HESTO has successfully developed and deployed its new Automated Data Pipeline, a Python-based portfolio data parsing pipeline that will eliminate manual compilation of program metrics.
Shaun Hoffman, the HESTO summer intern who developed HESTO’s new Automated Data Pipeline, presented a poster on his work at the capstone poster session at NASA’s Wallops Flight Facility on July 28, 2026. The innovative tool he developed automatically extracts structured project data—including Technology Readiness Levels (TRLs), publications, and student metrics—directly from standard Principal Investigator (PI) PowerPoint reports and seamlessly loads it into a PostgreSQL database.
This new system recently processed all 48 active HESTO PI progress reports, utilizing validation checks to ensure data integrity. By replacing manual workflows with this scalable infrastructure, HESTO can now instantly generate complex “By the Numbers” metrics, significantly improving operational efficiency, data consistency, and overall confidence in Heliophysics technology portfolio reporting for the 2026 Annual Report and beyond.
NASA Artificial Intelligence (AI) Usage Disclosure: This article was created with assistance from AI (ChatGSFC) to summarize content from multiple sources. The resulting content has been reviewed and edited by the author team.