Curated collections

Research and data engineering

Ten practical templates for research and data engineering, covering inputs, deliverables and verification.

Contents and workflow

10 prompts
  1. A search strategy, screening table, evidence matrix and review outline.

  2. A paper summary, evidence chain, ranked comments and questions for authors.

  3. A literature matrix, gap candidates, feasibility assessment and validation plan.

  4. Normalized BibTeX, change notes, duplicate candidates and verification needs.

  5. An experiment design, evaluation matrix, run log template and risk checklist.

  6. A pipeline flow, data contracts, job dependencies and monitoring plan.

  7. Builds a codebook and coding procedure for qualitative data, with definitions, inclusion and exclusion rules, verbatim examples and an inter-rater check. Use before coding interviews or open text.

  8. Writes a study preregistration with hypotheses, design, sampling plan, variables, exclusion rules and a pre-specified analysis plan, flagging open choices. For OSF or AsPredicted users.

  9. Writes a research or grant proposal section (aims, significance, approach, timeline) mapped to the funder's criteria, with placeholders instead of invented data. Use for grant or thesis proposals.

  10. Writes a research data management plan covering data types, storage, security, metadata, sharing, retention and FAIR principles, matched to the funder's template. For grant applicants.