject of pgm languages." Clearly here we see that the subject is "Marek," the object is "pgm language," and the property is "teaches."

### **3.2 Representation of procedural knowledge**

The most successfully applied approach to the representation of procedural properties of the modeled world is the output of the process of algorithmic representation of the modeled reality, which builds a formal description of the reference world based on the graphic expression of the formalization—a flowchart of the basic elements of human activity in it.

Just as a formalization of declarative knowledge is guided by a conceptual flowchart, procedural knowledge [19] is the guiding factor of the problem of its algorithm, i.e., the way of seeing the process described based on elementary programming language components with special language syntax. The

#### **Figure 1.**

*Representation of the fact "Marek teaches the subject of pgm languages" using a RDF triple and with the help of RDF graph vectors.*

representative language used to simulate the performance of the modeled activity usually has a specific form of a programming language reflecting the characteristics of the modeled activity and the practical application needs.

*4.2.1 Definition*

or frame-like.

The knowledge pattern is a general type of component knowledge of proven success, often with a design concept of good practice, a process of structuring, to create the architecture of component knowledge. It may be declarative, procedural,

An anti-pattern is a common often accompanying process phenomenon that is not involved in solving the problem (wrong solutions or "worst-case" solutions). Unlike the model, the anti-model generally describes individual non-model cases

and highlights a general solution to recurring problems.

*Knowledge Patterns within the Conception of Semantic Web*

*DOI: http://dx.doi.org/10.5772/intechopen.88692*

composed, clearly defined, and described.

case of a declarative knowledge at its basic logical form.

more than a guideline on the application of a knowledge pattern.

derivation of a logical consequence from given assumptions.

that obtained a logical consequent from a knowledge base [4].

**knowledge patterns**

the semantic web.

**29**

**5. Rules of deduction in formal logics in the role of declarative**

The publication on formal logic and semantic web [4] lists several examples of the application of a resolution deduction rule as a knowledge model allowing the

The following example illustrates the use of RDF CFL resolution derivation rule

An example of immigration rules for Europe is given as a knowledge base in the language of the first-order predicate logic, which, as well known, is not one of the easy-to-understand and usable languages of formal logic. However, there is a way of transferring (according to well-known rules) to the special clause of CFL [24], which has been before based on conceptualization according to the RDF principle. To express its concepts and their properties and relationships, this language, on behalf of RDF CFL [25], uses exclusively the binary predicates. Consequently, a corresponding graphical representation has been used, playing an important role in

In its formal representation, the knowledge pattern should:

• Be anchored within a specific knowledge base with a given semantics.

• If possible be used for the formal representation of knowledge through a language with easy-to-understand interpretations (preferably graphical).

• Have individual atomic components, of which the pattern/anti-pattern is

**4.3 An example of a knowledge pattern for the case of declarative knowledge**

As an example of the knowledge pattern, we shall show in this paragraph the

In the field of formal logic [23], the declarative knowledge design pattern extends deep into the history of formal systems. At a time when philosophers and mathematicians changed their orientation from specific individual descriptions to general principles of reasoning, they came as a result of general principles of deduction in formal logics [23]. Procedures as a rule modus ponens or the resolution inference rule in propositional or predicate logic represent in terms of the ongoing development of artificial intelligence typically general guidance on how to derive from the assumption's logical consequences, respectively how to arrive at a logical deduction on the arguments that confirm or reject given assertions. This is nothing

Algorithms typically ignore entities with their properties and relationships, with the interconnection of modeling activities in the process providing "data," usually without any closer anchoring in entity representations. The problem solves the following frame approach of modeling.

#### **3.3 The framework character of knowledge**

Algorithmic representations of the modeled world with its procedural properties, as well as in the case of point 1, must take into a focus relation to elementary entities and their properties and relationships of a modeled world. It should, therefore, use a representation method based on the RDF model corresponding to point 1, with the terminology relating to entities with their properties and relationships being anchored in the chosen dictionary (ontology) to which access created by the RDF model [20] has been bound.

E.g. the language UML (as a means of describing RDF-modeled reality) would allow UML diagrams to data retrieve into the represented process and their belonging to home entities within the chosen ontology.

#### **4. Knowledge pattern in a semantic web context**

#### **4.1 RDF modeling principle and knowledge patterns**

Creating data for the semantic web means conceptualizing world using E-R model with a participation of a key ontology because of sharing and reusing formalized knowledge representation. Each data item can take its meaning from a standardized description of web resources within the proper ontology using its URI identifier.

