نوع مقاله : مقاله پژوهشی
نویسندگان
1 استادیار، گروه علم اطلاعات و دانششناسی، دانشگاه شهید چمران اهواز، اهواز، ایران
2 دانشجوی دکتری علم اطلاعات و دانششناسی، دانشگاه شهید چمران اهواز، اهواز، ایران
چکیده
لایههای وب معنایی در حوزههای مختلف همچون تلفیق دادهها، مهارتیابی، اتاق فکر برخط، سرویسگذاری مجموعههای چندرسانهای، خرید برخط و تعامل بین سامانهها بهکار میرود. به نظر میرسد بهکارگیری وب معنایی در نرمافزارهای مدیریت دانش مسلماً در ارائه اطلاعات مفید مؤثر واقع خواهد شد؛ بنابراین هدف پژوهش حاضر بررسی میزان پیادهسازی فناوری وب معنایی در نرمافزارهای مدیریت دانش است. جامعه آماری پژوهش حاضر سه نرمافزار مدیریت دانش که شامل نرمافزار مدیریت دانش دانا، سامانه جامع مدیریت دانش نداک و نرمافزار MTA share است. دادهها از طریق تدوین سیاهه وارسی بر مبنای مقیاس بله/ خیر، گردآوری شدند و تجزیهوتحلیل دادهها نیز با کمک نرمافزار اکسل انجام شد. یافتهها نشان داد معماری فناوری معنایی در هر شش لایه (یوآرال، ایکسامال، آردیاف، هستیشناسی، فراداده و منطق) در نرمافزارهای مذکور، مورداستفاده و در سطح مطلوبی قرار دارد. ولی ابزارهای معنایی برای جستجو و بازیابی اطلاعات در هر سه لایه (هستیشناسی، آردیاف، فراداده) کاربرد چندانی در این نرمافزارها نداشته و موردتوجه قرار نگرفته است. لذا نتایج پژوهش حاضر نشانگر آن است که نیاز است کاربرد معماری فناوری معنایی در نرمافزارهای سامانه جامع مدیریت دانش نداک و MTA share بیشتر موردتوجه قرار گیرد و از آنها در تمامی لایههای مذکور استفاده شود. همچنین نیاز است که از ابزارهای معنایی برای جستجو و بازیابی اطلاعات در تمامی لایهها (هستیشناسی، آردیاف و فراداده) در نرمافزار مدیریت دانش دانا و سامانه جامع مدیریت دانش نداک استفاده بیشتری شود. با توجه به نتایج در بهکارگیری حوزه کاربرد معماری فناوری وب، در نرمافزار مدیریت دانش دانا نسبت به دو نرمافزار دیگر توجه بیشتری شده است.
کلیدواژهها
موضوعات
عنوان مقاله [English]
Investigation of the Implementation Rate of Semantic Web Technology in Knowledge Management Software
نویسندگان [English]
- Mohammad Hassan Azimi 1
- Hadi Alhaei 2
1 Assistant professor, Department of Knowledge and Information Science, Faculty of Education & Psychology, Shahid Chamran University of Ahvaz, Ahvaz, Iran
2 Ph.D Candidate in Knowledge and Information Science, Department of Knowledge and Information Science, Faculty of Education & Psychology, Shahid Chamran University of Ahvaz, Ahvaz, Iran
چکیده [English]
1. Introduction
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.
2. Literature Review
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).
3. Methodology
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.
4. Results
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.
5. Conclusion
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.
کلیدواژهها [English]
- Knowledge Management
- KM Software
- Semantic Web
- Semantic Web Technologies