Development of protocols for interoperable laboratory infrastructure, materials traceability, and FAIR materials data — Machine actionable data is a critical enabler of data-intensive science and engineering. Within materials science and engineering, process-structure-property-performance relationships present unique challenges, which have persisted for some time. The goals of our work in Materials Data Infrastructure is centered around the interoperability and reusability of materials data and metadata. The FAIR data principles are a set of aspirational goals which guide and inform our efforts.
We work closely with partners across NIST, including with the Office of Data and Informatics (ODI). We recently partnered with ODI to perform a landscape analysis to understand the challenges that impact research and development within the community. We found that challenges that have persisted over many years include the need for improved data interoperability, improved coordination, and increased access to Automated Experimental Technology.