DataDocket

DataDocket is a web app (with optional desktop sync) that helps academic labs prepare “journal-ready” data and code packages without weeks of manual cleanup. It connects to common storage (OSF, GitHub, institutional S3, Google Drive) and guides researchers through a structured checklist: required files, metadata, README, license, environment capture, and dataset validation. An AI assistant drafts documentation, flags missing provenance, and suggests a minimal reproducible run command, but the user must approve every change. The app generates a clean archive plus a shareable landing page for reviewers and collaborators. Brutal truth: this won’t magically make bad science reproducible; it just reduces the boring, error-prone packaging work that delays submissions and causes desk rejections or reviewer complaints. Pricing targets labs and departments that repeatedly publish and need consistent outputs.