MOODA: the module for ocean observatory data analysis and harmonization
The development of straightforward tools in data analysis plays a signifcant role in the available accumulative data from marine observatories. A large number of diferent variables recorded with diferent formats in marine observatories require methodologies that allow analysis and integration of the...
| Autores: | , , , , |
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| Formato: | artículo |
| Fecha de publicación: | 2021 |
| País: | España |
| Recursos: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/356420 |
| Acesso em linha: | https://hdl.handle.net/2117/356420 |
| Access Level: | acceso abierto |
| Palavra-chave: | Oceanography Data management Python Data science Data harmonization EMSO ERIC Oceanografia Gestió de dades Anàlisi de dades Àrees temàtiques de la UPC::Informàtica::Sistemes d'informació |
| Resumo: | The development of straightforward tools in data analysis plays a signifcant role in the available accumulative data from marine observatories. A large number of diferent variables recorded with diferent formats in marine observatories require methodologies that allow analysis and integration of these data automatically. In this paper, we present the MOODA open-source Python package, which provides an extensive range of procedures for harmonization and analysis of data from marine observatories, including feature extraction, quality control, fltering features, and visualization tools. We present the key aspects of the design and implementation of the package (mooda v1.x). MOODA is an integral component of the European Multidisciplinary Seafoor and water-column Observatory (EMSO) data management platform to harmonize and manage data from the diferent marine observatories. MOODA’s dynamic development model based on user feedback achieves a continuous enhancement and integration of the library. |
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