The role of semantic web in the big data process

Abstract

The Semantic Web presents a theoretical corpus and a range of technologies and applications that demonstrate its consistency, including in use of its concepts and its technologies in other scopes than the Web. In this sense, Big Data's projects can take advantage of the application of principles and developments in the area of the Semantic Web, to improve the processes of data analysis, especially in the insertion of semantic characteristics for data contextualization. Thus, this research aims to analyze and discuss the potential of Semantic Web technologies as a means of integrating and developing Big Data applications. An exploratory qualitative methodology was used, where we searched for points of the literature and documentary texts dealt with the convergence between the Semantic Web and the Big Data. Four main points were identified and discussed: the application of Linked Data as a data source for Big Data; the use of ontologies in data analysis; the use of Semantic Web technologies to promote interoperability in Big Data scenarios; and the use of machine learning to extract data automatically and convert them to Semantic Web standards. Therefore, it was possible to identify that the Semantic Web, especially with regard to its technologies, can help Big Data, since it provides a paradigm different from those applied mainly in data analysis.