NOAACOTS Enterprise QAQC

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NOAA/COTS Enterprise QA/QC
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NOAA/COTS Enterprise QA/QC

• Documented process by which COTS real time data
  streams flow through NOAA QA/QC processes and are
  made available to various gateways

3
NOAA/COTS Enterprise QA/QC

• Goal NOAA CSC, NDBC and CO-OPS work with COTS
  partners to enhance the quality and availability
  of data
• COTS service fee from last year supporting this
  effort

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Benefits

• Improve quality and availability of data
• Increases cost-effectiveness of COTS projects
• Demonstrate partnerships and leadership in
  integrating federal and non-federal data streams
  in building IOOS (success story)
• Partners become a recognized part of IOOS
• Provides stamp of approval for data quality
• Opportunity to work towards standards for data
  quality, transport
• Data QA/QC and archived can save IT costs at
  institutions

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Collecting Common Variables
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Some of you are doing this!
CaroCOOPS
SCCOOS/CDIP
CO-OPS
GoMOOS
LISICOS

• COMPS

WaveCIS
NDBC
CORMP
NYHOPS
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• Processes and examples of working with
  external partners
• Steve Collins
• National Data Buoy Center (NDBC)
• Steve Gill
• Center for Operational Oceanographic Products
• and Services (CO-OPS)

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Process Framework

• Repeatable, uniform, well described process for
• Documentation (metadata)
• Data formats/standards
• Data access and transfer protocols
• QA/QC
• Data destination(s)
• Assigning levels of reliability and QA/QC
• Data access and archival

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Next Steps

• COTS partners share vision
• Complete hiring of technical liaisons at NDBC and
  CO-OPS
• Prepare data process documentation
• Conduct a more thorough inventory of COTS data
  collection, quality control, metadata, and IT
  infrastructure
• Identify needs and opportunities to enhance the
  quality control and availability of data

10
Next Steps

• Develop plan for addressing priority needs and
  opportunities define responsibilities
• Implement plan to increase data quality and
  availability
• Begin with accepted data transfer methods used by
  NDBC and CO-OPS continue to explore new
  standards and protocols as IOOS/DMAC evolves

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Challenges

• Identify appropriate data streams quality,
  reliability, sustained (operational v. research)
• Multiple NOAA entry points for data
• Resource limitations (recipients and NOAA)
• IOOS which standards?
• Need to develop QA/QC algorithms for certain data
  types