Recent Developments of Semantic Web: Technologies and Challenges

Introduction

Ontologies are the foundation for organising linked data, and they play a critical role in establishing connections between datasets and across datasets. They provide users with the ability to search a schematic representation of all data included in the apps. We can integrate deep domain knowledge with raw data and connect datasets across domains by utilising ontology. Ontologies are attempts to more accurately categorise portions of data and to allow communication between data in different forms. Web ontology language is the global standard for exchanging ontologies and data on the Semantic Web. In the domain of the semantic web benchmarks, the database is not publicly appropriate since it is built in the direction of a relational data model. The set theory, which is a component of the Cartesian product, is the mathematical concept underlying the relational data model. On the other hand, the web ontology language data model offers a great deal of flexibility.

The concept of graph theory underpins the resource description framework (RDF). In addition, web ontology language is built on description logic, which contains DL expressions and axioms or restrictions. The semantic web would not be complete without a knowledge graph. Google created the term “Information Graph” in 2012 to describe any graph-based knowledge. Many other kinds of knowledge graphs exist, including DBpedia, Freebase, Open- Cyc, Wikidata, YAGO, and so on. In the end, extensive knowledge bases such as DBPEDIA and WIKIDATA are critical in addressing the issue of information overload. The idea of introducing semantics to web search is not apparent in an exclusive way. Other significant difficulties for the semantic web, which offers paths for researchers, include scalability, content availability, visualisation, ontology creation and evolution, multilingualism, and stability of semantic web languages.

Understanding Web queries and Web resources annotated with background information specified by ontologies and looking into the structured large datasets and knowledge bases of the semantic web as an alternative or a supplement to the current web are the two most common behaviours of semantic web technology. Semantic web technologies' wide range of applications enable them to help various areas such as sensor networks, big data, cloud computing, the Internet of Things, and so on. The learning scenario in e-Learning is completely different from traditional learning, in which the instructor serves as an intermediary between the learner and the learning material: instructors no longer control the delivery of material, and learners have the ability to combine learning material in courses on their own. In addition, learning processes must be quick and precise. Not only does speed need appropriate learning material content, but it also requires a strong method for organising that information (Yang, 2020) (Pereiro, 2020). E-learning should also be a personalised online solution based on user profiles and company needs. The above-mentioned criteria are not met by current web-based solutions. Information overload, a lack of reliable data, and material that is not machine-understandable are all potential problems.

The Semantic Web, the next generation of the internet, seems to be a viable technology for e-learning implementation. The major industrial firms, as well as academic and research institutions, have begun to seriously consider the use and applications of Semantic Web technology, in which machine-processable information can coexist and complement the current web, allowing computers and people to work together more effectively. The Semantic Web is a semantically based ecosystem in which human and machine agents may interact. Items may simply be grouped into personalised learning courses (quick and just-in-time) and provided to users on demand, based on their profile and company requirements. This article discusses e-Learning, including its advantages and needs, as well as the prospective applications of semantic web technologies in e-Learning. In the educational process, technology has always played a significant role. Radio, and subsequently television, were utilised as tools for distant education around the turn of the twentieth century.