Microstructure Research Data Workshop at the South Big Data Innovation Hub

This workshop will bring together experts to advance public accessibility and interoperation standards for microstructural material science datasets, a category of data that has broad utility for many areas of materials science research. The workshop builds on previous workshops, which succeeded in identifying targeted gaps in microstructure descriptors commonly used in manufacturing to correlate synthesis and macroscopic properties that determine structural performance.

This workshop aims at identifying metadata needed to enable interoperability of distributed and federated microstructure data worldwide. The identification and adoption of these metadata standards will have widespread practical impacts in manufacturing, and be pursued through community engagement and consensus building. The results of this workshop will have the potential to dramatically advance manufacturing industries; efficiently developing synthesis strategies towards targeted structural performance, that could include resilience to extreme environments such as nuclear reactors and wind farms, to extreme weather conditions (coastal erosion), to fatigue in bridges, and to earthquake damage.

This workshop will focus on FAIR principles-oriented specifications for data management issues that were deemed crucial to the data science enterprise in previous gatherings, including: 1) metadata curation, 2) data ownership, provenance and sharing, 3) ontologies and schema, etc. The workshop will include a number of tracks: Data Science Education and Workforce, Manufacturing, Team Science, Smart Cities, Data Sharing, and Health Disparities.

In addition, the materials track will reach out to the other tracks and will: 1) connect with experts in resilient cities and ask what properties in cement, steel, etc. they are concerned with and incorporate those in the case studies, 2) connect with experts in Team Science for advice on how to efficiently execute the actionable items identified in the workshop, and 3) connect with experts in Workforce development for help in crafting a training program for data technicians in this realm (e.g. how much data science and how much materials science would a technician, researcher, etc. need to know to work in this space).

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.