2021 ESIP Winter Meeting

Session Description: Artificial intelligence (AI) is a leading technology that may transform the research and applications of Earth and space science and amplify the benefits to society. One of the key bottlenecks limiting exploring/applying AI in Earth and space sciences at scale is the lack of analysis-ready data for AI applications. It's often cited that researchers can spend 80% of their project time wrangling with the large heterogeneous volumes of data that are needed for the application. To accelerate the application of AI in Earth and space sciences, it is essential to minimize users’ burden of data wrangling by providing AI-ready data with machine-readable metadata that is not only compliant with FAIR principles but also tuned for AI applications (e.g., data biases). In this session, we will convene a panel of stakeholders from data providers, users, and data engineers to discuss the path of defining the requirements and creating inter-organization matrices to assess and describe data “AI-readiness”. The outcome of this session will be summarized in a short report, and the document will be used as a guiding document to pursue further collaboration across Earth and space science data communities on this topic.

Session Agenda:

1. Session Scope (5 min)
2. Establish A Baseline (5 min)
3. Invited Presentations (Gregory Dusek, Kirstine Dale, Sophie Hou) (25 min)
4. Breakout Discussion (35 min)
5. Setting Community-Driven Priority (15 min)
6. Close & Depart (5 min)

Slides & Relevant Documents:

• Data AI-readiness matrix (presented during 2nd NOAA AI Workshop).
• Session slide deck
• All slides from speakers can be found at the bottom of this page.

Relevant Sessions:

• Analysis Ready Data in Science and Industry (01/27 11:00 am -12:30 pm)
• Best Practices and Fundamental Challenges of AI in Earth and Space Sciences (01/28 1:30 pm - 3:00 pm)
• Research Showcase (01/27 6:00 pm - 7:30 pm)

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