Data management and interactive visualizations for the evolving marine biodiversity observation network

Assessing the current state of and predicting change in the ocean’s biological and ecosystem resources requires observations and research to safeguard these valuable public assets. The Marine Biodiversity Observation Network (MBON) partnered with the Global Ocean Observing System Biology and Ecosyst...

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Detalles Bibliográficos
Autores: Benson, Abigail, Murray, Tylar, Triñanes Fernández, Joaquín Ángel, deWitt, Lynn M.
Tipo de recurso: artículo
Fecha de publicación:2021
País:España
Institución:Universidad de Santiago de Compostela (USC)
Repositorio:Minerva. Repositorio Institucional de la Universidad de Santiago de Compostela
Idioma:inglés
OAI Identifier:oai:minerva.usc.gal:10347/45214
Acceso en línea:https://hdl.handle.net/10347/45214
Access Level:acceso abierto
Palabra clave:Ocean’s biological and ecosystem resources
Data Management
Observations
Evolving Marine Biodiversity Observation Network
Descripción
Sumario:Assessing the current state of and predicting change in the ocean’s biological and ecosystem resources requires observations and research to safeguard these valuable public assets. The Marine Biodiversity Observation Network (MBON) partnered with the Global Ocean Observing System Biology and Ecosystems Panel and the Ocean Biodiversity Information System to address these needs through collaboration, data standardization, and data sharing. Here, we describe the generalized MBON data processing flow, which includes several steps to ensure that data are findable, accessible, interoperable, and reusable. By following this flow, data collected and managed by MBON have contributed to our understanding of the Global Ocean Observing System Essential Ocean Variables and demonstrated the value of web-based, interactive tools to explore and better understand environmental change. Although the MBON’s generalized data processing flow is already in practice, work remains in building ontologies for biological concepts, improving processing scripts for data standardization, and speeding up the data collection-to-sharing timeframe