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For over 20 years, ESIP meetings have brought together the most innovative thinkers and leaders around Earth observation data, thus forming a community dedicated to making Earth observations more discoverable, accessible and useful to researchers, practitioners, policymakers, and the public. The theme of this year’s meeting is Leading Innovation in Earth Science Data Frontiers.
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Thursday, July 22 • 4:00pm - 5:30pm
AI Data Readiness: What Does ML Training Data Interoperability Mean to You? Examples and Use Cases

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The results from machine learning are only as good as their training data. At the same time, it’s difficult and time consuming to develop quality training data. It would be valuable if we could reuse training data in other contexts. What is necessary to make that happen? 

In this session we explore several examples of preparing and sharing ML training data and then explore whether there are certain attributes or processes that we can standardize in order to make trains data more interoperable.

David Roy, Univ. Mich., on the reuse of burned area data from Landsat
Gabriel Tseng, Univ MD., on the collection and later sharing of training data on agricultural conditions
Christian Schroeder de Witt, Univ. Oxford, on a benchmark data set for precipitation prediction

Community exercise to refine most effective ways to enhance ML training data reusability and readiness.

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Organizers & Speakers
avatar for Mark Parsons

Mark Parsons

University of Alabama in Huntsville

Aleksandar Jelenak

The HDF Group
avatar for Tyler Christensen

Tyler Christensen

Oceanographer, NOAA / National Ocean Service
avatar for Douglas Rao

Douglas Rao

I am currently a Postdoctoral Research Scholar at North Carolina Institute for Climate Studies, also affiliated with NOAA National Centers for Environmental Information. My current research at NCICS focuses on generating a blended near-surface air temperature dataset by integrating... Read More →

Thursday July 22, 2021 4:00pm - 5:30pm EDT