2018 Ocean Sciences Meeting

February 11-16

When operational oceanographic data are provided to users in real time, it is imperative that automated quality control is performed on those observations. By reducing the dissemination of flawed values and highlighting questionable ones, users gain confidence in the data stream. Further, the operator benefits from early detection and subsequent repair of sensor/system failures, improving data return rates. Researchers and the operational community are engaged in developing, consolidating, and documenting procedures and sharing implementation experiences. We solicit abstracts relating to QC plans, expectations, and best practices, in regional and global contexts, for emerging technologies striving to achieve an interoperable capability and an operational status. The described QC techniques should be specific to the emerging technology, adhering to existing standards or introducing new standards if necessary. Potential topics include: supporting real-world solutions through the implementation of QARTOD tests or other QC information within observing system networks (ex. OOI, IOOS, Cabled Observatories, NERRS CDMO, etc.); Regional QA/QC standards development by operators and/or vendors; and data management of QC information. Case studies and lessons learned that describe any aspects of quality control are also encouraged.