Linked data to streaming data sensors sources for direct access

Detalhes bibliográficos
Autor(a) principal: Calvetti, Diego
Data de Publicação: 2024
Outros Autores: Nascimento, Daniel Luiz de Mattos, Araújo Filho, Flávio Ney Magno de, Abreu, Rafael Henrique Viana, Papadopoulos , Nicolas Alexandros
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Brazilian Journal of Operations & Production Management (Online)
Texto Completo: https://bjopm.org.br/bjopm/article/view/1993
Resumo: Goal: Industrial operations are complex, and data sensors assure safety and reliable information for production improvements. Multiple stakeholders can take advantage of data acquisition for post-analysis and process control. Providing users and systems with friendly access to operating data is fundamental to the digital transition in the industry 4.0 scenario. Linking data and systems over ontologies and Industry Foundation Classes will boost supply chain performance in many layers. This paper presents the concept of valid data points over Uniform Resource Identifiers for sensor time-series into triples stores via Application Programming Interfaces. Design/Methodology/Approach: A streaming data source approach to integrating industrial sensor data and sharing it via Uniform Resource Identifiers is developed and tested using Node-Red with multiple data connection types, such as the Industry Foundation Classes and open-source time series databases. Results: The detailed proof of concept presented valid the feasibility of sharing sensor data via Uniform Resource Identifiers. The findings provide a backbone of a system able to interop Message Queuing Telemetry Transport data, Resource Description Framework datasets and Industry Foundation Classes schema. Limitations of the investigation: The system envisaged was tested using simulated data. However, it is expected to have similar results from real data use. Nevertheless, more research will be needed to implement more features, such as three-dimensional object integration. Practical implications: The solution designed and tested presented can be used in practice for companies that desire to expand via linked data shareability and interoperability. Also, researchers can advance the solution for specific features, such as creating an open-source data query and manipulation language. Originality/Value: This paper examines future deployments of systems-to-systems interoperability targeting user-friendly data shareability. It is meant to be useful for industrial and academic developments.
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spelling Linked data to streaming data sensors sources for direct accessIndustry 4.0Linked systemsServer-Sent EventsTime-seriesMQTTGoal: Industrial operations are complex, and data sensors assure safety and reliable information for production improvements. Multiple stakeholders can take advantage of data acquisition for post-analysis and process control. Providing users and systems with friendly access to operating data is fundamental to the digital transition in the industry 4.0 scenario. Linking data and systems over ontologies and Industry Foundation Classes will boost supply chain performance in many layers. This paper presents the concept of valid data points over Uniform Resource Identifiers for sensor time-series into triples stores via Application Programming Interfaces. Design/Methodology/Approach: A streaming data source approach to integrating industrial sensor data and sharing it via Uniform Resource Identifiers is developed and tested using Node-Red with multiple data connection types, such as the Industry Foundation Classes and open-source time series databases. Results: The detailed proof of concept presented valid the feasibility of sharing sensor data via Uniform Resource Identifiers. The findings provide a backbone of a system able to interop Message Queuing Telemetry Transport data, Resource Description Framework datasets and Industry Foundation Classes schema. Limitations of the investigation: The system envisaged was tested using simulated data. However, it is expected to have similar results from real data use. Nevertheless, more research will be needed to implement more features, such as three-dimensional object integration. Practical implications: The solution designed and tested presented can be used in practice for companies that desire to expand via linked data shareability and interoperability. Also, researchers can advance the solution for specific features, such as creating an open-source data query and manipulation language. Originality/Value: This paper examines future deployments of systems-to-systems interoperability targeting user-friendly data shareability. It is meant to be useful for industrial and academic developments.Brazilian Association for Industrial Engineering and Operations Management (ABEPRO)2024-01-24info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionResearch paperapplication/pdfhttps://bjopm.org.br/bjopm/article/view/199310.14488/BJOPM.1993.2024Brazilian Journal of Operations & Production Management; Vol. 21 No. 1 (2024)2237-8960reponame:Brazilian Journal of Operations & Production Management (Online)instname:Associação Brasileira de Engenharia de Produção (ABEPRO)instacron:ABEPROenghttps://bjopm.org.br/bjopm/article/view/1993/1065Copyright (c) 2024 Diego Calvetti, Daniel Luiz de Mattos Nascimento, Flávio Ney Magno de Araújo Filho, Rafael Henrique Viana Abreu, Nicolas Alexandros Papadopoulos http://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessCalvetti, DiegoNascimento, Daniel Luiz de MattosAraújo Filho, Flávio Ney Magno deAbreu, Rafael Henrique VianaPapadopoulos , Nicolas Alexandros2024-01-24T12:11:17Zoai:ojs.bjopm.org.br:article/1993Revistahttps://bjopm.org.br/bjopmONGhttps://bjopm.org.br/bjopm/oaibjopm.journal@gmail.com2237-89601679-8171opendoar:2024-01-24T12:11:17Brazilian Journal of Operations & Production Management (Online) - Associação Brasileira de Engenharia de Produção (ABEPRO)false
