A Parallel World Framework for scenario analysis in knowledge graphs

This paper presents Parallel World Framework as a solution for simulations of complex systems within a time-varying knowledge graph and its application to the electric grid of Jurong Island in Singapore. The underlying modeling system is based on the Semantic Web Stack. Its linked data layer is desc...

詳細記述

書誌詳細

出版年:	Data-Centric Engineering
主要な著者:	Andreas Eibeck, Arkadiusz Chadzynski, Mei Qi Lim, Kevin Aditya, Laura Ong, Aravind Devanand, Gourab Karmakar, Sebastian Mosbach, Raymond Lau, Iftekhar A. Karimi, Eddy Y. S. Foo, Markus Kraft
フォーマット:	論文
言語:	英語
出版事項:	Cambridge University Press 2020-01-01
主題:	Interoperability knowledge graph parallel world scenario analysis superstructure versioning
オンライン･アクセス:	https://www.cambridge.org/core/product/identifier/S2632673620000064/type/journal_article