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A data model and file format to represent and store high frequency energy monitoring and disaggregation datasets
There is a generalized consensus in the Non-Intrusive Load Monitoring research community on the importance of public datasets for improving this research field. Still, despite the considerable efforts to release public data, what is currently available suffers from serious issues, among which is the...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9206669/ https://www.ncbi.nlm.nih.gov/pubmed/35717423 http://dx.doi.org/10.1038/s41598-022-14517-y |
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author | Pereira, Lucas Velosa, Nuno Pereira, Manuel |
author_facet | Pereira, Lucas Velosa, Nuno Pereira, Manuel |
author_sort | Pereira, Lucas |
collection | PubMed |
description | There is a generalized consensus in the Non-Intrusive Load Monitoring research community on the importance of public datasets for improving this research field. Still, despite the considerable efforts to release public data, what is currently available suffers from serious issues, among which is the lack of widely accepted data models and common interfaces to access the currently available and future datasets. This paper proposes the Energy Monitoring and Disaggregation Data Format (EMD-DF64). EMD-DF64 is a data model, file format, and application programming interface developed to provide a unique interface to create, manage, and access high-frequency (≥ 1 Hz) electric energy consumption datasets. More precisely, the present paper describes the data model and its respective implementation, which was done by leveraging the well-known Sony WAVE64 format that supports the storage of audio data and metadata annotations. |
format | Online Article Text |
id | pubmed-9206669 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-92066692022-06-20 A data model and file format to represent and store high frequency energy monitoring and disaggregation datasets Pereira, Lucas Velosa, Nuno Pereira, Manuel Sci Rep Article There is a generalized consensus in the Non-Intrusive Load Monitoring research community on the importance of public datasets for improving this research field. Still, despite the considerable efforts to release public data, what is currently available suffers from serious issues, among which is the lack of widely accepted data models and common interfaces to access the currently available and future datasets. This paper proposes the Energy Monitoring and Disaggregation Data Format (EMD-DF64). EMD-DF64 is a data model, file format, and application programming interface developed to provide a unique interface to create, manage, and access high-frequency (≥ 1 Hz) electric energy consumption datasets. More precisely, the present paper describes the data model and its respective implementation, which was done by leveraging the well-known Sony WAVE64 format that supports the storage of audio data and metadata annotations. Nature Publishing Group UK 2022-06-18 /pmc/articles/PMC9206669/ /pubmed/35717423 http://dx.doi.org/10.1038/s41598-022-14517-y Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Pereira, Lucas Velosa, Nuno Pereira, Manuel A data model and file format to represent and store high frequency energy monitoring and disaggregation datasets |
title | A data model and file format to represent and store high frequency energy monitoring and disaggregation datasets |
title_full | A data model and file format to represent and store high frequency energy monitoring and disaggregation datasets |
title_fullStr | A data model and file format to represent and store high frequency energy monitoring and disaggregation datasets |
title_full_unstemmed | A data model and file format to represent and store high frequency energy monitoring and disaggregation datasets |
title_short | A data model and file format to represent and store high frequency energy monitoring and disaggregation datasets |
title_sort | data model and file format to represent and store high frequency energy monitoring and disaggregation datasets |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9206669/ https://www.ncbi.nlm.nih.gov/pubmed/35717423 http://dx.doi.org/10.1038/s41598-022-14517-y |
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