UDASH-SalaciaML-2-Arctic: Unified Database for Arctic and Subarctic Hydrography - Simplified and extended for quality control analyses
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| Format: | Dataset Open Access |
| Langue: | en |
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PANGAEA
2025
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| _version_ | 1867171052895862784 |
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| author | Kreps, Gastón Mieruch, Sebastian |
| author_facet | Kreps, Gastón Mieruch, Sebastian |
| collection | Datos científicos de ciencias marinas y ambientales |
| contents | UDASH-SalaciaML-2-Arctic represents an updated and simplified version of the UDASH dataset, that has been created to develop an artificial intelligence algorithm, that we name SalaciaML-2-Arctic to support the visual/human quality control (QC) of the data. UDASH-SalaciaML-2-Arctic can be directly used with our algorithms, provided under the GitHub repository (https://github.com/GastonKreps/SalaciaML-2-Arctic), to reproduce our results, extend the methods and more. Additionally, we have implemented SalaciaML-2-Arctic as an user-friendly app at https://mvre.autoqc.cloud.awi.de. The following steps have been applied to the original UDASH dataset to create UDASH-SalaciaML-2-Arctic: - Single, annual .txt files were concatenated into two single .csv files, one for temperature and one for salinity. - Parameters have been reduced to a minimal set, names and units have been adapted slightly. - Temperature and salinity gradients have been calculated and added. - Missing values are kept as -999. - Traditional QC flags, generated by the classical algorithms, have been added: 0=good, 2=suspect_gradient, 4=spike. |
| format | Dataset Open Access |
| id | pangaea_https___doi_org_10_1594_PANGAEA_983690 |
| institution | PANGAEA |
| language | en |
| publishDate | 2025 |
| publisher | PANGAEA |
| record_format | pangaea |
| spellingShingle | UDASH-SalaciaML-2-Arctic: Unified Database for Arctic and Subarctic Hydrography - Simplified and extended for quality control analyses Kreps, Gastón Mieruch, Sebastian Arctic; Binary Object; Binary Object (File Size); CTD; DataHub; DataHub Earth and Environment of the Helmholtz Association; deep learning; File content; hydrography; pan-Arctic; quality control; UDASH UDASH-SalaciaML-2-Arctic represents an updated and simplified version of the UDASH dataset, that has been created to develop an artificial intelligence algorithm, that we name SalaciaML-2-Arctic to support the visual/human quality control (QC) of the data. UDASH-SalaciaML-2-Arctic can be directly used with our algorithms, provided under the GitHub repository (https://github.com/GastonKreps/SalaciaML-2-Arctic), to reproduce our results, extend the methods and more. Additionally, we have implemented SalaciaML-2-Arctic as an user-friendly app at https://mvre.autoqc.cloud.awi.de. The following steps have been applied to the original UDASH dataset to create UDASH-SalaciaML-2-Arctic: - Single, annual .txt files were concatenated into two single .csv files, one for temperature and one for salinity. - Parameters have been reduced to a minimal set, names and units have been adapted slightly. - Temperature and salinity gradients have been calculated and added. - Missing values are kept as -999. - Traditional QC flags, generated by the classical algorithms, have been added: 0=good, 2=suspect_gradient, 4=spike. |
| title | UDASH-SalaciaML-2-Arctic: Unified Database for Arctic and Subarctic Hydrography - Simplified and extended for quality control analyses |
| topic | Arctic; Binary Object; Binary Object (File Size); CTD; DataHub; DataHub Earth and Environment of the Helmholtz Association; deep learning; File content; hydrography; pan-Arctic; quality control; UDASH |
| url | https://doi.org/10.1594/PANGAEA.983690 |