Architecture of a data portal for publishing and delivering open data for atmospheric measurement

Abstract:

Atmospheric data are collected by researchers every day. Campaigns such as GOAmazon 2014/2015 and the Amazon Tall Tower Observatory collect essential data on aerosols, gases, cloud properties, and meteorological parameters in the Brazilian Amazon basin. These data products provide insights and essential information for analyzing and predicting natural processes. However, in Brazil, it is estimated that more than 80% of the scientific data collected are not published due to the lack of web portals that collect and store these data. This makes it difficult, or even impossible, to access and integrate the data, which can result in the loss of significant amounts of information and significantly affect the understanding of the overall data. To address this problem, we propose a data portal architecture and open data deployment that enable Big Data processing, human interaction, and download-oriented approaches with tools that help users catalog, publish and visualize atmospheric data. Thus, we describe the architecture developed, based on the experience of the Atmospheric Radiation Measurement Data Center, which incorporates the principles of FAIR, the infrastructure and content management system for managing scientific data. The portal partial results were tested with environmental data from contaminated areas at the University of São Paulo. Overall, this data portal creates more shared knowledge about atmospheric processes by providing users with access to open environmental data.

Reference:
QUILLE, Rosa Virginia Encinas; ALMEIDA, Felipe Valencia de; OHARA, Mauro Yuji; CORRÊA, Pedro Luiz Pizzigatti; FREITAS, Leandro Gomes de; ALVES-SOUZA; Solange Nice; ALMEIDA JUNIOR, Jorge Rady de; DAVIS, Maggie; PRAKASH, Giri. Architecture of a data portal for publishing and delivering open data for atmospheric measurement. Environmental Research and Public Health, v.20, n.7, 20p., 2023.

Access to the article on the Journal’s website:
https://www.mdpi.com/1660-4601/20/7/5374

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