#### **4.2 Semantic web patterns and anti-patterns**

The RDF as a general framework for describing, replacing, and reusing metadata represents the technological foundation of the semantic web. From anchoring corresponding concepts on the web (or the semantic web), the current state of development is the use of the RDF [4, 21] modeling principle.

RDF describes the resource, which has some properties, and these properties have corresponding values (**Figure 1**). While the subject defines the source, the property determines its nature and at the same time expresses the relationship between the subject and the object.

The semantic web idea is based on the RDF technology [22], which integrates the web language syntax and the naming of its elements by URIs. So a content presented on the semantic web has a well-defined meaning and allows a better understanding of both people and software agents.

The semantic web provides a common framework that allows data to be shared and reused.

It also emphasizes the ease of understanding and applicability of documents on the web, especially easy usability of knowledge model as well as knowledge pattern approach.

*Knowledge Patterns within the Conception of Semantic Web DOI: http://dx.doi.org/10.5772/intechopen.88692*

#### *4.2.1 Definition*

representative language used to simulate the performance of the modeled activity usually has a specific form of a programming language reflecting the characteristics

Algorithms typically ignore entities with their properties and relationships, with the interconnection of modeling activities in the process providing "data," usually without any closer anchoring in entity representations. The problem solves the

Algorithmic representations of the modeled world with its procedural properties, as well as in the case of point 1, must take into a focus relation to elementary entities and their properties and relationships of a modeled world. It should, therefore, use a representation method based on the RDF model corresponding to point 1, with the terminology relating to entities with their properties and relationships being anchored in the chosen dictionary (ontology) to which access created by the

E.g. the language UML (as a means of describing RDF-modeled reality) would allow UML diagrams to data retrieve into the represented process and their belong-

Creating data for the semantic web means conceptualizing world using E-R model with a participation of a key ontology because of sharing and reusing formalized knowledge representation. Each data item can take its meaning from a standardized description of web resources within the proper ontology using its URI

The RDF as a general framework for describing, replacing, and reusing metadata

RDF describes the resource, which has some properties, and these properties have corresponding values (**Figure 1**). While the subject defines the source, the property determines its nature and at the same time expresses the relationship

The semantic web idea is based on the RDF technology [22], which integrates the web language syntax and the naming of its elements by URIs. So a content presented on the semantic web has a well-defined meaning and allows a better

The semantic web provides a common framework that allows data to be shared

It also emphasizes the ease of understanding and applicability of documents on the web, especially easy usability of knowledge model as well as knowledge pattern

represents the technological foundation of the semantic web. From anchoring corresponding concepts on the web (or the semantic web), the current state of

development is the use of the RDF [4, 21] modeling principle.

of the modeled activity and the practical application needs.

*Ontological Analyses in Science,Technology and Informatics*

following frame approach of modeling.

RDF model [20] has been bound.

identifier.

and reused.

approach.

**28**

**3.3 The framework character of knowledge**

ing to home entities within the chosen ontology.

**4.2 Semantic web patterns and anti-patterns**

understanding of both people and software agents.

between the subject and the object.

**4. Knowledge pattern in a semantic web context**

**4.1 RDF modeling principle and knowledge patterns**

The knowledge pattern is a general type of component knowledge of proven success, often with a design concept of good practice, a process of structuring, to create the architecture of component knowledge. It may be declarative, procedural, or frame-like.

An anti-pattern is a common often accompanying process phenomenon that is not involved in solving the problem (wrong solutions or "worst-case" solutions). Unlike the model, the anti-model generally describes individual non-model cases and highlights a general solution to recurring problems.

In its formal representation, the knowledge pattern should:


#### **4.3 An example of a knowledge pattern for the case of declarative knowledge**

As an example of the knowledge pattern, we shall show in this paragraph the case of a declarative knowledge at its basic logical form.

In the field of formal logic [23], the declarative knowledge design pattern extends deep into the history of formal systems. At a time when philosophers and mathematicians changed their orientation from specific individual descriptions to general principles of reasoning, they came as a result of general principles of deduction in formal logics [23]. Procedures as a rule modus ponens or the resolution inference rule in propositional or predicate logic represent in terms of the ongoing development of artificial intelligence typically general guidance on how to derive from the assumption's logical consequences, respectively how to arrive at a logical deduction on the arguments that confirm or reject given assertions. This is nothing more than a guideline on the application of a knowledge pattern.
