Methods for Developing Digital Twins of Roles Based on Semantic Domain-Specific Languages Научная публикация
Сборник | 22nd IEEE International Conference of Young Professionals in Electron Devices and Materials, EDM 2021 Сборник, IEEE. 2021. 585 c. |
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Вых. Данные | Год: 2021, Том: 2021-June, Номер статьи : 9507716, Страниц : 5 DOI: 10.1109/EDM52169.2021.9507716 | ||||
Ключевые слова | business process modeling; digital twin; ontological model; ontology; semantic domain-specific language | ||||
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Реферат:
A digital twin is a virtual representation of a physical object or system throughout its entire lifecycle using real-time data. Digital twins of business processes are used to develop management and production methodologies. To create such digital twins, it is necessary to describe the knowledge about the subject domain, to model the regulations and roles involved in the processes. To solve this problem, we use semantic domain-specific languages (sDSL). They allow knowledge about the subject domain to be declaratively described and this knowledge into executable code to be implemented. The d0s1 language implements the ideas of sDSL in practice and allows domain-specific languages for modeling business processes to be created. The digital twin of role includes the knowledge and competencies of the original, is described in the d0s1 language and is able to perform the actions of its original as part of the implementation of business processes. © 2021 IEEE.
Библиографическая ссылка:
Palchunov D.
, Vaganova A.
Methods for Developing Digital Twins of Roles Based on Semantic Domain-Specific Languages
В сборнике 22nd IEEE International Conference of Young Professionals in Electron Devices and Materials, EDM 2021. – IEEE., 2021. – C.515-519. DOI: 10.1109/EDM52169.2021.9507716 Scopus OpenAlex
Methods for Developing Digital Twins of Roles Based on Semantic Domain-Specific Languages
В сборнике 22nd IEEE International Conference of Young Professionals in Electron Devices and Materials, EDM 2021. – IEEE., 2021. – C.515-519. DOI: 10.1109/EDM52169.2021.9507716 Scopus OpenAlex
Идентификаторы БД:
Scopus: | 2-s2.0-85113584091 |
OpenAlex: | W3193371585 |