The 2nd Workshop on AI-Ready Data for Science Discovery

Date: November 12-15,2026 | Location: Shenyang, China

About the Workshop

Scientific discovery is entering a new era—powered by artificial intelligence (AI) and machine learning (ML). These technologies are enabling breakthroughs across disciplines such as biology, physics, chemistry, and materials science. However, one major bottleneck remains: the lack of high-quality, domain-specific datasets that are truly AI-ready.

The 2nd Workshop on AI-ready Data for Science Discovery (ADSD 2026) aims to address this critical challenge by building a vibrant, interdisciplinary community focused on the creation, curation, and benchmarking of scientific datasets. Hosted at ICDM 2026, ADSD will serve as a platform for researchers, practitioners, and data professionals to collaborate on shaping the future of scientific data mining.

Call for Papers

We welcome a wide array of submissions focused on AI-Ready Dataset for Science Discovery, encompassing topics such as theories, algorithms, applications, systems, and tools. These topics include but are not limited to:

Data Acquisition and Integration

  • Automated methods for constructing AI-ready data from experiments, simulations, and publications.
  • Methods for multimodal datasets integration, including text, images, tables, and numerical data.
  • Retrieval-augmented generation (RAG) and literature mining for scientific knowledge extraction and organization.
  • Scientific knowledge graphs, ontologies, and semantic data integration.

Data Curation, Quality Control, and Enrichment

  • Methods for dataset collection, annotation, documentation, and metadata generation.
  • Methods for synthetic data generation and data enrichment.
  • Methods for data consistency, completeness, provenance, and versioning.
  • Automated data refinement, outlier detection, and correction to improve dataset reliability.
  • Systems and tools for continuous dataset integrity monitoring, including expert-in-the-loop quality control.

Benchmarking and Evaluation Frameworks

  • Standardized benchmarks across scientific domains, such as biomedicine, materials science, and environmental modeling.
  • Methods for developing standardized metrics e.g. accuracy, robustness, scalability, and interpretability, tailored to domain-specific data characteristics.
  • Methods to evaluate data quality, AI-readiness, and suitability for downstream scientific tasks.
  • Methods to evaluate the data interpretability, robustness, and trustworthiness.
  • Open platforms for standardized benchmarking.
  • Benchmarks and protocols for evaluating end-to-end data pipelines and agentic workflows.

Applications in Scientific Research

  • Tools and agentic workflows for publication summary, knowledge discovery, and trend analysis.
  • AI-ready data and data-centric methods for scientific foundation models and domain-specific AI.
  • AI for scientific challenges like drug discovery, climate modeling, and material prediction, etc.
  • Closed-loop scientific workflows connecting data, AI models, simulations, experiments, and laboratory automation.

Submission Details

We invite the submission of regular research papers (4-10 pages), including the bibliography and any possible appendices. Submissions must be in PDF format, and formatted according to IEEE Conference Template. Submissions must be anonymized for review. Authors should remove author names, affiliations, acknowledgments, and other identifying information from the manuscript before submission. Submitted papers will be assessed based on their novelty, technical quality, potential impact, insightfulness, depth, clarity, and reproducibility. All the papers are required to be submitted via the ADSD Submission. (Important: please double-check that you are submitting to the correct workshop. If you previously submitted through an earlier link, please resubmit using the current ADSD Submission link.) By the unique ICDM tradition, all accepted workshop papers will be published in the dedicated ICDMW proceedings published by the IEEE Computer Society Press. For more questions about the workshop and submissions, please send email to pfwang@cnic.cn.

Important Dates

* All deadlines are at 11:59 pm in the Anywhere on Earth timezone

Keynote Presentations

Erik Cambria

Keynote 1

Erik Cambria, Full Professor

Nanyang Technological University

Xia Hu

Keynote 2

Xia Hu, Full Professor

Shanghai Artificial Intelligence Laboratory

Organizing Committee

Steering Co-Chairs

Yuanchun Zhou

Yuanchun Zhou

Chinese Academy of Sciences

Hui Xiong

Hui Xiong

The Hong Kong University of Science and Technology
(Guangzhou)

Xiansheng Hua

Xiansheng Hua

Tongji University

Program Co-Chairs

Pengfei Wang

Pengfei Wang

Chinese Academy of Sciences

Yanjie Fu

Yanjie Fu

Arizona State University

Pengyang Wang

Pengyang Wang

University of Macau

Jiaxu Cui

Jiaxu Cui

Jilin University

Yi Du

Yi Du

Chinese Academy of Sciences

Poster Chair

Ran Zhang

Ran Zhang

Zhongguancun Academy

Jiajia Wang

Jiajia Wang

Chinese Academy of Sciences

Web Co-Chairs

Junjie Ye

Junjie Ye

Chinese Academy of Sciences

Pengjiang Li

Pengjiang Li

Chinese Academy of Sciences

Ping Xu

Ping Xu

Chinese Academy of Sciences

Program

TBD

Program Committee

Contact

For inquiries, please contact us at pfwang@cnic.cn.

Data Sharing Supporters

SciDB CSTR