RUI: Framework: Data - An Open Semantic Data Framework for Data-Driven Discovery

The project makes contributions to the ease of annotating, sharing, and searching heterogeneous data sets. It focuses upon undergraduate training, emphasizing data science capabilities applied to a range of science problems.

The project enables aggregation, search, and inference with heterogeneous datasets using a structured framework allowing data and metadata to be linked by encoding the framework as a JavaScript Object Notation (JSON) for Linked Data (JSON-LD) document. The approach builds on existing developments such as the Scientific Data (SciData) framework and associated ontology that has been developed by the PI, and Shape Constraint Language (SHACL) shapes to provide efficient searching, browsing, and visualization of data. The result extends existing approaches to link data and metadata and make data easily discoverable. The activity emphasizes Research in Undergraduate Institutions (RUI), training more than 30 undergraduates, graduate students and a post-doctoral student in the application of data science techniques to an array of science problems.

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.