Episode 12.4: How Are Open Practices Classified?

Last updated on 2026-09-08 | Edit this page

Overview

Questions

  • Open science covers a lot of ground: how do we make sense of it as a whole?
  • Do all open practices solve the same problem, or different ones?
  • Can a single study use more than one open practice at once?

Objectives

Learners will be able to:

  • List the major categories of open practice and what part of research each one opens up.
  • Match a research scenario to the open practice(s) it’s using.
  • Explain why most well-designed open studies combine several practices rather than relying on just one.

Why Classify Open Practices at All?

Imagine three researchers, each proud to say their work is “open.” One preregistered a hypothesis before collecting any data. Another uploaded their dataset to a public repository after publishing. A third made their paper free to read on a preprint server. All three are doing something real, but they’re opening up three completely different parts of the research process, and none of them, alone, gives you the full picture.

Sorting open practices into categories helps us:

see exactly what part of a study each practice makes visible, avoid assuming one open habit (like posting a preprint) covers everything, and combine practices deliberately, instead of by accident.

The Big Picture: A Map of Open Practices

Practice What It Opens Up Key Question It Answers Common Tools / Examples
Preregistration & Registered Reports The hypothesis and analysis plan Was this predicted in advance, or found after the fact?
OSF Registries, AsPredicted
Open Data The raw (usually de-identified) dataset Can someone else verify the numbers, or reuse them for a new question? Data repositories, institutional data archives
Open Materials & Code Instruments, protocols, and analysis scripts Can someone else rerun the exact same analysis? Code repositories, shared protocol documents
Open Access & Preprints The write-up itself Who is actually able to read this? Preprint servers, open-access journals
Open Educational Resources (OER) Teaching and training materials Who gets to learn from this, and can they adapt it? Open licences, shared course materials
Open Evaluation The review and quality-control process How was this judged, and by whom? Open or signed peer review, public reviewer reports
Team Science & Open Collaboration Who participates, and how credit is shared Who gets to contribute, and who gets recognised for it? Multi-site consortia, open contribution guidelines
Open Source Software The tools used to produce or manage the research Can the tools themselves be inspected, trusted, and improved? Publicly maintained code, open licences

Note: A single project can, and usually should, use several of these at once. A preregistered study with open data, open code, and a preprint isn’t unusual; it’s what a fully open project typically looks like.

A Closer Look at Each Category

  1. Preregistration & Registered: Reports Preregistration locks in a hypothesis and analysis plan before data collection. Registered Reports take it a step further: the study design itself is peer-reviewed and provisionally accepted for publication before the results exist, so the decision to publish never depends on how the results turned out.
  2. Open Data: Sharing the underlying dataset (properly documented and, where needed, de-identified) so others can check an analysis or reuse the data for a new question entirely.
  3. Open Materials & Code: Sharing the instruments (surveys, checklists, stimuli) and the exact analysis code, so the process of turning data into results is visible, not just the data itself.
  4. Open Access & Preprints: Making the written output freely available. A preprint is a version shared publicly before (or alongside) formal peer review; open access refers more broadly to removing paywalls, whether at a preprint stage or after formal publication.
  5. Open Educational Resources: Teaching materials (course notes, slide decks, textbooks, problem sets) released under licences that let others use, adapt, and redistribute them, rather than locking them behind a single classroom or institution.
  6. Open Evaluation: Making the peer review process itself visible: publishing reviewer reports, naming reviewers, or opening review up to public comment, instead of it happening entirely behind closed doors.
  7. Team Science & Open Collaboration: Structuring a project so that contribution and authorship are transparent, and so people who aren’t already part of an established network (students, researchers at smaller institutions, researchers in other countries) have a real way in.
  8. Open Source Software: Applying the same transparency principle to the tools researchers use: statistical packages, data-collection apps, lab equipment firmware. If the tool itself can be inspected, errors in it can be found and fixed by anyone, not just its original authors.

Test Your Knowledge!

Challenge

Challenge 1:

A team preregisters their hypothesis, then shares their anonymised dataset and analysis code on a public repository after publication. They still submit their paper to a journal that sits behind a paywall. Which practice from the table above have they not adopted?

Open access. They’ve adopted preregistration, open data, and open materials/code, but the paper itself is still not freely readable.

Challenge

Challenge 2:

True or False: Posting a paper on a preprint server automatically means the data behind it is also open.

False. A preprint opens up the write-up. It says nothing about whether the underlying data or code has been shared; those are separate practices.

Challenge

Challenge 3:

A university course releases its full syllabus, lecture slides, and assignments under a licence that allows other instructors to reuse and adapt them for their own classes. Which category does this best fit?

A. Open Data B. Open Educational Resources C. Open Evaluation D. Team Science

B. Open Educational Resources: this is specifically about teaching and training materials, distinct from research data or the review process.

Key Points
  • Open science is not one practice; it’s a set of distinct practices, each opening up a different part of the research process.
  • The major categories are: preregistration and Registered Reports, open data, open materials and code, open access and preprints, open educational resources, open evaluation, team science, and open source software.
  • A single study can combine several of these, and fully open projects usually do. Knowing which category a practice belongs to helps you spot what’s still missing, even when a study already looks “open” on the surface.

To-do: Add infographic.

Callout

💡 If someone tells you a study is “open,” a good follow-up question is: open in what way? The practices in this episode give you the vocabulary to ask that precisely.