[Esip-datareadiness] Reminder: ESIP Data Readiness Cluster November Meeting [11/21 1pm EST/UTC-5]

[Douglas Rao - NOAA Affiliate]

Dear all,

Apologies for the late reminder for our cluster meeting as I just returned
from travels.

For our November cluster call, the main agenda items are listed below.

   - Planning for the ESIP January Meeting session - jointly with
   Information Quality Cluster (see session proposal below) (20 minutes)
   - Cross-walk with CEOS ARD specification template (20 minutes)
   - AI-readiness checklist primer development (20 minutes)

You can join the meeting via the Zoom link on the ESIP Community Calendar
<https://www.esipfed.org/get-involved/community-calendar>.

ESIP January Meeting Session Proposal
*Session title*: Embracing Data Quality for AI-ready Open Data
*Session description*: This joint session is a collaboration between the
Information Quality Cluster and the Data Readiness Cluster focusing on
various perspectives of data quality that are relevant to artificial
intelligence (AI) applications and development. The ESIP Data Readiness
Cluster has been working on the development of a community guideline for
assessing the AI-readiness of open data and moving towards improved
AI-readiness for open environmental data. Data quality is critical in
defining AI-ready data during the process of developing the community
guidelines. The ESIP Information Quality Cluster collaboratively identifies
opportunities for improving the quality of data, software, and related
research products and services.

This joint session plans to focus on four perspectives of data quality – 1)
how data producers determine and provide quality information about the
data, 2) how data repositories disseminate quality information of the data
and assist users in identifying/accessing the relevant data, 3) how data
users (particularly AI/ML developers) use quality information in their data
processing workflow, and 4) how can an interactive process between data
producers and users as well as technologies improve the characterization of
data quality.

The session will include three to four invited presentations that cover
each perspective outlined above and conclude with an interactive discussion
on how the community can work together towards a common practice to provide
data quality information that enables trusted applications of Earth science
data, including the rapid development of AI/ML applications.

-Douglas

-- 
Douglas Rao, Ph.D. (he/him/his)
Research Scientist
North Carolina State University <http://www.ncsu.edu>
Cooperative Institute for Satellite Earth System Studies (CISESS)
<http://www.ncics.org>
NOAA National Centers for Environmental Information
<http://www.ncei.noaa.gov>
151 Patton Ave. Asheville, NC 28801
+1.828.271.4903

I work on a flexible work schedule and across a number of time zones.
Apologies for any out of hours email.

"Every individual matters. Every individual has a role to play. Every
individual makes a difference.” – *Dr. Jane Goodall*
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