Knowledge Graph Modeling for Semantic Integration of Energy Services

Sejin Chun; Xiongnan Jin; Seungmin Seo; Kyong Ho Lee; Youngmee Shin; Ilwoo Lee

doi:10.1109/BigComp.2018.00138

Knowledge Graph Modeling for Semantic Integration of Energy Services

Sejin Chun, Xiongnan Jin, Seungmin Seo, Kyong Ho Lee, Youngmee Shin, Ilwoo Lee

College of Computing

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

14 Citations (Scopus)

Abstract

The forthcoming smart-grid is expected to provide advanced energy services more efficiently and eco-friendly with an integrated network of various information such as a smart meter and social networks. As an information model of expressing such an integrated network, a knowledge graph (KG) represents a formal and common specification of concepts and relations in a specific domain. It is essential to leverage KGs for the interoperability, reusability, and scalability of smart-grid applications. However, existing KGs have limitations in accommodating detailed descriptions of energy services. In this paper, we propose an energy knowledge graph, which provides the semantic integration of various energy services. The proposed model also provides the detailed description of a micro-grid community. To verify the proposed model, we present and discuss its use-cases based on energy service scenarios.

Original language	English
Title of host publication	Proceedings - 2018 IEEE International Conference on Big Data and Smart Computing, BigComp 2018
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	732-735
Number of pages	4
ISBN (Electronic)	9781538636497
DOIs	https://doi.org/10.1109/BigComp.2018.00138
Publication status	Published - 2018 May 25
Event	2018 IEEE International Conference on Big Data and Smart Computing, BigComp 2018 - Shanghai, China Duration: 2018 Jan 15 → 2018 Jan 18

Publication series

Name	Proceedings - 2018 IEEE International Conference on Big Data and Smart Computing, BigComp 2018

Other

Other	2018 IEEE International Conference on Big Data and Smart Computing, BigComp 2018
Country/Territory	China
City	Shanghai
Period	18/1/15 → 18/1/18

Bibliographical note

Funding Information:
ACKNOWLEDGEMENT This work was supported by both Electronics and Telecommunications Research Institute (ETRI) and National Research Foundation of Korea (NRF) grant, which are funded by the Korean government. [Development of Energy Sharing Networking for Zero-Energy Community(15ZC1600) and MSIP(no. NRF-2016R1A2B4015873)].

Publisher Copyright:
© 2018 IEEE.

All Science Journal Classification (ASJC) codes

Artificial Intelligence
Computer Networks and Communications
Information Systems
Information Systems and Management

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/BigComp.2018.00138

Cite this

Chun, S., Jin, X., Seo, S., Lee, K. H., Shin, Y., & Lee, I. (2018). Knowledge Graph Modeling for Semantic Integration of Energy Services. In Proceedings - 2018 IEEE International Conference on Big Data and Smart Computing, BigComp 2018 (pp. 732-735). Article 8367218 (Proceedings - 2018 IEEE International Conference on Big Data and Smart Computing, BigComp 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BigComp.2018.00138

Chun, Sejin ; Jin, Xiongnan ; Seo, Seungmin et al. / Knowledge Graph Modeling for Semantic Integration of Energy Services. Proceedings - 2018 IEEE International Conference on Big Data and Smart Computing, BigComp 2018. Institute of Electrical and Electronics Engineers Inc., 2018. pp. 732-735 (Proceedings - 2018 IEEE International Conference on Big Data and Smart Computing, BigComp 2018).

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title = "Knowledge Graph Modeling for Semantic Integration of Energy Services",

abstract = "The forthcoming smart-grid is expected to provide advanced energy services more efficiently and eco-friendly with an integrated network of various information such as a smart meter and social networks. As an information model of expressing such an integrated network, a knowledge graph (KG) represents a formal and common specification of concepts and relations in a specific domain. It is essential to leverage KGs for the interoperability, reusability, and scalability of smart-grid applications. However, existing KGs have limitations in accommodating detailed descriptions of energy services. In this paper, we propose an energy knowledge graph, which provides the semantic integration of various energy services. The proposed model also provides the detailed description of a micro-grid community. To verify the proposed model, we present and discuss its use-cases based on energy service scenarios.",

author = "Sejin Chun and Xiongnan Jin and Seungmin Seo and Lee, {Kyong Ho} and Youngmee Shin and Ilwoo Lee",

note = "Funding Information: ACKNOWLEDGEMENT This work was supported by both Electronics and Telecommunications Research Institute (ETRI) and National Research Foundation of Korea (NRF) grant, which are funded by the Korean government. [Development of Energy Sharing Networking for Zero-Energy Community(15ZC1600) and MSIP(no. NRF-2016R1A2B4015873)]. Publisher Copyright: {\textcopyright} 2018 IEEE.; 2018 IEEE International Conference on Big Data and Smart Computing, BigComp 2018 ; Conference date: 15-01-2018 Through 18-01-2018",

