Scientific Data Management

During my time within the Office of Data and Informatics at NIST, I have focused on working directly with other researchers to address data and workflow challenges through novel data management solutions. This work has involved both in‑depth technical proficiency as well as experience leading both project teams and federally‑funded working groups.

Selected highlights from my time at NIST include:

  • Designed, implemented, deployed, and maintained usnistgov/NexusLIMS – a laboratory information management system (LIMS) to automatically harvest, categorize, and display data from dozens of electron microscopes and associated spectrometers (backend and frontend dev using Python, Django, SQLite, MongoDB)
  • Published ETSpy – usnistgov/etspy – a HyperSpy extension package to facilitate electron tomographic data analysis (using Python, Jupyter, Sphinx)
  • Proposed, architected, and implemented an internal staff scheduling application to manage in‑person room utilization during the COVID‑19 pandemic featuring calendaring, approvals, notifications, etc. Used by over 800 employees during the return to hybrid work schedules. (using PostgreSQL, Shiny, PostgREST, Office 365 APIs, Python)
  • Identified and deployed an electronic lab notebook platform (ELN) for use by research staff at NIST (eLabFTW). Developed data models for microbial research workflows and an automated experiment metadata validation and export pipeline. (using LinkML, pydantic, Python, Web APIs)
  • Co‑chaired a working group of the Materials Research Data Alliance (MaRDA) focused on producing recommendations for the use of LIMS in materials research environments (results published in the MRS Bulletin)
  • Maintained and managed community for open‑source hyperspectral data analysis software – hyperspy/hyperspy (Python)
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