IN008-08
Analyzing and download integrated oceanographic data from the EMSO FAIR data stack with the DataLab

Tuesday, 8 December 2020: 10:51
Virtual
Raul Bardaji, Marine Technology Unit - CSIC, Barcelona, Spain, Ivan Rodero, EMSO ERIC, CMO, Rome, Italy, Jaume Piera, ICM-CSIC, Department of Physical and Technological Oceanography, Barcelona, Spain, Paolo Favali, EMSO ERIC - European Multidisciplinary Seafloor and Water-Column Observatory, Rome, Italy and Juanjo Danobeitia, EMSO ERIC, Rome, Italy; Spanish National Research Council, UTM-CSIC, Barcelona, Spain
Abstract:
The European Multidisciplinary Seafloor and water column Observatory (EMSO) data management platform integrates harmonized ocean variables across EMSO data sources according to FAIR (Findable, Accessible, Interoperable, Reusable) principles and EOSC (European Open Science Cloud) guidelines. Core components of the EMSO FAIR data stack include the harmonization subsystem and the EMSO RESTful API to provide programmatic access to harmonized EMSO data and metadata. The harmonization subsystem has adopted key outcomes of the EMSODEV project, such as the Module for Ocean Observatory Data Analysis (MOODA). It is based on the OceanSites specifications, and it is a contribution of EMSO ERIC to the ENVRI-FAIR H2020 project.

Implementing the harmonization subsystem and RESTful API has enabled the development of EMSO data services, impacting EMSO’s capabilities, and facilitating the adoption of FAIR principles. In addition to facilitating data discovery, access, and download, it enables building tools, including data portals, dashboards, and data product generation tools. Enabled tools include the EMSO DataLab, a cloud-based framework that provides users with capabilities to preview, make custom graphs, combine and download integrated ocean data from EMSO ERIC observatories, and other oceanographic data sources.

The DataLab is built on top of the EMSO API to access data and deliver its functions intuitively and without the users' need to learn how the machine-to-machine interface works. The DataLab has been developed using engineering best practices and trend technologies for data management. It has been coded with Python, using libraries for web environments, oceanographic data management, and front-end tools for data science models, such as Flask, Plotly, Dash, and MOODA.

This work will present the EMSO DataLab by providing its architecture and logical design and elaborating on use case scenarios by combining and comparing data from different observatories in the Mediterranean Sea, the Black Sea, and the Atlantic Ocean.

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