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doi = "10.1109/BigComp.2018.00138",

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series = "Proceedings - 2018 IEEE International Conference on Big Data and Smart Computing, BigComp 2018",

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Chun, S, Jin, X, Seo, S, Lee, KH, Shin, Y & Lee, I 2018, Knowledge Graph Modeling for Semantic Integration of Energy Services. in Proceedings - 2018 IEEE International Conference on Big Data and Smart Computing, BigComp 2018., 8367218, Proceedings - 2018 IEEE International Conference on Big Data and Smart Computing, BigComp 2018, Institute of Electrical and Electronics Engineers Inc., pp. 732-735, 2018 IEEE International Conference on Big Data and Smart Computing, BigComp 2018, Shanghai, China, 18/1/15. https://doi.org/10.1109/BigComp.2018.00138

Knowledge Graph Modeling for Semantic Integration of Energy Services. / Chun, Sejin; Jin, Xiongnan; Seo, Seungmin et al.
Proceedings - 2018 IEEE International Conference on Big Data and Smart Computing, BigComp 2018. Institute of Electrical and Electronics Engineers Inc., 2018. p. 732-735 8367218 (Proceedings - 2018 IEEE International Conference on Big Data and Smart Computing, BigComp 2018).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AU - Lee, Kyong Ho

AU - Shin, Youngmee

AU - Lee, Ilwoo

N1 - Funding Information: ACKNOWLEDGEMENT This work was supported by both Electronics and Telecommunications Research Institute (ETRI) and National Research Foundation of Korea (NRF) grant, which are funded by the Korean government. [Development of Energy Sharing Networking for Zero-Energy Community(15ZC1600) and MSIP(no. NRF-2016R1A2B4015873)]. Publisher Copyright: © 2018 IEEE.

PY - 2018/5/25

Y1 - 2018/5/25

N2 - The forthcoming smart-grid is expected to provide advanced energy services more efficiently and eco-friendly with an integrated network of various information such as a smart meter and social networks. As an information model of expressing such an integrated network, a knowledge graph (KG) represents a formal and common specification of concepts and relations in a specific domain. It is essential to leverage KGs for the interoperability, reusability, and scalability of smart-grid applications. However, existing KGs have limitations in accommodating detailed descriptions of energy services. In this paper, we propose an energy knowledge graph, which provides the semantic integration of various energy services. The proposed model also provides the detailed description of a micro-grid community. To verify the proposed model, we present and discuss its use-cases based on energy service scenarios.

AB - The forthcoming smart-grid is expected to provide advanced energy services more efficiently and eco-friendly with an integrated network of various information such as a smart meter and social networks. As an information model of expressing such an integrated network, a knowledge graph (KG) represents a formal and common specification of concepts and relations in a specific domain. It is essential to leverage KGs for the interoperability, reusability, and scalability of smart-grid applications. However, existing KGs have limitations in accommodating detailed descriptions of energy services. In this paper, we propose an energy knowledge graph, which provides the semantic integration of various energy services. The proposed model also provides the detailed description of a micro-grid community. To verify the proposed model, we present and discuss its use-cases based on energy service scenarios.

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M3 - Conference contribution

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BT - Proceedings - 2018 IEEE International Conference on Big Data and Smart Computing, BigComp 2018

PB - Institute of Electrical and Electronics Engineers Inc.

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Y2 - 15 January 2018 through 18 January 2018

ER -

Chun S, Jin X, Seo S, Lee KH, Shin Y, Lee I. Knowledge Graph Modeling for Semantic Integration of Energy Services. In Proceedings - 2018 IEEE International Conference on Big Data and Smart Computing, BigComp 2018. Institute of Electrical and Electronics Engineers Inc. 2018. p. 732-735. 8367218. (Proceedings - 2018 IEEE International Conference on Big Data and Smart Computing, BigComp 2018). doi: 10.1109/BigComp.2018.00138

Knowledge Graph Modeling for Semantic Integration of Energy Services

Abstract

Publication series

Other

Bibliographical note

All Science Journal Classification (ASJC) codes

UN SDGs

Access to Document

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Cite this