MOODA, a comprehensive tool to analyze EMSO ERIC data

• Main Authors: Bardají, Raúl, Piera, Jaume, Huber, Robert, Rodero, Iván, Dañobeitia, Juan José, Favali, Paolo
• Format: Conference Object
• Language: English
• Published: European Geosciences Union 2019
• Subjects: North Atlantic
• Online Access: http://hdl.handle.net/10261/241202

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