# Charting Past, Present, and Future Research in the Semantic Web and Interoperability
## 1 Introduction  
Globalization, collaboration, and co-operation have significantly altered the software industry and led to the sharing of knowledge in vast, open settings [1]. A single human user cannot develop competencies and knowledge unless he or she collaborates with other human users and businesses. Consequently, the difficulty of knowledge representation is elevated to a central position [2; 3]. Any user, including software agents, robots, smart devices, and humans, should use, generate, and exchange knowledge in expansive and heterogeneous environments. A common language and structure for expressing knowledge are utilized to address this issue. The semantic web as an infrastructure of computer-interpretable structured information [4; 5; 6] is a new technological development for describing and storing knowledge on the web [7; 8]. The semantic web arose from the desire to provide query and comparison capabilities for all World Wide Web data standardized by the World Wide Web Consortium (W3C), allowing it to link URLs to resources and classify specific knowledge domains. Semantic web technology derives meaning from a structured hierarchy of data classification, like an encyclopedia's collective volumes, and is used to develop knowledge domains. Classification techniques for unstructured data are the initial step toward defining quantitative and qualitative relationships between data so that they can be queried and analyzed using semantic web technologies. According to [9], the semantic web is an extension of the existing web, in which knowledge is assigned a well-defined and unambiguous meaning through ontologies [10; 11]. Ontologies are essential for achieving interoperability, as they provide structured vocabularies with a formal specification of shared concepts [12; 13; 14]. By providing a shared understanding of a particular topic of interest, ontologies aid in overcoming the problems caused by semantic heterogeneity. However, the most significant barrier to data integration and interoperability continues to be matching ontologies. The research on the semantic web demonstrates how ontologies can be utilized to resolve interoperability issues at the application level. Consequently, ontologies have been used during the discovery process to express the capabilities of the services. Similarly, ontologies improve user communication by defining the semantics of the symbolic representations used in the communication process. Numerous scholars have examined the applications of semantic web technologies in various fields. For instance, in education, ref. [15] argues that the semantic web's reliance on ontologies that provide machine-interpretable information can facilitate the realization of \"anybody, anytime, anywhere\" learning. Similarly, ref. [15] proposes developing a framework for personalized e-learning based on domain ontology and aggregate user profiles. The entire procedure is divided into two stages: offline, which includes data preparation, ontology development, and usage mining; and online, which includes the production of recommendations. The authors of [16] describe 18 ontologies based on different states of human behavior such as emotion, needs, and mood. According to the authors, ontology is the actual representation of knowledge in a format that a computer can easily interpret. The authors of [17] describe the evolution of linked data on the web and its applications. The authors illustrate several web-based data publication methods. Recognizing the interoperability issue between systems and applications, ref. [18] explains how to effectively leverage semantic web technologies (SWTs) to address security and interoperability issues. In addition, some academics have conducted research on semantic web applications in knowledge discovery and data mining. These include [19; 20], which summarize research on semantic web mining and demonstrate the efficacy of semantic web in enhancing web mining results. Similarly, ref.