The Federal NanoEHS Data Landscape: Machine-learning and Large Language Methods to Improve Data Accessibility, Interoperability and Semantic Queries

 Pranav Singh, NNCO's VSFS intern mentored by Dr. Holly Mortensen (US EPA), presents the work he has been doing using EPA’s automated ontology mapping tool (OntoSearcher) to create interoperable file formats for several agency nanomaterial databases, and in applying large language models to assist in query creation and visualize federated query results.

Impact/Purpose

This work follows data and tools published in Mortensen HM, Beach B, Slaughter W et al. Translating nanoEHS data using EPA NaKnowBase and the resource description framework [version 1; peer review: 2 approved]. F1000Research 2024, 13:169 (https://doi.org/10.12688/f1000research.141056.1 NNI VFSF intern, Pranav Singh (mentor: Holly Mortensen) is working to improve the semi automated semantic mapping of nanoEHS data initiated in Mortensen et al as part of the Federal nanoEHS data consortium, and improve search and query capabilities for the semantic graphs created for each federal partner using Large Language Models and machine learning methods. 

Citation

Singh, P. AND H. Mortensen. The Federal NanoEHS Data Landscape: Machine-learning and Large Language Methods to Improve Data Accessibility, Interoperability and Semantic Queries. ICCVAM Public Forum (details at https://ntp.niehs.nih.gov/go/iccvamforum-2025), virtual, NC, July 21, 2025.