Research output: Chapter in Book/Report/Conference proceeding › Article in an anthology › Research › peer-review
Ontology-based Methodology for Knowledge Maps Design. / Гаврилова, Татьяна Альбертовна; Алканова, Ольга Николаевна; Кузнецова, Анна Вениаминовна.
Proceedings of the Seventh International Scientific Conference “Intelligent Information Technologies for Industry” (IITI’23). IITI 2023. ed. / Sergey Kovalev; Andrey Sukhanov; Igor Kotenko. Springer Nature, 2023. p. 250-259 (Lecture Notes in Networks and Systems; Vol. 776, No. 23).Research output: Chapter in Book/Report/Conference proceeding › Article in an anthology › Research › peer-review
}
TY - CHAP
T1 - Ontology-based Methodology for Knowledge Maps Design
AU - Гаврилова, Татьяна Альбертовна
AU - Алканова, Ольга Николаевна
AU - Кузнецова, Анна Вениаминовна
N1 - Conference code: 7
PY - 2023
Y1 - 2023
N2 - Visualization of corporate knowledge in organizations creates thepotential for a significant improvement in the quality of decision making andmanagementefficiency. However, at the moment there is little correlation between theneeds of enterprises and new technologies in the field of knowledge engineering.Models and methods of knowledge visualization are not yet mature enough tosolve practical problems of information and knowledge management. This is especiallytrue for knowledge-intensive enterprises and organizations, universities, andresearch institutes. The paper presents a new methodology for the knowledge andcompetences mapping of the faculty members (or any employees). The methodologyis supported by the ontology-based approach and significantly expandsthe traditional knowledge engineering palette of methods. Ontologies as conceptualmodels of the subject areas are one of the most promising approaches to thedevelopment of knowledge bases and knowledge graphs. The importance of ontologyengineering is rapidly gaining the new adopters. The proposed methodologyconsists of 4 main meta-steps to create a knowledge map:• Set of ontologies design (ON);• Knowledge elicitation for ontology population (E);• Visual knowledge mapping (VI);• Knowledge map justification and dissemination (D).The proposed ONE-VID approach was implemented at Graduate School ofManagement in Saint-Petersburg State University for the sample of 63 facultymembers. Several types of K-maps were designed and developed – treemaps,radars, knowledge profiles, etc.The paper describes the new methodology and illustrates the first results. Thesubsequent longitude study plan is considered that will give the possibility tocompare the specific knowledge profiles and gaps as time passes.
AB - Visualization of corporate knowledge in organizations creates thepotential for a significant improvement in the quality of decision making andmanagementefficiency. However, at the moment there is little correlation between theneeds of enterprises and new technologies in the field of knowledge engineering.Models and methods of knowledge visualization are not yet mature enough tosolve practical problems of information and knowledge management. This is especiallytrue for knowledge-intensive enterprises and organizations, universities, andresearch institutes. The paper presents a new methodology for the knowledge andcompetences mapping of the faculty members (or any employees). The methodologyis supported by the ontology-based approach and significantly expandsthe traditional knowledge engineering palette of methods. Ontologies as conceptualmodels of the subject areas are one of the most promising approaches to thedevelopment of knowledge bases and knowledge graphs. The importance of ontologyengineering is rapidly gaining the new adopters. The proposed methodologyconsists of 4 main meta-steps to create a knowledge map:• Set of ontologies design (ON);• Knowledge elicitation for ontology population (E);• Visual knowledge mapping (VI);• Knowledge map justification and dissemination (D).The proposed ONE-VID approach was implemented at Graduate School ofManagement in Saint-Petersburg State University for the sample of 63 facultymembers. Several types of K-maps were designed and developed – treemaps,radars, knowledge profiles, etc.The paper describes the new methodology and illustrates the first results. Thesubsequent longitude study plan is considered that will give the possibility tocompare the specific knowledge profiles and gaps as time passes.
U2 - 10.1007/978-3-031-43789-2_23
DO - 10.1007/978-3-031-43789-2_23
M3 - Article in an anthology
SN - 978-3-031-43788-5
T3 - Lecture Notes in Networks and Systems
SP - 250
EP - 259
BT - Proceedings of the Seventh International Scientific Conference “Intelligent Information Technologies for Industry” (IITI’23). IITI 2023
A2 - Kovalev, Sergey
A2 - Sukhanov, Andrey
A2 - Kotenko, Igor
PB - Springer Nature
T2 - Seventh International Scientific Conference “Intelligent Information Technologies for Industry”
Y2 - 25 September 2023 through 30 September 2023
ER -
ID: 118316477