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Welcome to the Summer Meeting for the Earth Science Information Partners (ESIP)! The 2017 theme is Strengthening Ties Between Observations and User Communities. The theme is based on one of the goals in the 2015 - 2020 ESIP Strategic Plan, which provides a framework for ESIP’s activities over the next three years.
  • Check out the full 2017 Summer Meeting Guide here -> http://bit.ly/ESIP_Sum_Guide_2017
  • Find a map if the Indiana Memorial Union HERE.
  • There will be lots going on in Slack during the meeting, find your invite HERE. #summer_mtg

Miss the plenary? Click here to check it out!
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Wednesday, July 26 • 4:00pm - 5:30pm
Geoscience in the Cloud: Data-Proximate Science to Address Big Data and Open Science Challenges

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The advent of cloud computing has opened new avenues for not only addressing both big data and Open Science challenges to accelerate scientific discoveries. However, to successfully leverage the enormous potential of cloud technologies, it will require the data providers and the scientific communities to develop new paradigms to enable next-generation workflows and transform the conduct of science.

In this session, speakers will present ongoing work to facilitate a new paradigm for doing science by offering a suite of tools, resources, and platforms to leverage cloud technologies for addressing both big data and Open Science/reproducibility challenges, and engage in a community dialog on the opportunities and challenges of the new paradigm.

4:00-4:20 “Data Proximate Computing in the Cloud”,  Mohan Ramamurthy (Unidata Program Center)

Rapid advances in computing, communications, and observational technologies — along with concomitant advances in high-resolution modeling, ensemble and coupled-systems predictions of the Earth system — are revolutionizing nearly every aspect of the geosciences. Modern data volumes from high-resolution ensemble prediction/projection/simulation systems and next-generation remote-sensing systems like hyper-spectral satellite sensors and phased-array radars are staggering. In this talk we will discuss strategies, tools and techniques Unidata is taking to address these issues.

4:20-4:40 “Jetstream Cloud”,  Jeremy Fischer (Indiana University)

NSF’s Jetstream Cloud is a Infrastructure-as-a-Service platform comprised of two geographically isolated OpenStack+Ceph clusters, each supporting hundreds of virtual machines and data volumes. The two cloud systems are integrated via a user-friendly web application that provides a user interface for common cloud computing operations, authentication to XSEDE via Globus, and an expressive set of web service APIs. Jetstream enables on-demand access to interactive, user-configurable computing and analysis capability. It also seeks to democratize access to cloud capabilities and promote sharable, reproducible research. This talk will describe Jetstream in greater detail, as well as how its unique combination of hardware, software, and user engagement support the "long tail of science".

4:40-5:00 “Web APIs in the Cloud”, James Gallagher (OPeNDAP)

The OPeNDAP and HDF groups have been working some experiments in cloud-based data servers for NASA. Our results to-date include cost- and performance-modeling for three distinct architectures serving two test datasets (large collections of AIRES and MERRA data). Our study exclusively used AWS EC2 and S3.

5:00-5:20 “Met/Ocean Modeling Workflows on XSEDE via HPC & Cloud”, Rich Signell (USGS) and Julien Chastang (Unidata Program Center)

Met/ocean modeling workflows have technical challenges: compute power with fast connections for producing simulations, large storage space for output, powerful tools for analysis and visualization, and specialized services for effectively distributing data.  To address this issues, we have developed a sample end-to-end workflow solution for generating and handling simulation data on NSF XSEDE HPC and cloud computing resources.  Simulations are conducted on HPC systems (e.g. “Bridges”, “Stampede”) and then transferred to the Jetstream Cloud via Globus GridFTP. Model output can then be analyzed and visualized using JupyterHub, keeping computations close to the data, and taking advantage of custom Python environments that are preinstalled.  Data can also be shared with colleagues outside XSEDE using a THREDDS Data Server running on Jetstream.  The components are packaged as Docker containers for deployment on other systems.

5:20-5:30 “Next Steps and Challenges” (Speakers and Attendees)


Speakers | Moderators
avatar for Julien Chastang

Julien Chastang

Software Engineer, UCAR - Unidata
Scientific software developer at UCAR-Unidata.
avatar for Rich Signell

Rich Signell

Oceanographer, USGS Coastal and Marine Geology Program
Ocean Modeling, Python, NetCDF, THREDDS, ERDDAP, UGRID, SGRID, CF-Conventions, Jupyter, JupyterHub, CSW, TerriaJS


Wednesday July 26, 2017 4:00pm - 5:30pm
5 - Oak 900 E 7th St, Bloomington, IN 47405

Attendees (41)