research-article

Explainable cyber-physical energy systems based on knowledge graph

Authors:

Peb Ruswono Aryan,

Fajar Juang Ekaputra,

Andreas RauberAuthors Info & Claims

MSCPES '21: Proceedings of the 9th Workshop on Modeling and Simulation of Cyber-Physical Energy Systems

Article No.: 4, Pages 1 - 6

https://doi.org/10.1145/3470481.3472704

Published: 06 October 2021 Publication History

Get Access

Abstract

Explainability can help cyber-physical systems alleviating risk in automating decisions that are affecting our life. Building an explainable cyber-physical system requires deriving explanations from system events and causality between the system elements. Cyber-physical energy systems such as smart grids involve cyber and physical aspects of energy systems and other elements, namely social and economic. Moreover, a smart-grid scale can range from a small village to a large region across countries. Therefore, integrating these varieties of data and knowledge is a fundamental challenge to build an explainable cyber-physical energy system. This paper aims to use knowledge graph based framework to solve this challenge. The framework consists of an ontology to model and link data from various sources and graph-based algorithm to derive explanations from the events. A simulated demand response scenario covering the above aspects further demonstrates the applicability of this framework.

References

[1]

Peb R Aryan, Fajar J Ekaputra, Marta Sabou, Daniel Hauer, Ralf Mosshammer, Alfred Einfalt, Tomasz Miksa, and Andreas Rauber. 2020. Simulation Support for Explainable Cyber-Physical Energy Systems. In 2020 8th Workshop on Modeling and Simulation of Cyber-Physical Energy Systems. IEEE, IEEE, 1--6.

Google Scholar

[2]

Ralf Mosshammer, Konrad Diwold, Alfred Einfalt, Julian Schwarz, and Benjamin Zehrfeldt. 2019. BIFROST: A Smart City Planning and Simulation Tool. In Intelligent Human Systems Integration, Waldemar Karwowski and Tareq Ahram (Eds.). Springer, 217--222.

Google Scholar

[3]

Nasrin Mostafazadeh, Alyson Grealish, Nathanael Chambers, James Allen, and Lucy Vanderwende. 2016. CaTeRS: Causal and temporal relation scheme for semantic annotation of event structures. In Proceedings of the Fourth Workshop on Events. 51--61.

Crossref

Google Scholar

[4]

Emil Krabbe Nielsen, Stefan Jespersen, Xinxin Zhang, Ole Ravn, and Morten Lind. 2018. On-line fault diagnosis of produced water treatment with multilevel flow modeling. Ifac-papersonline 51, 8 (2018), 225--232.

Crossref

Google Scholar

[5]

Tim O'Gorman, Kristin Wright-Bettner, and Martha Palmer. 2016. Richer Event Description: Integrating event coreference with temporal, causal and bridging annotation. In Proceedings of the 2nd Workshop on Computing News Storylines (CNS 2016). 47--56.

Crossref

Google Scholar

[6]

Joern Ploennigs, Anika Schumann, and Freddy Lécué. 2014. Adapting Semantic Sensor Networks for Smart Building Diagnosis. In 13th International Semantic Web Conference (ISWC). Springer, 308--323.

Digital Library

Google Scholar

[7]

Juan Qiu, Qingfeng Du, Kanglin Yin, Shuang-Li Zhang, and Chongshu Qian. 2020. A causality mining and knowledge graph based method of root cause diagnosis for performance anomaly in cloud applications. Applied Sciences 10, 6 (2020), 2166.

Crossref

Google Scholar

[8]

Ansgar Scherp, Thomas Franz, Carsten Saathoff, and Steffen Staab. 2009. F-a model of events based on the foundational ontology dolce+ DnS ultralight. In Proceedings of the fifth international conference on Knowledge capture. 137--144.

Digital Library

Google Scholar

[9]

Fan Yang, Ping Duan, Sirish L Shah, and Tongwen Chen. 2014. Capturing connectivity and causality in complex industrial processes. Springer Science & Business Media.

Google Scholar

[10]

Qin Zhang. 2012. Dynamic uncertain causality graph for knowledge representation and reasoning: Discrete DAG cases. Journal of Computer Science and Technology 27, 1 (2012), 1--23.

