

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.
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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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Geoffrey Fox, University of Virginia
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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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Notes
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Authors Do Not pay publication fees
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Articles are open access
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Guidelines
AI Magazine prefers expository articles, 6000-9000 words in length (including references and author biographies), without a lot of mathematical formalism.
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​Tentative Schedule
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Papers due: June 16, 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
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