Suchergebnisse

© The Author(s), 2021. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Wang, Z. A., Michel, A. P. M., & Mooney, T. A. Accelerating global ocean observing: monitoring the coastal ocean through broadly accessible, low-cost sensor networks. Marine Technology Society Journal, 55(3), (2021): 82–83, https://doi.org/10.4031/MTSJ.55.3.52. ; The global coastal ocean provides food and other critical resources to human societies. Yet this habitat, for which many depend, has experienced severe degradation from human activities. The rates of human-induced changes along the coast demand significantly improved coverage of ocean observations in order to support science-based decision making and policy formation tailored to specific regions. Our proposal envisions developing a global network of low-cost, easily produced and readily deployed oceanographic sensors for use on a wide variety of platforms in the coastal ocean. A substantially large number of these sensors can thus be installed on existing infrastructure, ships of opportunity, and fishing fleets, or even individually along the coast, particularly in vulnerable and disadvantaged regions. This would vastly increase the spatiotemporal resolution of the current data coverage along the coast, allowing greater equitable access. It would also offer significant opportunities for partnership with communities, NGOs, governments, and other stakeholders, as well as a wide range of commercial and industrial sectors to develop and deploy sensors in scalable networks transmitting data in near-real time. Finally, it presents a vastly lowered bar for participation by citizen scientists and other engaged members of the public to address location-specific coastal problems anywhere in the world. ; National Science Foundation; Project Title "Collaborative Research: IDBR: Type A: A High-resolution bio-sensor to simultaneously measure the behavior, vital rates and environment of key marine organisms"; Award ...

14 pages, 4 tables, 4 figures.-- This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) ; Effective data management plays a key role in oceanographic research as cruise-based data, collected from different laboratories and expeditions, are commonly compiled to investigate regional to global oceanographic processes. Here we describe new and updated best practice data standards for discrete chemical oceanographic observations, specifically those dealing with column header abbreviations, quality control flags, missing value indicators, and standardized calculation of certain properties. These data standards have been developed with the goals of improving the current practices of the scientific community and promoting their international usage. These guidelines are intended to standardize data files for data sharing and submission into permanent archives. They will facilitate future quality control and synthesis efforts and lead to better data interpretation. In turn, this will promote research in ocean biogeochemistry, such as studies of carbon cycling and ocean acidification, on regional to global scales. These best practice standards are not mandatory. Agencies, institutes, universities, or research vessels can continue using different data standards if it is important for them to maintain historical consistency. However, it is hoped that they will be adopted as widely as possible to facilitate consistency and to achieve the goals stated above. ; Funding for L-QJ and AK was from NOAA Ocean Acidification Program (OAP, Project ID: 21047) and NOAA National Centers for Environmental Information (NCEI) through NOAA grant NA19NES4320002 [Cooperative Institute for Satellite Earth System Studies (CISESS)] at the University of Maryland/ESSIC. BT was in part supported by the Australia's Integrated Marine Observing System (IMOS), enabled through the National Collaborative Research Infrastructure Strategy (NCRIS). AD was supported in part by the United States National Science Foundation. AV and FP were supported by BOCATS2 Project (PID2019-104279GB-C21/AEI/10.13039/501100011033) funded by the Spanish Research Agency and contributing to WATER:iOS CSIC interdisciplinary thematic platform. MH was partly funded by the European Union's Horizon 2020 Research and Innovation Program under grant agreement N°821001 (SO-CHIC) ; Peer reviewed

Effective data management plays a key role in oceanographic research as cruise-based data, collected from different laboratories and expeditions, are commonly compiled to investigate regional to global oceanographic processes. Here we describe new and updated best practice data standards for discrete chemical oceanographic observations, specifically those dealing with column header abbreviations, quality control flags, missing value indicators, and standardized calculation of certain properties. These data standards have been developed with the goals of improving the current practices of the scientific community and promoting their international usage. These guidelines are intended to standardize data files for data sharing and submission into permanent archives. They will facilitate future quality control and synthesis efforts and lead to better data interpretation. In turn, this will promote research in ocean biogeochemistry, such as studies of carbon cycling and ocean acidification, on regional to global scales. These best practice standards are not mandatory. Agencies, institutes, universities, or research vessels can continue using different data standards if it is important for them to maintain historical consistency. However, it is hoped that they will be adopted as widely as possible to facilitate consistency and to achieve the goals stated above. ; Funding for L-QJ and AK was from NOAA Ocean Acidification Program (OAP, Project ID: 21047) and NOAA National Centers for Environmental Information (NCEI) through NOAA grant NA19NES4320002 [Cooperative Institute for Satellite Earth System Studies (CISESS)] at the University of Maryland/ESSIC. BT was in part supported by the Australia's Integrated Marine Observing System (IMOS), enabled through the National Collaborative Research Infrastructure Strategy (NCRIS). AD was supported in part by the United States National Science Foundation. AV and FP were supported by BOCATS2 Project (PID2019-104279GB-C21/AEI/10.13039/501100011033) funded by the Spanish Research Agency and contributing to WATER:iOS CSIC interdisciplinary thematic platform. MH was partly funded by the European Union's Horizon 2020 Research and Innovation Program under grant agreement N°821001 (SO-CHIC).