Use Cases¶
End-to-end walkthroughs for representative scientific and data-readiness scenarios live in use_cases/. Each covers data acquisition, code registration, pipeline construction, and agent-driven execution against a real dataset.
| Use case | Domain | Summary |
|---|---|---|
| Microbial Isolates | Genomics — short-read QC and assembly with fastp + megahit |
Register short-read QC and assembly tools, ingest genomics best-practice knowledge, and build a reproducible isolate-processing pipeline against real sequencing reads. |
| Cryo-EM | Structural biology — EMPIAR-10017 β-galactosidase micrographs via CryoPPP | DSAgt-assisted curation of cryo-EM data from the EMPIAR public archive (EMPIAR-10017 β-galactosidase micrographs via CryoPPP) — register curation tools, ingest cryo-EM quality knowledge, and build a micrograph-preprocessing pipeline. |
| VASP / ISAAC | Materials science — DFT input/output handling with VASP | Convert VASP DFT input/output into an AI-ready ISAAC record — register the conversion tooling and build the pipeline against bundled NEB fixture data (no DFT run, no HPC). |
| AIDRIN Readiness Gate (Cryo-EM) | AI data readiness — aidrin quality metrics before/after cryo-EM curation |
Use AIDRIN as a readiness gate around a cryo-EM curation step — run the applicable data-quality and class-balance metrics before and after particle curation, with full provenance, to measure how much the pipeline improved AI-readiness. |
| AIDRIN Full Feature Tour | AI data readiness — all 15 aidrin metrics (quality, fairness, privacy) on UCI Adult |
Drive every AIDRIN metric through DSAgt on a single tabular dataset (UCI Adult) — all 15 metrics across data-quality, impact-on-AI, fairness-and-bias, and data-governance, each recorded with full provenance. |
Adding a use case
Drop a README.md with frontmatter (title, domain, summary) into a
use_cases/<name>/ folder — it is auto-added to this table, gets its own
page, and appears in the nav. Folders without frontmatter are left out
entirely. See
hooks/gen_use_cases.py.