[CODATA-international] AGU2020 (virtual): Digital Transformation of Earth Science Cloud: Data-Oriented and Self-Optimizing Architectures and Workflows

[Christian Pagé]

(sincere apologies for cross-posting)...

 
Dear colleague,

We would like to encourage you to submit an abstract to the following session of the Fall 2020 American Geophysical Union meeting Virtual (mostly) and in San Francisco, CA (possibly) (December 7-11).
It is a great opportunity because AGU2020 will be mostly virtual, meaning that more people can have the opportunity to present and attend the conference.

Digital Transformation of Earth Science Cloud: Data-Oriented and Self-Optimizing Architectures and Workflows (IN Session ID# 104374)
https://agu.confex.com/agu/fm20/prelim.cgi/Session/104374 <https://agu.confex.com/agu/fm20/prelim.cgi/Session/104374> 
 
The goal of this session is to discuss innovative approaches and new ideas on data distribution platforms, architectures, and workflows themselves to support research in Earth and Space Sciences. There will also be invited speakers in this session.

Computational and information technology concepts have evolved to create virtualization technologies and turned cloud computing from a buzzword into an emerging trend. Increasingly, scientists are performing analyses, sharing data and collaborating on research papers in the cloud. Scientists must rethink how they will leverage this new environment to analyze their model and observational data in the future when our “workstations” are in the cloud. Developers need to reach across infrastructure boundaries transparently with scalable solutions, while effectively moving processing and analysis, but not control, away from users and closer to the data. Innovative approaches are needed to support the scientific data life cycle within widely distributed and diverse infrastructures. Methods borrowed from optimization, machine learning and semantics, not excluding others, can be useful towards reducing complexity while increasing usefulness and uptake. Contributions may include novel architectures or use-cases that support seamless access and processing of large scientific datasets, e.g. CMIP6.
 
Presentations are encouraged on, but are not limited to:
            • Novel research architectures;
            • Workflows and intelligent optimization;
            • HPC integration and data-driven approaches, including HPC on the Cloud;
            • Provenance;
            • Front-ends and services designed for large-scale data-oriented solutions.

We look forward to a stimulating set of talks and discussions, and hope that you will consider participating. Please note that the strict deadline for abstract submission is Wednesday, 29 July at 23:59 EDT/03:59 +1 GMT.

To submit an abstract to this session:
https://agu.confex.com/agu/fm20/in/papers/index.cgi?sessionid=104374 <https://agu.confex.com/agu/fm20/in/papers/index.cgi?sessionid=104374>
and general information about abstract submissions:
https://agu.confex.com/agu/fm20/prelim.cgi/Home/0 <https://agu.confex.com/agu/fm20/prelim.cgi/Home/0>

Please circulate this to your colleagues who may have interest in this session.  We look forward to receiving your contribution.

Best regards,

Christian Pagé
CERFACS, France
 
Tsengdar J Lee
NASA, US
 
Iraklis Klampanos
National Centre for Scientific Research “Demokritos”, Greece




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