Documents

Visual knowledge mapping simplifies the process of knowledge search and processing that helps to find potential partners for joint projects, and organization management to facilitate the processes of decision making more effectively. The article proposes a new approach to university teachers’ knowledge mapping. The approach is based on ontology engineering and extensive use of bibliometric analysis. As part of the proposed framework, a set of ontologies was created to describe the scientific activity of a faculty member in terms of his competencies and performance indicators. Then the BIB-METR visualization system was created to collect and visualize information about faculty members and researchers. The proposed approach was justified on the sample of one department of the university-based business school. The developed ontology works as a skeleton of a multidimensional portrait of university faculty member in the part of their research activity. And the set of such portraits generates the information research landscape of the university.
Translated title of the contributionМеждународный симпозиум «Знания Онтологии Теории» : Мультиконф. по инженерным, компьютерным и информационным системам
Original languageEnglish
Title of host publicationInternational Symposium on Knowledge-Ontology-Theory KNOTH2024
Subtitle of host publicationwithin IEEE International Multi-Conference on Engineering, Computer and Information Sciences (SIBIRCON)
Place of PublicationНовосибирск
Pages334-339
Number of pages6
StatePublished - 2024
Event International Symposium on Knowledge-Ontology-Theory : 2024 IEEE International Multi-Conference on Engineering, Computer and Information Sciences (SIBIRCON). - Новосибирск, Russian Federation
Duration: 30 Sep 20242 Oct 2024
https://knoth.ru/

Conference

Conference International Symposium on Knowledge-Ontology-Theory
Abbreviated titleKNOTH2024
Country/TerritoryRussian Federation
CityНовосибирск
Period30/09/242/10/24
Internet address

    Research areas

  • ontology, visualization system, bibliometric data analysis, bibliometrics, knowledge maps

    Scopus subject areas

  • Computer Science(all)

ID: 126786100