MOODA, a comprehensive tool to analyze EMSO ERIC data

MOODA, a comprehensive tool to analyze EMSO ERIC data

European Geosciences Union (EGU) General Assembly, 7-12 April 2019, Vienna, Austria.-- 1 page

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Main Authors: Bardají, Raúl, Piera, Jaume, Huber, Robert, Rodero, Iván, Dañobeitia, Juan José, Favali, Paolo
Format: comunicación de congreso biblioteca
Language:English
Published: European Geosciences Union 2019-04
Online Access:http://hdl.handle.net/10261/241202
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spelling dig-icm-es-10261-2412022021-05-20T01:34:46Z MOODA, a comprehensive tool to analyze EMSO ERIC data Bardají, Raúl Piera, Jaume Huber, Robert Rodero, Iván Dañobeitia, Juan José Favali, Paolo European Geosciences Union (EGU) General Assembly, 7-12 April 2019, Vienna, Austria.-- 1 page The EMSO ERIC is a European environmental research infrastructure distributed throughout European seas,from the North Atlantic across the Mediterranean to the Black Sea, at 11 key environmental sites whose overallobjective is to record at Essential Ocean Variables (EOv′s) to respond to the societal challenges in global changeissues.This work presents MOODA (Module for Ocean Observatory Data Analysis), an open-source python pack-age that allows to create, open and analyse data files from different scientific instrumentation, platforms, andformats, to generate quality control of data and to create graphs. The package, developed in the framework of theH2020 project EMOSDEV, has been conceived mainly for oceanographers and marine science students.In MOODA, data is structured in WaterFrames. A WaterFrame, an extension of the DataFrame data struc-ture included in Pandas, the popular data analysis library for Python. The WaterFrame object contains a PandasDataFrame and two dictionaries, allowing to include relevant metadata of the acquired observations of the EMSOERIC nodes. The WaterFrame, allows using a DataFrame of Pandas without losing the metadata information,which is essential for different processes (mainly data quality control). MOODA has been designed to be scalable,being able not only to process data from EMSO ERIC but also other ocean data platforms such as EMODNET.MOODA is provided as a standalone framework, and it contains a Graphical User Interface (GUI) to be used fornon-Python users. However, MOODA can also be delivered as a service Peer reviewed 2021-05-19T11:29:05Z 2021-05-19T11:29:05Z 2019-04 comunicación de congreso http://purl.org/coar/resource_type/c_5794 Geophysical Research Abstracts 21: EGU2019-13508 (2019) 1607-7962 http://hdl.handle.net/10261/241202 en Publisher's version https://meetingorganizer.copernicus.org/EGU2019/EGU2019-13508.pdf Sí open European Geosciences Union
institution ICM ES
collection DSpace
country España
countrycode ES
component Bibliográfico
access En linea
databasecode dig-icm-es
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region Europa del Sur
libraryname Biblioteca del ICM España
language English
description European Geosciences Union (EGU) General Assembly, 7-12 April 2019, Vienna, Austria.-- 1 page
format comunicación de congreso
author Bardají, Raúl
Piera, Jaume
Huber, Robert
Rodero, Iván
Dañobeitia, Juan José
Favali, Paolo
spellingShingle Bardají, Raúl
Piera, Jaume
Huber, Robert
Rodero, Iván
Dañobeitia, Juan José
Favali, Paolo
MOODA, a comprehensive tool to analyze EMSO ERIC data
author_facet Bardají, Raúl
Piera, Jaume
Huber, Robert
Rodero, Iván
Dañobeitia, Juan José
Favali, Paolo
author_sort Bardají, Raúl
title MOODA, a comprehensive tool to analyze EMSO ERIC data
title_short MOODA, a comprehensive tool to analyze EMSO ERIC data
title_full MOODA, a comprehensive tool to analyze EMSO ERIC data
title_fullStr MOODA, a comprehensive tool to analyze EMSO ERIC data
title_full_unstemmed MOODA, a comprehensive tool to analyze EMSO ERIC data
title_sort mooda, a comprehensive tool to analyze emso eric data
publisher European Geosciences Union
publishDate 2019-04
url http://hdl.handle.net/10261/241202
work_keys_str_mv AT bardajiraul moodaacomprehensivetooltoanalyzeemsoericdata
AT pierajaume moodaacomprehensivetooltoanalyzeemsoericdata
AT huberrobert moodaacomprehensivetooltoanalyzeemsoericdata
AT roderoivan moodaacomprehensivetooltoanalyzeemsoericdata
AT danobeitiajuanjose moodaacomprehensivetooltoanalyzeemsoericdata
AT favalipaolo moodaacomprehensivetooltoanalyzeemsoericdata
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