Key Points

Big Data


Workflows


  • A workflow is not extra work — it is how you make your research repeatable, scalable, and understandable.
  • If you can’t clearly describe your workflow (inputs, steps, outputs), you can’t reliably trust or reproduce your results.
  • Workflows save time in the long run by turning ad‑hoc processes into reusable, adaptable systems.

Reproducible Research


  • Reproducible research makes your work easier to understand, reuse, and extend.
  • Small, well-documented steps can significantly improve reproducibility and FAIRness.
  • Clear documentation is more valuable than detailed but incomplete records.
  • FAIR practices are about clarity and accessibility, not complex infrastructure.
  • Improving reproducibility is incremental: consistency matters more than perfection.

Interlude


  • Your facilitators will be here for all of the HWSA
  • Feel free to discuss further questions from our workshops
  • We are also available to chat about software / hardware questions you might have that relate to your research

Workflows and Reproducibility in Practice


  • Don’t let the perfect be the enemy of done.
  • Your future self is your most important collaborator.