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- W4285254984 abstract "The scientific novelty of the article is to ground the digital transformation of railway universities through the development of an ontology-based service-oriented ecosystem. The analysis of scientific publications and results of technical and technological initiatives in the field of railway transport revealed that the industry business ecosystem based on ontologies would determine the nature of digital transformation in railway universities. This idea, however, has not yet been sufficiently developed in education studies. It is obvious that ontologisation will require new conceptual solutions and tools to be implemented. The authors propose a new didactic concept called knowledge factory. The implementation of this didactic concept requires the development of ontology-based didactic tools. In particular, standardisation of education content through the concepts and relations in ontologies makes it possible to develop a web-application such as an intelligent tutoring agent. The study involved two stages. The first stage - conceptual - grounded the new knowledge factory didactic concept and the ontological model of interaction between the railway industry and railway universities. For this purpose, the authors applied the methods of ecosystem and ontological-semantic approaches. At the second stage - practical - an attempt was made to develop a prototype of an intelligent tutoring agent. With this purpose a fragment of ontology for the education course Artificial Intelligence Systems in Transport: Agent-Based Approach was developed. The top-down method was applied to develop this ontology. What is also emphasized is that the findings are to a large extent transferable to many industries." @default.
- W4285254984 created "2022-07-14" @default.
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- W4285254984 date "2022-01-01" @default.
- W4285254984 modified "2023-10-01" @default.
- W4285254984 title "An impact of ontology-based service-oriented ecosystems on digital transformation of railway transport and engineering education" @default.
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- W4285254984 doi "https://doi.org/10.1016/j.trpro.2022.06.210" @default.
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