{
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{
"name": "Lester, Todd",
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"titles": [
{
"title": "Questions and responses to USGS-wide poll on quality assurance practices for timeseries data, 2021"
}
],
"publisher": "U.S. Geological Survey",
"container": {},
"publicationYear": 2023,
"subjects": [
{
"subject": "Aquatic Biology, Hydrology, Information Sciences, Water Quality, Water Resources"
}
],
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"dates": [
{
"date": "2023",
"dateType": "Issued"
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"description": "This data record contains questions and responses to a USGS-wide survey conducted to identify issues and needs associated with quality assurance and quality control (QA/QC) of USGS timeseries data streams. This research was funded by the USGS Community for Data Integration as part of a project titled ?From reactive- to condition-based maintenance: Artificial intelligence for anomaly predictions and operational decision-making?. The poll targeted monitoring network managers and technicians and asked questions about operational data streams and timeseries data collection in order to identity opportunities to streamline data access, expedite the response to data quality issues, improve QA/QC procedures, reduce operations costs, and uncover other maintenance needs. The poll was created using an online survey platform. It was sent to 2326 systematically selected USGS email addresses and received 175 responses in 11 days before it was closed to respondents. The poll contained 48 questions of various types including long answer, multiple choice, and ranking questions. The survey contained a mix of mandatory and optional questions. These distinctions as well as full descriptions of survey questions are noted on the metadata.",
"descriptionType": "Abstract"
}
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"created": "2023-01-23T21:32:48Z",
"registered": "2023-01-23T21:32:49Z",
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"updated": "2023-01-23T21:32:57Z"
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