Unidata Science Gateway on the XSEDE Jetstream Cloud

<div><div>With the goal of better serving our community and in fulfillment of objectives articulated in "Unidata 2018: Transforming Geoscience through Innovative Data Services," Unidata is investigating how its technologies can best make use of cloud computing. The observation that science students and professionals are spending too much time distracted by software that is difficult to access, install, and use, motivates Unidata’s investigation. In addition, cloud computing can tackle a class of problems that cannot be approached by traditional, local computing methods because of its ability to scale and its capacity to store large quantities of data. Cloud computing accelerates scientific workflows, discoveries, and collaborations by reducing research and data friction. We aim to improve “time to science” with the NSF-funded XSEDE Jetstream cloud. We describe a Unidata science gateway on Jetstream. With the aid of open-source cloud computing projects such as OpenStack and Docker on Linux VMs, we deploy a variety of scientific computing resources on Jetstream for our scientific community. These systems can be leveraged with data-proximate Jupyter notebooks, and remote visualization clients such as the Unidata Integrated Data Viewer (IDV) and AWIPS CAVE. This gateway will enable students and scientists to spend less time managing their software and more time doing science.</div></div><div><br></div

Met/Ocean Modeling Workflows on XSEDE via HPC & Cloud

Met/Ocean Modeling Workflows on XSEDE via HPC & Clou

A Cloud-based Science Gateway for the Geoscience Community

A Cloud-based Science Gateway for the Geoscience Community with End-to-end Workflows on the Jetstream Cloud Computing Platform<br><div><br></div

Reducing Time to Science: Unidata and JupyterHub Technology Using the XSEDE Jetstream Cloud

<div>Cloud computing can accelerate scientific workflows, discovery, and collaborations by reducing research and data friction. We describe the deployment of Unidata and JupyterHub technologies on the NSF-funded XSEDE Jetstream cloud. With the aid of virtual machines and Docker technology, we deploy a Unidata JupyterHub server co-located with a Local Data Manager (LDM), THREDDS data server (TDS), and RAMADDA geoscience content management system. We provide Jupyter Notebooks and the pre-built Python environments needed to run them. The notebooks can be used for instruction and as templates for scientific experimentation and discovery. We also supply a large quantity of NCEP forecast model results to allow data-proximate analysis and visualization. In addition, users can transfer data using Globus command line tools, and perform their own data-proximate analysis and visualization with Notebook technology. These data can be shared with others via a dedicated TDS server for scientific distribution and collaboration. There are many benefits of this approach. Not only is the cloud computing environment fast, reliable and scalable, but scientists can analyze, visualize, and share data using only their web browser. No local specialized desktop software or a fast internet connection is required. This environment will enable scientists to spend less time managing their software and more time doing science. </div><div><br></div

A Unidata JupyterHub Server: An Online PyAOS Resource for Students and Educators

<div>In recent years, the Python programming language coupled with Jupyter notebooks have become vital tools for atmospheric science educators and their students. Python’s batteries-included philosophy along with an increasingly vast array of scientific libraries make it an excellent choice for explaining scientific concepts. Programming notebooks excel at teaching objectives by allowing expository prose and equations to be interspersed with executable cells of code performing data analysis and visualization. Installing this software, however, can be intimidating, time-consuming and confusing. We describe the deployment of a JupyterHub server on the NSF-funded Jetstream cloud targeted at students and educators. JupyterHub is a multi-user server for Jupyter notebooks. We provide Jupyter notebooks from three Unidata projects: Unidata Python Workshop, Unidata Notebook Gallery, Unidata Online Python Training. These notebooks include pre-built Python environments needed to run them. The notebooks can be used for instruction and as templates for scientific experimentation. This Unidata JupyterHub server will enable students and educators to spend less time managing their software and more time learning and teaching. </div><div><br></div

Unidata and data-proximate analysis and visualization in the cloud

Unidata and data-proximate analysis and visualization in the clou

Science Gateways in the Cloud, a Platform for Providing Modern Scientific Workflows for Reproducible Research and Collaboration

The advent and maturity of cloud computing technologies and tools have opened new avenues for addressing both Big Data and Open Science challenges to accelerate scientific discoveries. There is broad consensus that as data volumes grow rapidly, it is particularly important to reduce data movement and bring processing and computations to the data. Data providers also need to give scientists an ecosystem that includes data, tools, workflows and other end-to-end applications and services needed to perform analysis, integration, interpretation, and synthesis - all in the same environment or platform. Instead of moving data to processing systems near users, as is the tradition, one will need to bring processing, computing, analysis and visualization to data – so called data-proximate workbench capabilities, also known as server-side processing. <br><br>Cloud-based Science Gateways, through online portals and user-friendly interfaces, provide access to a range of resources that are of interest to a community of researchers, educators, and students, including datasets, tools, services, and workspaces. These offerings permit researchers to access a suite of capabilities to not only achieve reproducible science in a web-based workspace but also provide a platform for collaboration and conducting team science. In this session, speakers will present on-going efforts to develop cloud-based Science Gateways to facilitate end-to-end scientific workflows for communities of researchers, educators, and students in the geosciences. <br