Dataset Papers
Submissions that introduce new datasets with comprehensive documentation, including data collection methods, preprocessing steps, statistical properties, and potential use cases.
AI/CORE Unranked
KDD D&B Track 2026
KDD 2026 Datasets and Benchmarks Track (Cycle 2)
The KDD 2026 Datasets and Benchmarks Track invites submissions of high-quality datasets and benchmarks to advance data mining and knowledge discovery research. It emphasizes the importance of well-documented, reusable, and impactful data resources that enable reproducible and scalable experimentation across the field.
Key deadlines
Verified September 9, 2026Abstract registration
February 2, 2026
AoE
Full paper
February 9, 2026
AoE
Conference timeline
Submission and decisions
Abstract registrationKey deadline
February 2, 2026 · AoE
Full paperKey deadline
February 9, 2026 · AoE
Paper fit
Contribution paths
A strong submission should clearly identify its contribution and evaluate it appropriately.
Benchmark Papers
Submissions that propose standardized benchmarks, evaluation protocols, or baselines for comparing algorithms on specific tasks using public or newly released data.
Research areas in scope
01
Datasets and Benchmarks
Novel datasets for data mining and machine learningBenchmark datasets for evaluating algorithmsData curation, annotation, and provenanceEthical and privacy-aware dataset creationBenchmarking frameworks and evaluation protocolsDataset usability, accessibility, and documentationDomain-specific datasets (e.g., healthcare, finance, climate, social media)Synthetic and simulated datasets for researchDataset versioning and long-term maintenanceCommunity-driven data initiatives and open data practices
Policies worth checking twice
- Submissions must be anonymized for double-blind review.
- Papers must not exceed 10 pages in ACM format (excluding references).
- Dual submission to other conferences or journals is not permitted during review.
- Authors must include a data availability statement and provide access to the dataset or benchmark via a public repository.
- Use of AI tools (e.g., LLMs) in generating content must be explicitly disclosed in the paper.
Official sources
Compiled from the official call for papers. The organizers’ pages remain authoritative.
Official conference siteFull ProgramWorkshopsTutorialsAuthor Presentation InstructionsResearch Track: Call for Papers
Last verified September 9, 2026