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Christopher Wingard OOI Endurance Array Data Access and Processing

Created by Christopher Wingard last modified

OOI Endurance Array Data Access and Processing

OOI Data for the Endurance Array is available from one of two sources: Raw Data Server or the Data Portal. In either case, just having access to the data is really of limited use. Ultimately, the data user needs to be able to understand and control the process of data downloads, processing and organization in order to start the process of converting the data to information, knowledge and wisdom.

The following examples are intended to help the user begin this process. The examples linked to below represent an attempt by staff operating the OOI Endurance Array to share with the user community the tools and processes we've developed as we've begun working with the data from the OOI Endurance Array. This list will continue to grow (at user request and as we continue to refine our processes and understanding of the data), so please check back early and often. Please do not hesitate to contact us directly if you have any questions. Note, you can add comments below or use the email link above.

Accessing and Parsing Files from the Raw Data Server

The following jupyter notebooks outline the initial steps needed to download and parse (convert the data from the different formats recorded by the mooring data logger system) the raw data files into a common format for further processing and analysis.

  • WET Labs, Inc. ECO Triplet FLORT data files.
  • WET Labs, Inc. AC-S OPTAA data files.
  • Satlantic, OCR-570 SPKIR data files.

Accessing NetCDF Data Files from the Data Portal

  • WET Labs, Inc. ECO Triplet FLORT data files.
  • WET Labs, Inc. AC-S OPTAA data files.
  • Satlantic, OCR-570 SPKIR data files.

Processing Raw Data

The next steps after obtaining the raw data files and parsing them into a common format, is processing of the data. Processing may include:

  • Applying factory calibration coefficients to convert raw units (e.g. counts) to engineering/scientific units (e.g. mg/L).
  • Unit conversions: convert between engineering/scientific units to more applicable units (e.g. psi to db).
  • Removal of parameters of limited interest to the processing at hand (that's on the user, the parameters are always available in the raw data).
  • Application of initial QA/QC tests (e.g. range tests to see if values are within a reasonable range).
  • Derivation of new parameters.

Examples coming soon

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