Investigation of the Implementation Rate of Semantic Web Technology in Knowledge Management Software

The explosive growth of information and lack of structuring of information and the problems of information retrieval caused the emergence of the third generation of the web. The third generation of the web, which was called the semantic web, sought the connection between humans and computers and tried to make information understandable to machines. The Semantic Web, an extended version of the current Web, provides a standard structure for representing and reasoning with data. The semantic web is about sharing data and facts, not sharing the text of a page. The Semantic Web helps build the technology stack to support the "Web of Data" rather than the "Web of Document". The ultimate goal of the Web of Data is to enable computers to perform meaningful tasks and to develop systems that can support reliable network interactions (Patel & Sarika, 2021). Semantic web technologies can be used in various fields such as data integration, skill-finding, online think tanks, serving multimedia collections, and so on. Semantic web technologies can be used in various fields such as data integration, skill finding, online think tank, serving multimedia collections, and such things.
It seems that the use of the semantic web in KM software will certainly be effective in providing useful information. In KM, various software appeared, which in the context of KM, play an important role in the field of registration, distribution and sharing, application and use of information and knowledge, automation of processes, reduction of costs of acquisition, creation, organization, and application of a large amount of information and knowledge without time and place restrictions for people in organizations and companies, and causes changes in the methods of production, transfer and use of knowledge in them and prevent the entry and exit of unrelated and repetitive information and knowledge and improper processing of information and knowledge. Therefore, the aim of the current research is to investigate the implementation of semantic web technology in KM software.

 Over the past few decades, many technologies related to the Semantic Web have appeared or been developed. The World Wide Web Consortium (W3C), which works intensively on semantic standards, has endorsed the Resource Definition Framework (RDF) and the OWL Web Ontology Language (OWL), which provide a solid foundation for building semantic enterprise applications and Moving the Semantic Web from the research level partially led to its becoming the industry standard needed to build next-generation applications (Tjoa et al., 2005).
The Semantic Web is an extension of the current Web that improves machine-human interaction by giving information clear meaning. The idea of the Semantic Web is to hand over most of the tasks and decision-making to machines. This is made possible by adding knowledge to web content through machine-understandable language and creating intelligent software agents that can process this information. The Semantic Web, on the other hand, consists of structured information and explicit metadata, paving the way for rapid access to information and semantic search capabilities (Hassanzadeh & Keyvanpour, 2012). The semantic web was first introduced in 1988 by Tim Bernersley, known as the father of the web. But its definition was officially presented including seven-layer architecture in 2001. These seven layers include (URL), XML, (RDF), (Ontology), (Proof Layer), (Logic Layer) and (Trust Layer) (Gerber, Barnard & Van der Merwe, 2007).
The structure of the semantic web is a way of organizing data in a descriptive technology, RDF, which specifies data sources and their relationships, and identifies or names the resource's URAs, and OWL describes specifications. and data classes with a common language. Sparquel is a query language that searches RDF data. Another part of the Semantic Web is making sure that different databases use the same vocabulary to describe everything (Azimi & Rafieinasab, 2022).

The current research is applied, using a survey method and a descriptive approach. The statistical population of the current research is three KM software, which includes Dana KM software, Nedak comprehensive KM system, and MTA share software, which were investigated and analyzed. The data collection tool was also a checklist using a yes/no scale. After collecting the data and in order to confirm that the criteria of the Semantic Web, the checklist (questionnaire) was provided to the experts, and using their opinion, the presence or absence of the application of the Semantic Web capabilities in the KM software was confirmed. Finally, the obtained data were analyzed in Excel software.

Therefore, the present study shows that the architecture of semantic technology in all six layers (URL, XML, RDF, ontology, metadata, and logic) in all three software (Dana KM software, Nedak's comprehensive KM system, and MTA share software) is used and at a favorable level. But the semantic tools for searching and retrieving information in all three layers (ontology, RDF, metadata) in these types of software have not been used much and have not been paid attention to.

The results show that it is necessary to pay more attention to the application of semantic technology architecture in the comprehensive KM system software of Nadak and MTA share and to use them in all the mentioned layers. It is also necessary to use semantic tools for searching and retrieving information in any software called Dana KM, Nedak Comprehensive KM System in all layers (ontology, RDF, and metadata). In the field of application of web technology architecture, Dana's KM software is at a favorable level compared to the other two software.