Difference between revisions of "Data Readiness"
From Earth Science Information Partners (ESIP)
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===Activities=== | ===Activities=== | ||
+ | *Cluster May meeting (05/12 1PM ET) | ||
*Cluster kick-off meeting (04/12 12PM ET) – use this [https://www.google.com/url?q=https://us02web.zoom.us/j/89570417449?pwd%3DVE8vYzZ1SGRRRVc2aXE1c3dQM3JKZz09&sa=D&source=calendar&usd=2&usg=AOvVaw3low1xl_LpJoWUNRVXZxno Zoom link] to join. | *Cluster kick-off meeting (04/12 12PM ET) – use this [https://www.google.com/url?q=https://us02web.zoom.us/j/89570417449?pwd%3DVE8vYzZ1SGRRRVc2aXE1c3dQM3JKZz09&sa=D&source=calendar&usd=2&usg=AOvVaw3low1xl_LpJoWUNRVXZxno Zoom link] to join. | ||
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*'''Email List:''' [https://lists.esipfed.org/mailman/listinfo/esip-datareadiness esip-datareadiness@lists.esipfed.org] | *'''Email List:''' [https://lists.esipfed.org/mailman/listinfo/esip-datareadiness esip-datareadiness@lists.esipfed.org] | ||
− | * | + | *Monthly meeting: second Wednesday of each month (1-2 pm ET) |
− | |||
*'''Contact Co-Chairs:''' | *'''Contact Co-Chairs:''' |
Revision as of 06:35, May 14, 2021
The goal of the Data Readiness Cluster is to bring together ESIP members and external partners to discuss advancements, define standards, and develop tools for open environmental data for artificial intelligence (AI) applications. The main goals of the cluster include:
- Coordinate the development of the maturity matrix for AI-ready environmental data and promote the endorsement of national/international standards for AI-ready environmental data;
- Provide a platform for stakeholders to exchange experiences of curating, managing, providing, and using AI-ready open environmental data;
- Promote technology and tool development to improve the readiness of open environmental data for AI.
The cluster will meet regularly to implement the roadmap co-designed by group members. This group will seek active collaboration with other groups within and beyond ESIP to ensure our work benefits the general environmental data community. The group will seek active collaboration with Machine Learning, Cloud Computing, and other relevant clusters.
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