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River Basin Cyberinfrastructure in the Big Data Era: An Integrated Observational Data Control System in the Heihe River Basin
River basin cyberinfrastructure with the Internet of Things (IoT) as the core has brought watershed data science into the big data era, greatly improving data acquisition and sharing efficiency. However, challenges in analyzing, processing, and applying very large quantities of observational data re...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8401438/ https://www.ncbi.nlm.nih.gov/pubmed/34450871 http://dx.doi.org/10.3390/s21165429 |
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author | Guo, Jianwen Zhang, Minghu Shang, Qingsheng Liu, Feng Wu, Adan Li, Xin |
author_facet | Guo, Jianwen Zhang, Minghu Shang, Qingsheng Liu, Feng Wu, Adan Li, Xin |
author_sort | Guo, Jianwen |
collection | PubMed |
description | River basin cyberinfrastructure with the Internet of Things (IoT) as the core has brought watershed data science into the big data era, greatly improving data acquisition and sharing efficiency. However, challenges in analyzing, processing, and applying very large quantities of observational data remain. Given the observational needs in watershed research, we studied the construction of river basin cyberinfrastructure and developed an integrated observational data control system (IODCS). The IODCS is an important platform for processing large quantities of observational data, including automated collection, storage, analysis, processing, and release. This paper presents various aspects of the IODCS in detail, including the system’s overall design, function realization, big data analysis methods, and integrated models. We took the middle reaches of the Heihe River Basin (HRB) as the application research area to show the performance of the developed system. Since the system began operation, it has automatically received, analyzed, and stored more than 1.4 billion observational data records, with an average of more than 14 million observational data records processed per month and up to 21,011 active users. The demonstrated results show that the IODCS can effectively leverage the processing capability of massive observational data and provide a new perspective for facilitating ecological and hydrological scientific research on the HRB. |
format | Online Article Text |
id | pubmed-8401438 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-84014382021-08-29 River Basin Cyberinfrastructure in the Big Data Era: An Integrated Observational Data Control System in the Heihe River Basin Guo, Jianwen Zhang, Minghu Shang, Qingsheng Liu, Feng Wu, Adan Li, Xin Sensors (Basel) Article River basin cyberinfrastructure with the Internet of Things (IoT) as the core has brought watershed data science into the big data era, greatly improving data acquisition and sharing efficiency. However, challenges in analyzing, processing, and applying very large quantities of observational data remain. Given the observational needs in watershed research, we studied the construction of river basin cyberinfrastructure and developed an integrated observational data control system (IODCS). The IODCS is an important platform for processing large quantities of observational data, including automated collection, storage, analysis, processing, and release. This paper presents various aspects of the IODCS in detail, including the system’s overall design, function realization, big data analysis methods, and integrated models. We took the middle reaches of the Heihe River Basin (HRB) as the application research area to show the performance of the developed system. Since the system began operation, it has automatically received, analyzed, and stored more than 1.4 billion observational data records, with an average of more than 14 million observational data records processed per month and up to 21,011 active users. The demonstrated results show that the IODCS can effectively leverage the processing capability of massive observational data and provide a new perspective for facilitating ecological and hydrological scientific research on the HRB. MDPI 2021-08-11 /pmc/articles/PMC8401438/ /pubmed/34450871 http://dx.doi.org/10.3390/s21165429 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Guo, Jianwen Zhang, Minghu Shang, Qingsheng Liu, Feng Wu, Adan Li, Xin River Basin Cyberinfrastructure in the Big Data Era: An Integrated Observational Data Control System in the Heihe River Basin |
title | River Basin Cyberinfrastructure in the Big Data Era: An Integrated Observational Data Control System in the Heihe River Basin |
title_full | River Basin Cyberinfrastructure in the Big Data Era: An Integrated Observational Data Control System in the Heihe River Basin |
title_fullStr | River Basin Cyberinfrastructure in the Big Data Era: An Integrated Observational Data Control System in the Heihe River Basin |
title_full_unstemmed | River Basin Cyberinfrastructure in the Big Data Era: An Integrated Observational Data Control System in the Heihe River Basin |
title_short | River Basin Cyberinfrastructure in the Big Data Era: An Integrated Observational Data Control System in the Heihe River Basin |
title_sort | river basin cyberinfrastructure in the big data era: an integrated observational data control system in the heihe river basin |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8401438/ https://www.ncbi.nlm.nih.gov/pubmed/34450871 http://dx.doi.org/10.3390/s21165429 |
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