Crossref

Google Scholar

Cited By

View all

Schreiberhuber KEkaputra FSabou MHauer DDiwold KFrühwirth TSteindl GSchwarzinger T(2024)Towards a State Explanation Framework in Cyber-Physical SystemsACM SIGEnergy Energy Informatics Review10.1145/3717413.37174264:4(142-154)Online publication date: 1-Oct-2024
https://dl.acm.org/doi/10.1145/3717413.3717426
Steindl GSchwarzinger TSchreiberhuber KEkaputra F(2024)Toward Semantic Event-Handling for Building Explainable Cyber-Physical SystemsIEEE Open Journal of the Industrial Electronics Society10.1109/OJIES.2024.34470015(928-945)Online publication date: 2024
https://doi.org/10.1109/OJIES.2024.3447001
Jha SMayer SGarcia K(2023)Actionable Contextual Explanations for Cyber-Physical Systems2023 IEEE 22nd International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)10.1109/TrustCom60117.2023.00255(1879-1886)Online publication date: 1-Nov-2023
https://doi.org/10.1109/TrustCom60117.2023.00255
Show More Cited By

Index Terms

Explainable cyber-physical energy systems based on knowledge graph

Recommendations

Poster: Towards Explaining the Effects of Contextual Influences on Cyber-Physical Systems
IoT '21: Proceedings of the 11th International Conference on the Internet of Things

The increasing complexity of Cyber-Physical Systems (CPS) increases the difficulty for users to understand their behavior. Using existing Explainable Artificial Intelligence (XAI) methods, CPS can explain their behavior to the users. However, the input-...
Cyber-Physical Systems: A Computational Perspective
An ontological framework for knowledge modeling and decision support in cyber-physical systems

Our work is concerned with the development of knowledge structures to support correct-by-design cyber-physical systems (CPS). This class of systems is defined by a tight integration of software and physical processes, the need to satisfy stringent ...

Comments

Information & Contributors

Information

Published In

MSCPES '21: Proceedings of the 9th Workshop on Modeling and Simulation of Cyber-Physical Energy Systems

May 2021

83 pages

ISBN:9781450386081

DOI:10.1145/3470481

General Chairs:
Peter Palensky
TU Delft
,
Anurag Srivastava
Washington State University
,
Program Chair:
Edmund Widl
AIT Austrian Institute of Technology

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

In-Cooperation

IEEE Signal Processing Society
IEEE CS

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 06 October 2021

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Funding Sources

Austrian Research Promotion Agency

Conference

CPS-IoT Week '21

Sponsor:

SIGBED

CPS-IoT Week '21: Cyber-Physical Systems and Internet of Things Week 2021

May 19 - 21, 2021

Virtual Event

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

6
Total Citations
View Citations
254
Total Downloads

Downloads (Last 12 months)57
Downloads (Last 6 weeks)10

Reflects downloads up to 28 Feb 2025

Other Metrics

View Author Metrics

Citations

Cited By

View all

Schreiberhuber KEkaputra FSabou MHauer DDiwold KFrühwirth TSteindl GSchwarzinger T(2024)Towards a State Explanation Framework in Cyber-Physical SystemsACM SIGEnergy Energy Informatics Review10.1145/3717413.37174264:4(142-154)Online publication date: 1-Oct-2024
https://dl.acm.org/doi/10.1145/3717413.3717426
Steindl GSchwarzinger TSchreiberhuber KEkaputra F(2024)Toward Semantic Event-Handling for Building Explainable Cyber-Physical SystemsIEEE Open Journal of the Industrial Electronics Society10.1109/OJIES.2024.34470015(928-945)Online publication date: 2024
https://doi.org/10.1109/OJIES.2024.3447001
Jha SMayer SGarcia K(2023)Actionable Contextual Explanations for Cyber-Physical Systems2023 IEEE 22nd International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)10.1109/TrustCom60117.2023.00255(1879-1886)Online publication date: 1-Nov-2023
https://doi.org/10.1109/TrustCom60117.2023.00255
Xu CLiao ZLi CZhou XXie R(2022)Review on Interpretable Machine Learning in Smart GridEnergies10.3390/en1512442715:12(4427)Online publication date: 17-Jun-2022
https://doi.org/10.3390/en15124427
Capuano NFenza GLoia VStanzione C(2022)Explainable Artificial Intelligence in CyberSecurity: A SurveyIEEE Access10.1109/ACCESS.2022.320417110(93575-93600)Online publication date: 2022
https://doi.org/10.1109/ACCESS.2022.3204171
Aryan PDeimel MEkaputra FSabou M(2021)Using SPARQL to express Causality in Explainable Cyber-Physical Systems2021 8th International Conference on Advanced Informatics: Concepts, Theory and Applications (ICAICTA)10.1109/ICAICTA53211.2021.9640268(1-5)Online publication date: 29-Sep-2021
https://doi.org/10.1109/ICAICTA53211.2021.9640268

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Abstract

References

Cited By

Index Terms

Recommendations

Poster: Towards Explaining the Effects of Contextual Influences on Cyber-Physical Systems

Cyber-Physical Systems: A Computational Perspective

An ontological framework for knowledge modeling and decision support in cyber-physical systems

Comments

Information

Published In

Sponsors

In-Cooperation

Publisher

Publication History

Permissions

Check for updates

Author Tags

Qualifiers

Funding Sources

Conference

Contributors

Other Metrics

Bibliometrics

Article Metrics

Other Metrics

Citations

Cited By

Login options

Full Access

View options

PDF

eReader

Share

Share this Publication link

Share on social media

Affiliations