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A Data Quality Control Method for Seafloor Observatories: The Application of Observed Time Series Data in the East China Sea
Zhou, Yusheng1,2; Qin, Rufu1; Xu, Huiping1,3; Sadiq, Shazia2; Yu, Yang1
2018-08-01
Source PublicationSENSORS
ISSN1424-8220
Volume18Issue:8Pages:1
Abstract

With the construction and deployment of seafloor observatories around the world, massive amounts of oceanographic measurement data were gathered and transmitted to data centers. The increase in the amount of observed data not only provides support for marine scientific research but also raises the requirements for data quality control, as scientists must ensure that their research outcomes come from high-quality data. In this paper, we first analyzed and defined data quality problems occurring in the East China Sea Seafloor Observatory System (ECSSOS). We then proposed a method to detect and repair the data quality problems of seafloor observatories. Incorporating data statistics and expert knowledge from domain specialists, the proposed method consists of three parts: a general pretest to preprocess data and provide a router for further processing, data outlier detection methods to label suspect data points, and a data interpolation method to fill up missing and suspect data. The autoregressive integrated moving average (ARIMA) model was improved and applied to seafloor observatory data quality control by using a sliding window and cleaning the input modeling data. Furthermore, a quality control flag system was also proposed and applied to describe data quality control results and processing procedure information. The real observed data in ECSSOS were used to implement and test the proposed method. The results demonstrated that the proposed method performed effectively at detecting and repairing data quality problems for seafloor observatory data.

SubtypeArticle
KeywordSeafloor Observatory Data Quality Control Arima Outlier Detection Data Interpolation
WOS HeadingsScience & Technology ; Physical Sciences ; Technology
DOI10.3390/s18082628
Indexed BySCI
Funding OrganizationScience and Technology Commission of Shanghai(15DZ1207104 ; Shanghai Oceanic Administration(Huhaike 2016-07) ; 15DZ1203100)
Language英语
WOS KeywordSensor Data ; Benefits ; Canada
WOS Research AreaChemistry ; Electrochemistry ; Instruments & Instrumentation
WOS SubjectChemistry, Analytical ; Electrochemistry ; Instruments & Instrumentation
WOS IDWOS:000445712400228
PublisherMDPI
Citation statistics
Document Type期刊论文
Version出版稿
Identifierhttp://ir.idsse.ac.cn/handle/183446/6313
Collection所领导
Corresponding AuthorQin, Rufu
Affiliation1.Tongji Univ, State Key Lab Marine Geol, Shanghai 200092, Peoples R China
2.Univ Queensland, Sch Informat Technol & Elect Engn, St Lucia, Qld 4072, Australia
3.Chinese Acad Sci, Inst Deep Sea Sci & Engn, Sanya 572000, Peoples R China
Recommended Citation
GB/T 7714
Zhou, Yusheng,Qin, Rufu,Xu, Huiping,et al. A Data Quality Control Method for Seafloor Observatories: The Application of Observed Time Series Data in the East China Sea[J]. SENSORS,2018,18(8):1.
APA Zhou, Yusheng,Qin, Rufu,Xu, Huiping,Sadiq, Shazia,&Yu, Yang.(2018).A Data Quality Control Method for Seafloor Observatories: The Application of Observed Time Series Data in the East China Sea.SENSORS,18(8),1.
MLA Zhou, Yusheng,et al."A Data Quality Control Method for Seafloor Observatories: The Application of Observed Time Series Data in the East China Sea".SENSORS 18.8(2018):1.
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