2026-07-11 11:09:18 -04:00
2026-07-11 11:09:18 -04:00

LabDataStorageEvaluation

Build a complete, reproducible pipeline that:

Defines a simulated tribology laboratory (Sandia Pt-Au LDRD context) with real instruments and a realistic test workflow. Generates ~150 MB of physically plausible measurement data in CSV (the canonical raw format). Converts the CSV corpus into 4 target storage formats: JSON-LD, SQLite (optimized), PostgreSQL (indexed + partitioned), RDF TripleStore. Benchmarks 7 laboratory-standard retrieval scenarios (Q1Q7) against all 5 formats, measuring wall time, peak RAM, CPU utilization, disk I/O, and disk footprint. Extrapolates measured results to 600 GB and beyond (0.6 / 1.2 / 6 TB) using complexity-aware scaling models. Produces summary tables and charts that clearly rank storage formats for laboratory use (analysis, reporting, search/filter, archiving, inter-lab exchange).

Description
Reproducible pipeline that benchmarks storage formats (CSV, JSON-LD, SQLite, PostgreSQL, RDF) for laboratory measurement data on a simulated tribology lab, then extrapolates to TB scale and ranks them per use case.
Readme 1.4 MiB
Languages
Python 98.6%
Mermaid 1.4%