International Workshop on Polymer Data

Workshop Purpose

A fundamental prerequisite for achieving genuine innovation in AI-driven science is the availability of large-scale datasets. However, compared with advanced AI domains such as natural language processing and computer vision, data resources in polymer science remain severely limited. Openly accessible polymer data is also much smaller than other material domains, such as inorganic crystals and small molecules. This deficiency arises not only from technical factors—most notably the substantial cost associated with data generation—but also from cultural factors that have hindered momentum toward building shared foundational data infrastructure.

This invitation-only workshop brings together leading domain experts and data-platform architects from academia, industry, and government agencies. We believe that the viable path to overcoming the limitation of polymer data resources lies in co-creation that transcends organizational, disciplinary, and national boundaries. Participants will engage in discussions from multiple strategic perspectives, including the development of standardized schemas to enable future database integration and cross-referencing; the construction of highly generalizable foundational AI models trained on diverse and heterogeneous datasets, even when quantitatively limited; and the establishment of a sustainable framework for international collaboration.