Assembling extreme-scale datasets for AI and data-intensive analysis was initially an obstacle in its own right, but we now find ourselves in an era where we need to think more deeply about managing, versioning, subsetting, and curating large numbers of such datasets. This workshop invites submissions that advance the theory, practice, and evaluation of data curation for large-scale, heterogeneous, and computationally intensive research environments. Our intent is to build a collaborative discussion around curation as an active lifecycle process supporting data quality, provenance, governance, reuse, and responsible analysis rather than just as a final-stage preservation activity.

Submissions may present new methods, conceptual frameworks, systems, infrastructure, empirical studies, benchmarks, or lessons learned from operational deployments. We particularly encourage work that connects curation requirements with scientific workflows, high performance and distributed computing, and the preparation and maintenance of data for AI and machine learning (E.G., AI-Ready).

We welcome submissions from researchers and practitioners across data curation, data management, scientific computing, information science, AI/ML, and related disciplines. Interdisciplinary contributions and papers that identify unresolved technical, organizational, or governance challenges are especially encouraged.

Topics of Interest

We invite submissions on topics including but not limited to:

• Practical experiences with success and failure of extreme scale dataset management
• Foundations of data curation: theory, life cycle models, conceptual frameworks, and evaluation models
• Provenance capture, representation, querying, validation, and management at scale
• Data life cycle curation of heterogeneous datasets to preserve privacy and community access requirements
• Actionable FAIR properties in computational science workflows: beyond FAIRness checklists, including limits, tradeoffs, and complementary curation mechanisms
• Data quality assessment, observability, validation, repair, and remediation for large-scale heterogeneous datasets
• Curation for AI/ML readiness including privacy, dataset versioning, and data life cycle management
• Automated and AI-assisted curation, including human-in-the-loop approaches
• Life cycle management and data curation in HPC, cloud, and distributed computing environments
• Curation tooling, infrastructure, middleware, and workflow-integrated services
• Case studies and lessons learned from scientific and enterprise deployments
• Benchmarks, metrics, and evidence for curation effectiveness and reuse outcomes

Submission Types

We solicit original research papers up to 8 pages in length (including references). Submitted papers should be in IEEE 2-column format and be formatted to IEEE Computer Society Proceedings Manuscript Formatting Guidelines available at https://www.ieee.org/conferences/publishing/templates.html.

We encourage the submission of complete and self-contained papers shorter than the above limit which align with the topics of the workshop. Length will not on its own be a reason for not accepting a submission, but all submissions will be evaluated in part for completeness.

Submission Instructions

Submission information will be provided here when available.

All submissions will be single-blind peer-reviewed. Authors of accepted papers will receive an invitation for an oral presentation at the workshop. At least one author of each accepted paper must register as an author for the workshop. Accepted papers will be published as part of the IEEE BigData proceedings.

Generated content disclosure

Authors shall disclose any use of artificial intelligence (AI)-generated content in the acknowledgments section of their paper. The AI system used and the specific sections of the paper that contain AI-generated content shall be identified, accompanied by a brief explanation regarding the level at which the AI system was used to generate the content. Authors are fully responsible for all content they submit. For more information, please consult https://conferences.ieeeauthorcenter.ieee.org/author-ethics/guidelines-and-policies/submission-policies/.

Important Dates

Event	Date
Submission deadline	October 1, 2026
Notification	November 4, 2026
Camera-ready	November 25, 2026
Workshop	TBD during December 14–17, 2026

Contact

For questions about submissions, contact the workshop organizers at extreme-data-curation-organizers@googlegroups.com.