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Updated: May 2, 2026

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Unraveling the Unseen Players in the Ocean - A Field Guide to Water Chemistry and Marine Microbiology
Published on: November 5, 2014
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A biological ocean data reformatting effort
Kimberlee Baldry1, Robert Johnson2, Peter G Strutton3,4,5
1Institute for Marine and Antarctic Studies, University of Tasmania, Hobart, Australia. kimberlee.baldry@ga.gov.au.
Scientific Data
|February 16, 2024
Summary
A new BIOlogical ocean data reforMATting Effort (BIO-MATE) creates accessible subsurface bio-physical data aggregates. This open-source R software reformats oceanographic voyage data for improved long-term change documentation and model validation.
Area of Science:
- Oceanography
- Marine Biology
- Data Science
Background:
- Biological ocean data from ships are crucial for understanding long-term changes, validating satellite algorithms, and assessing models.
- Existing aggregated data products often lack subsurface data, physical parameters, or comprehensive biological information.
Purpose of the Study:
- To introduce the first version of the BIOlogical ocean data reforMATting Effort (BIO-MATE).
- To address the gap in accessible subsurface bio-physical data aggregates.
- To provide a reproducible method for data reformatting.
Main Methods:
- Utilized open-source R software for data reformatting.
- Processed openly sourced, published datasets from oceanographic voyages.
- Integrated biological and physical data from various sensors and analyses (underway, profiling, pigment, particulate organic carbon).
Main Results:
- Developed an interoperable BIO-MATE data product containing reformatted biological and physical data.
- Ensured easy access and usability of the aggregated data.
- Facilitated the application of QA/QC protocols for diverse applications.
Conclusions:
- BIO-MATE establishes a reproducible framework for creating subsurface bio-physical data aggregates.
- The BIO-MATE data product enhances the utility of historical oceanographic data.
- This effort supports a wider range of oceanographic research, from surface to subsurface studies.
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