72
R. P. França et al.
relationships of an infinite database, with the possibility of using specific languages
and tools to query and filter all this valuable content [55].
The concept of artificial intelligence is related to inference, which generates positive and negative expectations for future scenarios, enabling devices and systems,
from the information provided, to establish meaningful relationships. Which can
help, facilitating, and automating decisions that are exhausting and complex for
people. Within semantic web studies, the inference is the possibility of discovering new relationships between the terms used and their meanings, allowing new
relationships and automatic processes to establish new rulesets [56].
Finally, in the context of the Semantic Web, the most commonly used languages
are RDF, OWL, and SPARQL. Assessing that RFD was briefly created for modeling
and describing information in real-world entities and Web resources consisting of
making sentences about features in expression format subject-predicate-object type.
In this context, RFD enables making sentences about sentences and extensions that
allow working with classes, subclasses, and collections of instances, still providing
the term that assigns a type to a resource (rdf: type). SPARQL is a standardized RDF
query language, and concerning the OWL language. It was developed for descriptive
logical addition to the RDF language, consisting of a set of Knowledge Representation languages with a formal semantics based on their mapping in the First Order
Logic, extending the expressiveness of the RDF structure in the characterization of
classes and properties [22].
In turn, the Semantic Web content pages will move to meaningful (semantic)
pages allowing computers to perform more useful services through systems that
offer smarter relationships. The basis of this technology will be the ontologies that
allow nurturing meaning to content pages as well as relating them to each other. In
this scenario, computers will be able to execute queries through virtual agents that
find the desired information more quickly and accurately, together with providing
the possibility of inference about them and their relationships [32].
To give meaning to the traditional web that is based on static content pages
(HTML), it is necessary to adopt technologies such as RDF, or even the Resource
Description Framework Schema (RDF-S), or yet the Simple Knowledge Organization System Reference (SKOS). Which are descriptive languages of the content of
a page and work in conjunction with ontological languages like OWL, bringing out
structured knowledge allowing the use of search and inference agents [48].
5 Architecture Semantic Web
The architecture that synthesizes the Semantic Web conception focuses on understanding the technology that allows users to visualize its role in the semantic construction of the Web. Which over the years and with the evolution of studies, the architecture has undergone several changes and conceptions since the original design. By
aiming to highlight the reflexes of the new technological approaches of representation
and retrieval of information resources, as illustrated in Fig. 5 [48].
R. P. França et al.
relationships of an infinite database, with the possibility of using specific languages
and tools to query and filter all this valuable content [55].
The concept of artificial intelligence is related to inference, which generates positive and negative expectations for future scenarios, enabling devices and systems,
from the information provided, to establish meaningful relationships. Which can
help, facilitating, and automating decisions that are exhausting and complex for
people. Within semantic web studies, the inference is the possibility of discovering new relationships between the terms used and their meanings, allowing new
relationships and automatic processes to establish new rulesets [56].
Finally, in the context of the Semantic Web, the most commonly used languages
are RDF, OWL, and SPARQL. Assessing that RFD was briefly created for modeling
and describing information in real-world entities and Web resources consisting of
making sentences about features in expression format subject-predicate-object type.
In this context, RFD enables making sentences about sentences and extensions that
allow working with classes, subclasses, and collections of instances, still providing
the term that assigns a type to a resource (rdf: type). SPARQL is a standardized RDF
query language, and concerning the OWL language. It was developed for descriptive
logical addition to the RDF language, consisting of a set of Knowledge Representation languages with a formal semantics based on their mapping in the First Order
Logic, extending the expressiveness of the RDF structure in the characterization of
classes and properties [22].
In turn, the Semantic Web content pages will move to meaningful (semantic)
pages allowing computers to perform more useful services through systems that
offer smarter relationships. The basis of this technology will be the ontologies that
allow nurturing meaning to content pages as well as relating them to each other. In
this scenario, computers will be able to execute queries through virtual agents that
find the desired information more quickly and accurately, together with providing
the possibility of inference about them and their relationships [32].
To give meaning to the traditional web that is based on static content pages
(HTML), it is necessary to adopt technologies such as RDF, or even the Resource
Description Framework Schema (RDF-S), or yet the Simple Knowledge Organization System Reference (SKOS). Which are descriptive languages of the content of
a page and work in conjunction with ontological languages like OWL, bringing out
structured knowledge allowing the use of search and inference agents [48].
5 Architecture Semantic Web
The architecture that synthesizes the Semantic Web conception focuses on understanding the technology that allows users to visualize its role in the semantic construction of the Web. Which over the years and with the evolution of studies, the architecture has undergone several changes and conceptions since the original design. By
aiming to highlight the reflexes of the new technological approaches of representation
and retrieval of information resources, as illustrated in Fig. 5 [48].