A practical, structured audit template to identify and prioritize documentation, data, protocol, and workflow gaps that undermine reproducibility and research quality.
Why a Reproducibility & Quality Audit matters — and how to get started. Reproducible research is not a nice-to-have; it is the groundwork of trustworthy results, efficient teams, and reliable progress. Many organizations discover that the problem isn’t one dramatic failure but dozens of small gaps: missing protocol...
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How to run a Reproducibility & Quality Audit and turn findings into action. Running an audit is as much about focus and follow-up as it is about the questions you ask. This practical guide shows how to scope an audit, use the walk‑through form, score findings, and convert them into prioritized work that fits your...
Quick wins: 12 small changes that improve reproducibility now. These items are intentionally short, low-effort, and high-value. Pick one or two to implement within a week and measure the improvement. Centralize protocol storage. Put canonical protocol versions in one shared location and link to them from project...
Measuring reproducibility: KPIs and a simple dashboard. Measurement keeps improvement accountable. These KPIs are pragmatic and observable for most research teams. Use them to track progress across audits and to report improvements to stakeholders. Recommended KPIs. Audit risk score (median) — Median overall...
A practical remediation workbook that converts reproducibility audit findings into prioritized, time-bound actions with owners, verification checks, and a sample 90-day plan. Includes prioritization guidance, reusable remediation card template, verification checklist, communication and handoff practices, and options for making the plan an interactive, trackable tool.
An actionable audit checklist to verify code, data, environment, and documentation for reproducible analyses — capture evidence, assign owners, set priorities, and record remediation actions.
An interactive experiment registry form and minimal schema to capture consistent experiment metadata, ownership, protocols, datasets, analysis scripts, outcomes, and reproducibility evidence.
A step-by-step, prioritized playbook that turns reproducibility audit findings into concrete remediation actions: creating snapshots (data + code + env), improving documentation and SOPs, versioning artifacts, scheduling verification runs, and tracking KPIs until fixes are verified.
A concise, actionable checklist covering documentation, data, code, protocols, environment capture, and validation steps to improve reproducibility.
A practical, facilitator-ready playbook to convert failed or inconclusive experiments into reliable learning. Includes pre-retrospective data collection, a timed retrospective agenda, a step-by-step facilitation script, evidence-capture checklist, root-cause prompts (5 Whys and fishbone options), a SMART action-assignment template, and an experiment redesign checklist that helps teams close learning loops and improve reproducibility.