2018 ESIP Summer Meeting

Session Description: When data is shared in the cloud, anyone can analyze it without having to download it or store it themselves, which lowers the cost of new product development, reduces the time to scientific discovery, and can accelerate innovation. However, staging large-scale datasets for analysis in the cloud requires consideration of how data should be prepared and organized to allow fast, efficient, and programmatic access from distributed computing systems. This workshop will provide a forum for members of the community to share lessons learned as they explore ways to use the cloud to expand access to data. It seeks to encourage dialog between users interested in leveraging data in the AWS Cloud for research and application development.


Data Optimization for the cloud: Tools and Services (July 17th, 9:30 am – 11:30 am):

AGENDA

Joe Flasher, AWS (10 min)
Introduction

Dan Pilone, Element84 (10 min)
Title: Interdisciplinary research, heterogeneous data, and the case for Archives of Convenience
Description: Earth Science data is measured in petabytes and represents decades of data collection, evolution of technology and practices, and provides an unparalleled view of our planet. The pace of change is only accelerating: NASA and other agencies are on their way to making hundreds of Petabytes of data available in the cloud, highly scalable processing and analysis architectures and tools are in active use with more being developed every day, and each of these brings with it opportunities for optimization and innovation. This talk demonstrates leveraging the elastic nature of the cloud using GOES-16 data to create ephemeral Archives of Convenience, targeting individual researcher needs, optimized for their problems and tool suites, instead of trying to settle on a single "cloud optimized" solution.

Ilya Khamushkin, Intertrust (10 min)
Title: Earth Data for Everyone
Description: At Intertrust, we believe that working with Earth science data should be easy. Too often file formats, transfer protocols, and cumbersome access interfaces make it difficult for users without domain knowledge to incorporate these data into their workflows. During this session we’ll share our experiences from the past five years building and operating the Planet OS Datahub, our cloud-based data as a service platform.

Marty J. Sullivan, Cornell University (10 min)
Title: The Need for Data Lakes in Climate Science
Description: Climate data is massive. The archive data formats used in the field are difficult to retrieve and analyze, they also come from so many different sources. Learn how and why Cornell University’s department of Earth & Atmospheric Sciences is moving toward the concept of building geospatial data lakes in Amazon S3 and using tools like Amazon Athena.

Sudhir Shrestha, ESRI (10 min)
Title: Scientific Earth Science Data to Cloud Optimized Web Services;
Description: Working with earth science data to extract information sometimes can be challenging due to its diversity and complexity. In this session, we will demonstrate real world examples of successful application of open earth science data in ArcGIS platform. We will share briefly the workflow of optimized scientific data management (ingesting, managing, analyzing and sharing) in cloud and how you can quickly spin up the web applications to share your information products including analytics to larger community. We will share few use cases, such as NOAA High Resolution Refresh Radar (HRRR), Sentinel data and other webmap applications that demonstrate how we access large collections of near real-time data that are stored on-premise or on the cloud, disseminate them dynamically, process and analyze them on-the-fly, and serve them to a variety of geospatial applications.

General discussion (10 min)

Breakout groups: focus on tools and services (30 minutes)

(Continue conversation over coffee - 30 minutes)