UDASH-AI: Unified Database for Arctic and Subarctic Hydrography Optimized for Artificial Intelligence Applications ...
UDASH-AI represents an updated version of the UDASH dataset, that has been created to develop an artificial intelligence algorithm, that we name SalaciaML-Arctic to support the visual/human quality control of the data. UDASH-AI can be directly used with our algorithm, provided under the DOI: https:/...
| Main Authors: | , , , , |
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| Format: | Dataset |
| Language: | unknown |
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PANGAEA
2024
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| Subjects: | |
| Online Access: | https://dx.doi.org/10.1594/pangaea.973235 https://doi.pangaea.de/10.1594/PANGAEA.973235 |
| Summary: | UDASH-AI represents an updated version of the UDASH dataset, that has been created to develop an artificial intelligence algorithm, that we name SalaciaML-Arctic to support the visual/human quality control of the data. UDASH-AI can be directly used with our algorithm, provided under the DOI: https://doi.org/10.5281/zenodo.11535790 and the respective GitHub repository, to reproduce our results, extend the methods and more. Additionally, we have implemented SalaciaML-Arctic as an user-friendly app at https://mvre.autoqc.cloud.awi.de. Following steps have been applied on the original UDASH dataset to create UDASH-AI:• Concatenation of the single, annual txt files into one single csv file.• The original encoding of missing time and day information in the date/time string as 'T99:99' and '-00T' have been changed to ISO8601 conformity: 'T00:00' and '-01T'. To not loose this information we have added a quality flag ('QF_time') in the column next to the date/time with following encoding:◦ 0: No missing data (good ... |
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