IEEE 27th International Conference on Information Reuse and Integration for Data Science 2026

IEEE IRI 2026 is the 27th edition of the International Conference on Information Reuse and Integration for Data Science. The conference focuses on the role of information reuse and integration in modern AI and data science, emphasizing how data, knowledge representations, and reusable computational systems can be combined to support better decision making in real-world settings. The official description highlights IRI as a forum where researchers and practitioners from academia, industry, and government present theoretical and applied work that addresses practical problems with practical solutions. The conference is organized around three major themes—information reuse, information integration, and reusable systems—and continues a long-standing tradition of selective review and interdisciplinary exchange. The 2026 edition will be held in Seattle and includes regular research papers, application and industry papers, short papers, posters, workshops, and plenary talks.

Information Integration: multimodal information fusion; information science and theory; AI and security; symbolic AI; hallucination detection and mitigation in AI; novel AI applications in computer vision, computer forensics, security, fake/forgery detection, robotics, recommender systems, and biomedical areas. Information Reuse: data lifecycle reuse; afterlives of data in AI/ML models; preventing model collapse via improved data lineage; knowledge graphs; ontologies, variable alignment, and contextual metadata; cross-domain and multilingual metadata systems; reuse in LLM and AI training data; interoperability and cross-disciplinary reuse; linking datasets from different domains or formats; tools for data transformation and harmonization. Reusable Systems: acceleration of AI system reuse and reuse efficiency; brain-computer interface applications and algorithms; reusable AI for edge and IoT; reusable AI in industry applications; software and systems reuse and reusability; software sustainability and reuse economics; software maintenance and life-cycle management; software reliability, robustness, and dependability; system applications in autonomous vehicles, business, education, engineering, healthcare, IoT, multimedia, NLP, robotics, science, security, social networking, space, and vision.