dc.title.none.fl_str_mv Linked data to streaming data sensors sources for direct access
title Linked data to streaming data sensors sources for direct access
spellingShingle Linked data to streaming data sensors sources for direct access
Calvetti, Diego
Industry 4.0
Linked systems
Server-Sent Events
Time-series
MQTT
title_short Linked data to streaming data sensors sources for direct access
title_full Linked data to streaming data sensors sources for direct access
title_fullStr Linked data to streaming data sensors sources for direct access
title_full_unstemmed Linked data to streaming data sensors sources for direct access
title_sort Linked data to streaming data sensors sources for direct access
author Calvetti, Diego
author_facet Calvetti, Diego
Nascimento, Daniel Luiz de Mattos
Araújo Filho, Flávio Ney Magno de
Abreu, Rafael Henrique Viana
Papadopoulos , Nicolas Alexandros
author_role author
author2 Nascimento, Daniel Luiz de Mattos
Araújo Filho, Flávio Ney Magno de
Abreu, Rafael Henrique Viana
Papadopoulos , Nicolas Alexandros
author2_role author
author
author
author
dc.contributor.author.fl_str_mv Calvetti, Diego
Nascimento, Daniel Luiz de Mattos
Araújo Filho, Flávio Ney Magno de
Abreu, Rafael Henrique Viana
Papadopoulos , Nicolas Alexandros
dc.subject.por.fl_str_mv Industry 4.0
Linked systems
Server-Sent Events
Time-series
MQTT
topic Industry 4.0
Linked systems
Server-Sent Events
Time-series
MQTT
description Goal: Industrial operations are complex, and data sensors assure safety and reliable information for production improvements. Multiple stakeholders can take advantage of data acquisition for post-analysis and process control. Providing users and systems with friendly access to operating data is fundamental to the digital transition in the industry 4.0 scenario. Linking data and systems over ontologies and Industry Foundation Classes will boost supply chain performance in many layers. This paper presents the concept of valid data points over Uniform Resource Identifiers for sensor time-series into triples stores via Application Programming Interfaces. Design/Methodology/Approach: A streaming data source approach to integrating industrial sensor data and sharing it via Uniform Resource Identifiers is developed and tested using Node-Red with multiple data connection types, such as the Industry Foundation Classes and open-source time series databases. Results: The detailed proof of concept presented valid the feasibility of sharing sensor data via Uniform Resource Identifiers. The findings provide a backbone of a system able to interop Message Queuing Telemetry Transport data, Resource Description Framework datasets and Industry Foundation Classes schema. Limitations of the investigation: The system envisaged was tested using simulated data. However, it is expected to have similar results from real data use. Nevertheless, more research will be needed to implement more features, such as three-dimensional object integration. Practical implications: The solution designed and tested presented can be used in practice for companies that desire to expand via linked data shareability and interoperability. Also, researchers can advance the solution for specific features, such as creating an open-source data query and manipulation language. Originality/Value: This paper examines future deployments of systems-to-systems interoperability targeting user-friendly data shareability. It is meant to be useful for industrial and academic developments.
publishDate 2024
dc.date.none.fl_str_mv 2024-01-24
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Research paper
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://bjopm.org.br/bjopm/article/view/1993
10.14488/BJOPM.1993.2024
url https://bjopm.org.br/bjopm/article/view/1993
identifier_str_mv 10.14488/BJOPM.1993.2024
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://bjopm.org.br/bjopm/article/view/1993/1065
dc.rights.driver.fl_str_mv http://creativecommons.org/licenses/by/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by/4.0
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Brazilian Association for Industrial Engineering and Operations Management (ABEPRO)
publisher.none.fl_str_mv Brazilian Association for Industrial Engineering and Operations Management (ABEPRO)
dc.source.none.fl_str_mv Brazilian Journal of Operations & Production Management; Vol. 21 No. 1 (2024)
2237-8960
reponame:Brazilian Journal of Operations & Production Management (Online)
instname:Associação Brasileira de Engenharia de Produção (ABEPRO)
instacron:ABEPRO
instname_str Associação Brasileira de Engenharia de Produção (ABEPRO)
instacron_str ABEPRO
institution ABEPRO
reponame_str Brazilian Journal of Operations & Production Management (Online)
collection Brazilian Journal of Operations & Production Management (Online)
repository.name.fl_str_mv Brazilian Journal of Operations & Production Management (Online) - Associação Brasileira de Engenharia de Produção (ABEPRO)
repository.mail.fl_str_mv bjopm.journal@gmail.com
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