From the Oceans to the Cloud: Opportunities and Challenges for Data, Models, Computation and Workflows

Abstract

Intent: Explores integrating the use of cloud-based data and how scientists can access large volumes of diverse, current and authoritative data, addresses the problem of locating and using large amounts of scientific data. The Section "Architectures for Real-Time Data Management and Services for Observations" describes streaming data and an architecture for making it easy to gather data. Also see Johanson et al. (2016). Cloud-Based Management of Scientific Data-Storing Data in the Cloud Intent: Explores storing and managing data in the cloud. Addresses the problem of ever increasing data quantities with decreasing budgets for data management. Explores the ways scientific projects can meet data access and dissemination requirements such as the U.S. Public Access to Research Results (PARR) mandate (Holdren, 2013). The section on the NOAA Big Data Project and open data and archiving are examples of this pattern. Also see Meisinger et al. (2009). Computing Infrastructure for Scientific Research Intent: Explores the ways in which cloud computing, in the form of PaaS or IaaS could be used as part of a research program and for teaching. It addresses the need for larger computational capabilities, especially under constrained budgets. The modeling efforts described in later sections are examples of this pattern.

Ocean FAIR Data Services

“…To progress toward increasing FAIRness of ocean data, there is a need to introduce the why and how of FAIR dataic to early career scientists in marine science so that adoption of these principles and this approach to data management becomes second nature and a natural part of doing ocean observations. We realize that future graduate students might not even go to sea but receive the data they need from autonomous platforms delivered through various integrated data services (Vance et al, 2019). Hodson (2018) outline several recommendations to foster the FAIR principles in a recent EU report.…”

Data Interoperability Between Elements of the Global Ocean Observing System

“…Therefore it is essential to support development of robust flexible server side subsetting tools if data consumers are to fully exploit the high volumes of information created by the modeling community. A promising area of development is in server side processing, especially when combined with cloud computing architectures (Vance et al, 2019).…”

Analysis and Visualization of Coastal Ocean Model Data in the Cloud

“…While there are numerous benefits to this framework, there are also some remaining challenges [40,41]. One important challenge is cost.…”