The advent of materials informatics (MI) with emerging global trends in digitalization, artificial intelligence, and automation has led to promising opportunities for transforming traditional scientific research workflows. However, new MI efforts rely critically on the establishment, management, and accessibility of high-quality thermophysical and chemical data, either by mining existing databases, labelling historical data in archives, or generating sufficient data sets as prerequisites to the creation of predictive machine learning models. For ambitious MI-driven projects, amassing systematic data can be a time-intensive and prohibitively costly endeavor in spaces where data is uncurated or scarce. Here, we describe a MI initiative that started in the 3M Corporate Research Laboratories (CRL), highlighting how we strategically applied MI tools and data-driven methodologies for industrial materials research and product development workflows. Robust web applications and cloud infrastructure were developed to structure, standardize, and aggregate materials data for specific CRL projects. This integrated approach leverages the diverse skills and deep technical expertise of subject-matter experts at 3M to build the foundations for MI through systematic data management in materials research and, ultimately, to advance core technology platforms with innovative, customer-driven product solutions. Key elements that have contributed to the ongoing implementation of this highly versatile MI program, as well as challenges encountered, are presented as lessons learned for the broader MI and cheminformatics communities.
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