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1. Introduction
The development of semantic technologies is associated with the realization of the idea for the semantic web. The purpose of the semantic web is to make it possible for the information available on the web to be processed by computers. Specifically, Web information can be described in a way that allows computers to be used not only for visualization but also for semantic interoperability and integration between systems and applications.
Resource description framework (RDF) is the W3C standard for creating descriptions of information. It is also suitable for presenting metadata for Web resources. RDF schema (RDFS) is an RDF extension that defines classes of resources, their properties, and relationships. Since RDF and RDFS are becoming increasingly popular among business and scientific environments, more and more RDF content is being created, and there is a need to standardize access to stored data. The language designed to allow RDF queries to be executed is SPARQL protocol and RDF query language (recursively referred to as SPARQL). Web ontology language (OWL) provides a language for defining structured web-based ontologies and allows richer integration and semantic data interoperability between communities and domains. One of the most important concepts related to the semantic web is so-called linked data. The goal is to publish structured data so that they can be easily linked to each other and be made more useful. Semantic web rule language (SWRL) is an OWL-based language that allows the compilation of rules that can be expressed in terms of OWL concepts to provide OWL with more powerful deductive reasoning.
Recent detailed research on the use of semantic technologies in various subject areas can be found, such as historical studies (Meroño-Peñuela et al., 2015); pervasive computing (Ye et al., 2015); robotics (Zander et al., 2016); Internet of things (Harlamova et al., 2017; Thoma et al., 2014); analysis of social networks (Bontcheva and Rout, 2014; Kulcu et al., 2016); online analytical data processing (OLAP) (Abelló et al., 2015); decision support (Blomqvist, 2014); digital libraries (Hallo et al., 2015; Pandey and Panda, 2014); archives and museums (Zeng, 2019); and science and education (Keßler et al., 2013; Tiropanis et al., 2009).
In Mitchell (2016), the adoption of linked data...