AI Readiness, AI Reproducibility, and Data Stewardship

This session will discuss lessons learned and emerging community practices as they relate to AI Readiness and AI Reproducibility. Insights into ways to leverage Gen-AI and LLMs for data stewardship will be shared, as well as open research questions, and gaps in practices at the intersection of AI and data. Please bring your own practices and insights to the session so they can inform the NSF-funded FAIR in Machine Learning, AI Readiness, (AI) Reproducibility Research Coordination Network (FARR). This presentation was part of the UC Love Data Week 2025 program (https://uc-love-data-week.github.io).

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-02-13
DOI
https://doi.org/10.5281/zenodo.14926743
Primary Topic
Research Data Management Practices
Type
article
Field-Weighted Citation Impact
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article

AI Readiness, AI Reproducibility, and Data Stewardship

Zenodo (CERN European Organization for Nuclear Research)
Research Data Management Practices
article

AI Readiness, AI Reproducibility, and Data Stewardship

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Abstract

This session will discuss lessons learned and emerging community practices as they relate to AI Readiness and AI Reproducibility. Insights into ways to leverage Gen-AI and LLMs for data stewardship will be shared, as well as open research questions, and gaps in practices at the intersection of AI and data. Please bring your own practices and insights to the session so they can inform the NSF-funded FAIR in Machine Learning, AI Readiness, (AI) Reproducibility Research Coordination Network (FARR). This presentation was part of the UC Love Data Week 2025 program (https://uc-love-data-week.github.io).

Zenodo (CERN European Organization for Nuclear Research)
San Diego Supercomputer Center (US)
Gender equality
Openalex Percentile: Top 43%
Research Data Management Practices
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AI Readiness, AI Reproducibility, and Data Stewardship · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS