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NOBEL PRIZE 2026

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NSFEXP PROG TO STIM COMP RES

Collaborative Research: Conference: CI PAOS: AI and FAIR Data Infrastructure for Advanced Materials and Manufacturing

Active
Institution
University of North Texas, TX
Principal investigator
Xinyi Xiao
Funding
$25K
Duration
2026–2027
Open portfolio

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Abstract

This project outlines a two-day workshop to be held in Norman, Oklahoma, focused on developing a community-wide roadmap for leveraging ontology-driven processes in advanced manufacturing (AM) to facilitate the integration and sharing of diverse, heterogeneous materials data - from synthesis and processing to characterization and performance. The central challenge is that materials data is often stored in disparate, isolated systems, creating "data silos" that hinder the ability to connect data with its critical contextual information, such as the material-process-structure-property relationship. This fragmentation is a fundamental bottleneck that slows the pace of innovation and discovery. The conference objective is to address this bottleneck by establishing a straightforward and systematic digitalization workflow that generates high-quality, semantically structured, and linked data adhering to the FAIR principles (Findable, Accessible, Interoperable, Reusable). This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

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EXP PROG TO STIM COMP RESDirectorate for Computer and Information Science and EngineeringNSF Public Access Initiativemanufacturingsilosmanufacturing projectdata criticalbottleneckadheringfair datafair

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