AI Magazine Special Issue
The FARR (FAIR in ML, AI-readiness and Reproducibility) Research Coordination Network is seeking articles for a special issue in AI Magazine at the intersection of the FAIR Principles and Machine Learning, AI Readiness and AI Reproducibility.
The special issue is interested in the following topics, with papers ideally addressing both research and practice aspects of more than one topic, and with other related topics also welcome:
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Improving AI reproducibility, and understanding sources of irreproducibility
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FAIR data practices and leveraging large language models (LLMs) for increasing the FAIRness of domain-specific applications
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Challenges and progress in making data AI-ready, including automation in dataset preparation
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Defining and improving FAIR in the context of AI, such as for AI models
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Metadata and AI, including potential standards for AI models
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Private AI models tailored to specific contexts
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Understanding and addressing gaps in standards and best practices across various fields
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The role of institutional stakeholders, such as data repositories
Special Issue Editors
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Daniel S. Katz, NCSA & SCDS & iSchool, University of Illinois Urbana-Champaign
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Christine R. Kirkpatrick, SDSC, University of California San Diego
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Yuhun (Douglas) Rao, North Carolina Institute for Climate Studies, North Carolina State University
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Lynne Schreiber, SDSC, University of California San Diego
Notes
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Authors Do Not pay publication fees
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Articles are open access
Guidelines
AI Magazine prefers expository articles, 6000-9000 words in length (including references and author biographies), without a lot of mathematical formalism.
Tentative Schedule
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Papers due: June 30, 2025
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Reviews due: August 15, 2025
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Paper submission addressing comments: September 30, 2025
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2nd reviews: October 31, 2025
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Final Papers: November 28, 2025
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Publication: Spring 2026