Committee Members:

Prof. Surya Kalidindi, Advisor, CSE/ME/MSE

Prof. David McDowell, ME/MSE

Prof. Josh Kacher, MSE

Prof. Sham Navathe, CoC

Zach Trautt, Ph.D., National Institute of Standards and Technology (NIST)

"A Knowledge Graph for Materials Informatics"

Abstract:

There is an exponential explosion in the amount of materials data being generated due to the advancements of measurement equipment, high-throughput testing protocols, simulations, and data generation initiatives. However, the existence of more data is not directly correlated to a better understanding of material systems, as it generally does not meet the findable, accessible, interoperable, and reusable (FAIR) principles. The heterogeneous nature of the data, disparate sources, and inconsistent use of schemas (data models) has made the generation of FAIR and navigable materials datasets elusive. Therefore, analyzing multiple sources of data and extracting insights from multiple projects requires a great deal of conceptual background and preprocessing, which slows research or prevents analysis altogether.

This work develops the materials informatics knowledge graph to integrate a diverse and heterogeneous set of datasets. It incorporates a flexible ontological schema which captures the important relationships needed to represent challenging and complex materials concepts such as process-structure-property linkages. The schema is validated by demonstrating the ability to incorporate a hierarchy of material, process, and data classes needed to represent the diverse datasets, mining the datasets using a knowledge representation framework, and gaining insights about the datasets using only an understanding of the unifying schema and graph learning tools.