Past Events

September 8-12 , 2024, Stresa, Italy International Computing in Atmospheric Sciences (iCAS) 2024, Theme: Interdisciplinary and International Collaboration for Advancing Earth System Science .

May 29-31, 2024, Boulder, CO.Innovations in Open Science (IOS) Planning Workshop: Community Expectations for a Geoscience Data Commons,

May 14, 2024 , RDA Updates and feedback on the FAIR4ML IG activities

February 21, 2024 ESIP CDF Cluster. What does "AI-readiness" mean for geoscience data repositories? by Yuhan (Douglas) Rao (Video)

December 11-15, 2023; San Francisco, AGU23

• Implementing FAIR for AI: towards a community roadmap. Karen Stocks, UC San Diego; Yuhan Douglas Rao, NC State U; December 11

• FAIR in ML, AI Readiness, & Reproducibility Research Coordination Network (FARR RCN) - Meet and Greet; 13 December

• IN43A-05 User Registration and Authentication - Considerations for Data Repositories. Karen Stocks, Univ. of California San Diego and Council of Data Facilities; 14 December

• FARR at AGU23

December 5, 2023 AI Reproducibility Webinar: Embracing open science principles to improve reproducibility in Environmental Data Science. Alejandro Coca-Castro, Research Fellow at The Alan Turing Institute

November 12-17, 2023 • Denver SC 23,

• Machine Learning from the Data’s Perspective: Data-centric AI, AI readiness and AI Reproducibility. BoF. Organizers: Christine Kirkpatrick, Geoffrey Fox, Vijay Janapa Reddi. November 14

• GO FAIR US: FAIR Workflows for HPC. Presenter: Sean Wilkinson, Oak Ridge National Lab. November 15 at the San Diego Supercomputer Center Booth.

• Research Software Engineers in HPC (RSE-HPC-2023) Workshop. Session chairs: Sandra Gesing, Daniel S. Katz, Simon Hettrick, Charles Ferenbaugh. November 12

• Leveraging Large Language Models to Build and Execute Computational Workflows. Workshop paper presentation. Authors/presenters: Alejandro Duque, Abdullah Syed, Kastan Day, Matthew Berry, Daniel S. Katz, Volodymyr Kindratenko. November 13

• RSEs in HPC Centers: Funding, Coordinating, Doing. Panel. Moderator: Daniel S. Katz. Panelists: Gabrielle Allen, Neil P. Choe Hong, Alison M. Kennedy, Fabio Kon, Miranda Mundt. November 14

• Fine-Grained Policy-Driven I/O Sharing for Burst Buffers. Conference paper presentation. Authors: Ed Karrels, Lei Huang, Yuhong Kan, Ishank Arora, Yinzhi Wang, Daniel S. Katz, William Gropp, Zhao Zhang. November 16

October 23-26, 2023 • Salzburg, SciDataCon

• AI / ML and Repository - can we believe the hype and are we ready? Oct. 23

• AI and ethics in dialogue with data science. Oct. 26

October 23-26, 2023 • Salzburg, RDA P21

• Mastering the Art of Research Software Metadata and Metrics. Oct. 23

• FAIR for Machine Learning (FAIR4ML) IG, Building towards FAIR for Machine Learning. Oct. 25

• Bridging the Data/HPC Divide: lessons learned from community talks. Oct. 25

• Policies for Advancing Research Software in Research Performing Organizations (PRO4RS). Oct. 26

August 22, 2023. Strategies for Machine Learning Reproducibility - Webinar

June 27, 2023. Building Upon the EarthCube Community - A Geoscience and Cyberinfrastructure Workshop. Marina Del Rey (Los Angeles). Title: Working towards AI-ready Geoscience Data Repositories.

April 20, 2023.  “Accelerating and Deepening Approaches to FAIR Data Sharing: A Workshop” sponsored by the National Academies Board on Research Data and Information. Speakers included representatives from NLM, NASA, and NSF who spoke about “After the Nelson Memo: New Priorities and Opportunities for Research Data.” 

March 22, 2023. Research Data Alliance (RDA) Plenary 20.  FARR’s co-hosted  RDA FAIR 4 ML IG session, Defining the roadmap towards FAIR for Machine Learning. The outcomes of this meeting include 1. agreement that there are several open challenges around ML that require community effort in addressing them (such as ethics and IP rights); 2. There is a keen interest in pursuing FAIR for ML, especially around particular implementations (such as metadata and PIDs); 3. A concrete action for the next period is to start the work around a white paper on FAIR for Machine Learning.

January 26, 2023. ESIP session hosted by Data Readiness Cluster, Machine Learning Cluster, and FARR RCN. FAIR for AI in Geoscience: from AI-Ready Data to Practical AI Models.

December 12, 2022. AGU.  Listening Session – Advancing FAIR, AI-readiness, and reproducibility for AI in Geoscience.