Cargando…

Knowledge Graph Approach to Combustion Chemistry and Interoperability

[Image: see text] In this paper, we demonstrate through examples how the concept of a Semantic Web based knowledge graph can be used to integrate combustion modeling into cross-disciplinary applications and in particular how inconsistency issues in chemical mechanisms can be addressed. We discuss th...

Descripción completa

Detalles Bibliográficos
Autores principales: Farazi, Feroz, Salamanca, Maurin, Mosbach, Sebastian, Akroyd, Jethro, Eibeck, Andreas, Aditya, Leonardus Kevin, Chadzynski, Arkadiusz, Pan, Kang, Zhou, Xiaochi, Zhang, Shaocong, Lim, Mei Qi, Kraft, Markus
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2020
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7391961/
https://www.ncbi.nlm.nih.gov/pubmed/32743209
http://dx.doi.org/10.1021/acsomega.0c02055
_version_ 1783564755419529216
author Farazi, Feroz
Salamanca, Maurin
Mosbach, Sebastian
Akroyd, Jethro
Eibeck, Andreas
Aditya, Leonardus Kevin
Chadzynski, Arkadiusz
Pan, Kang
Zhou, Xiaochi
Zhang, Shaocong
Lim, Mei Qi
Kraft, Markus
author_facet Farazi, Feroz
Salamanca, Maurin
Mosbach, Sebastian
Akroyd, Jethro
Eibeck, Andreas
Aditya, Leonardus Kevin
Chadzynski, Arkadiusz
Pan, Kang
Zhou, Xiaochi
Zhang, Shaocong
Lim, Mei Qi
Kraft, Markus
author_sort Farazi, Feroz
collection PubMed
description [Image: see text] In this paper, we demonstrate through examples how the concept of a Semantic Web based knowledge graph can be used to integrate combustion modeling into cross-disciplinary applications and in particular how inconsistency issues in chemical mechanisms can be addressed. We discuss the advantages of linked data that form the essence of a knowledge graph and how we implement this in a number of interconnected ontologies, specifically in the context of combustion chemistry. Central to this is OntoKin, an ontology we have developed for capturing both the content and the semantics of chemical kinetic reaction mechanisms. OntoKin is used to represent the example mechanisms from the literature in a knowledge graph, which itself is part of the existing, more general knowledge graph and ecosystem of autonomous software agents that are acting on it. We describe a web interface, which allows users to interact with the system, upload and compare the existing mechanisms, and query species and reactions across the knowledge graph. The utility of the knowledge-graph approach is demonstrated for two use-cases: querying across multiple mechanisms from the literature and modeling the atmospheric dispersion of pollutants emitted by ships. As part of the query use-case, our ontological tools are applied to identify variations in the rate of a hydrogen abstraction reaction from methane as represented by 10 different mechanisms.
format Online
Article
Text
id pubmed-7391961
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher American Chemical Society
record_format MEDLINE/PubMed
spelling pubmed-73919612020-07-31 Knowledge Graph Approach to Combustion Chemistry and Interoperability Farazi, Feroz Salamanca, Maurin Mosbach, Sebastian Akroyd, Jethro Eibeck, Andreas Aditya, Leonardus Kevin Chadzynski, Arkadiusz Pan, Kang Zhou, Xiaochi Zhang, Shaocong Lim, Mei Qi Kraft, Markus ACS Omega [Image: see text] In this paper, we demonstrate through examples how the concept of a Semantic Web based knowledge graph can be used to integrate combustion modeling into cross-disciplinary applications and in particular how inconsistency issues in chemical mechanisms can be addressed. We discuss the advantages of linked data that form the essence of a knowledge graph and how we implement this in a number of interconnected ontologies, specifically in the context of combustion chemistry. Central to this is OntoKin, an ontology we have developed for capturing both the content and the semantics of chemical kinetic reaction mechanisms. OntoKin is used to represent the example mechanisms from the literature in a knowledge graph, which itself is part of the existing, more general knowledge graph and ecosystem of autonomous software agents that are acting on it. We describe a web interface, which allows users to interact with the system, upload and compare the existing mechanisms, and query species and reactions across the knowledge graph. The utility of the knowledge-graph approach is demonstrated for two use-cases: querying across multiple mechanisms from the literature and modeling the atmospheric dispersion of pollutants emitted by ships. As part of the query use-case, our ontological tools are applied to identify variations in the rate of a hydrogen abstraction reaction from methane as represented by 10 different mechanisms. American Chemical Society 2020-07-16 /pmc/articles/PMC7391961/ /pubmed/32743209 http://dx.doi.org/10.1021/acsomega.0c02055 Text en Copyright © 2020 American Chemical Society This is an open access article published under a Creative Commons Attribution (CC-BY) License (http://pubs.acs.org/page/policy/authorchoice_ccby_termsofuse.html) , which permits unrestricted use, distribution and reproduction in any medium, provided the author and source are cited.
spellingShingle Farazi, Feroz
Salamanca, Maurin
Mosbach, Sebastian
Akroyd, Jethro
Eibeck, Andreas
Aditya, Leonardus Kevin
Chadzynski, Arkadiusz
Pan, Kang
Zhou, Xiaochi
Zhang, Shaocong
Lim, Mei Qi
Kraft, Markus
Knowledge Graph Approach to Combustion Chemistry and Interoperability
title Knowledge Graph Approach to Combustion Chemistry and Interoperability
title_full Knowledge Graph Approach to Combustion Chemistry and Interoperability
title_fullStr Knowledge Graph Approach to Combustion Chemistry and Interoperability
title_full_unstemmed Knowledge Graph Approach to Combustion Chemistry and Interoperability
title_short Knowledge Graph Approach to Combustion Chemistry and Interoperability
title_sort knowledge graph approach to combustion chemistry and interoperability
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7391961/
https://www.ncbi.nlm.nih.gov/pubmed/32743209
http://dx.doi.org/10.1021/acsomega.0c02055
work_keys_str_mv AT faraziferoz knowledgegraphapproachtocombustionchemistryandinteroperability
AT salamancamaurin knowledgegraphapproachtocombustionchemistryandinteroperability
AT mosbachsebastian knowledgegraphapproachtocombustionchemistryandinteroperability
AT akroydjethro knowledgegraphapproachtocombustionchemistryandinteroperability
AT eibeckandreas knowledgegraphapproachtocombustionchemistryandinteroperability
AT adityaleonarduskevin knowledgegraphapproachtocombustionchemistryandinteroperability
AT chadzynskiarkadiusz knowledgegraphapproachtocombustionchemistryandinteroperability
AT pankang knowledgegraphapproachtocombustionchemistryandinteroperability
AT zhouxiaochi knowledgegraphapproachtocombustionchemistryandinteroperability
AT zhangshaocong knowledgegraphapproachtocombustionchemistryandinteroperability
AT limmeiqi knowledgegraphapproachtocombustionchemistryandinteroperability
AT kraftmarkus knowledgegraphapproachtocombustionchemistryandinteroperability