[ESIP-all] Survey on AI-Ready Open Environmental Data

[Yuhan Douglas Rao]

Dear colleagues,



Do you use open environmental data in your artificial intelligence or
machine learning (AI/ML) research and development? Do you have experience
and ideas about what factors make data easier to use for AI/ML applications?



The Data Readiness <http://wiki.esipfed.org/Data_Readiness> collaboration
group of the Earth Science Information Partners (ESIP) <http://esipfed.org/> is
conducting a voluntary and anonymous survey to understand user requirements
for open environmental data that can enable AI/ML applications (i.e.,
AI-readiness). This survey may take you *20–25* *minutes* to complete.



Access the survey using this link - https://bit.ly/ai-ready-data. The
survey will be open until *22 December 2021 *and we will send one reminder
request to complete it.



Your inputs are much needed to help data producers and providers to
understand user requirements for AI-ready data and make improvements for
open environmental data. These improvements will benefit all AI/ML
application developers and general data users with less effort in cleaning
and preparing the data for their use cases.



Here’s why we think it’s worth investing your time. To our knowledge, this
is the first time that AI/ML practitioners have been asked about their
detailed data needs. Your input will be analyzed and compiled as an
environmental and Earth data community guideline to:


   - Inform data providers in evaluating existing open environmental
   datasets to assess their AI-readiness, helping data users discover data
   that already meets their needs.
   - Provide a consistent framework for different data users to assess
   AI-readiness and ensure data interoperability across different data centers.
   - Prioritize modernization and improvement efforts to improve open
   environmental data for AI/ML applications and general uses.
   - Set community standards for new dataset development.



We hope this collaborative effort coordinated by the Data Readiness group
of ESIP can produce community-driven requirements for AI-ready data and
lead to official data standards development to improve the usability of
open environmental data.



Thank you so much for your time. Please reach out If you have any questions
about the survey.



Best regards,

Yuhan “Douglas” Rao, NC State University, co-chair

Tyler Christensen, NOAA Center for Artificial Intelligence, co-chair

ESIP Data Readiness Cluster

(in collaboration with NASA ESDS Data Interoperability Working Group)
[image: NCICS] <http://ncics.org/> Yuhan (Douglas) Rao
*Postdoctoral Research Scholar*
Pronoun: he/him/his
North Carolina State University <http://ncsu.edu/>
North Carolina Institute for Climate Studies (NCICS) <https://ncics.org/>
151 Patton Ave, Asheville, NC 28801
e: yrao5 at ncsu.edu
o: +1 828 271 4903
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