What kind of formal or non-written rules/requirements does our project need to match and follow so we can say that our project is open science?

Is it only about research data which should be accessible to all?

What if the project doesn't make sense and it's publishing correlation data of the number of pirates with global temperature? Does it still match the criteria of 'open science' project?

  • 3
    I would say code/analysis pipelines as well as data must be open ...
    – Ben Bolker
    Commented Aug 4, 2015 at 18:03
  • 3
    If there is a complete documentation, code and data, so anyone with a basic knowledge in the field can reproduce the results (and least statistically), they this will be an open science.
    – user3905
    Commented Aug 4, 2015 at 18:07
  • If you think that this thread should be migrated to Academia or another SE site because the OpenScience beta is closing, please edit the list of questions shortlisted for the migration here. Commented Aug 20, 2015 at 22:30

5 Answers 5


To answer the first question:

I asked a similar question on twitter a while back and got a range of responses. Those are summarized in a storify. To paraphrase that summary ...

  • open access to data
  • open access to code
  • open access to publications
  • open source
  • work must be reproducible
  • needs to be web enabled

The last bit, and I think this is an important component, is that open science is not binary. It occurs along a gradient.

As for you second question, I would use reproducibility as a guide. The minimum data that needs to be accessible is that which allows for an anlalysis/project to be reproduced. Following the gradient theme, you could open up more than this, but that it isn't necessarily required.

  • 1
    Is Twitter really the best source for this kind of thing?
    – HDE 226868
    Commented Aug 4, 2015 at 18:13
  • 1
    Given Twitter's centrality in communication for many in the open science community, I think it is a reasonable place to go for a first approximation.
    – jhollist
    Commented Aug 4, 2015 at 18:18
  • 2
    Seconding that the overriding consideration here should be reproducability - and this should be the guide as to (for example) which code needs to be released.
    – Flyto
    Commented Aug 4, 2015 at 20:21
  • 1
    You should define "reproducibility" here. What exactly has to be reproducible? And what is the criterion for whether an output is reproducible or not? Is there a gray area between reproducible and irreproducible?
    – Thomas
    Commented Aug 6, 2015 at 16:26
  • What about making the work public before publication? E.g. blogging, pre-prints, uploading (meta)data ahead, etc. Does that have a role in open science?
    – bsmith89
    Commented Aug 7, 2015 at 21:40

On his site opencontent.org, Dave Wiley maintains a document describing what "open" means with respect to open content. Admittedly, this site and Wiley's work focuses on education and OER (open educational resources), but he (and others) have put a lot of work and thought into this and I think the points he makes here are relevant to open science.

Here, "open content" is described as works licensed to enable users free access to:

  1. retain (store, own, control)
  2. reuse
  3. revise
  4. remix (aggregate, mashup)
  5. redistribute

Replicability and reproducibility are crucial to science, and I think these "5R activities" describe a necessary and sufficient set of conditions enabling a scientist to replicate and build on the work of another.

Of course, the extent to which others can reuse, revise, and remix your research depends on a lot of practical factors. You may have licensed your incomprehensible Matlab research scripts using a permissive open license, but if nobody can decipher them, their "revise"-ability and "remix"-ability are limited. On the other hand, writing production-quality research software takes time and training that many academic researchers frankly don't have.

So I think at a minimum, open science projects must be licensed in such a way as to facilitate these 5R activities. Ideally, research software, data, and other scientific outputs would be also break down practical and technical barriers to be easily consumable by others, but exactly what is reasonable for a particular researcher in a particular context is hard to say.


The Panton Principles are a good guide - the reported research and everything it relies on (data, code/methods, analysis software, publication) should be made open and put in the public domain.

I don't know that it has to be reproduced, but it should be possible for someone to try to reproduce!


A specific example of formal criteria is the Badges to Acknowledge Open Practices Project.

At the moment there are 3 main badges:

Badges: Open Data | Open Materials | Preregistered

They are awarded by participating journals to articles that adhere to that particular open practice. For example, if an article shares its data on a public third party repository then the editor can award it an Open Data Badge that usually appears in the article header.

There are currently few participating journals but one example is Psychological Science.

Another project you might be interested in is The Peer Reviewers' Openness Initiative (previously 'The Agenda for Open Research'). Signatories of the initiative are proposing to withdraw peer reviewer services if articles do not adhere to a series of open practices, such as sharing data and code.


Open Source Research (OSR) adopts the following basic criteria/rules/laws for open science:

  1. All data are open and all ideas are shared.
  2. Anyone can take part at any level.
  3. There will be no patents.
  4. Suggestions are the best form of criticism.
  5. Public discussion is much more valuable than private email.
  6. An open project is bigger than, and is not owned by, any given lab.

in can be summed as:

All data and ideas are freely shared between participants and anyone may take part.

Initially they were written as part of Open Source Drug Discovery for Malaria. They're also available at Wikiversity.

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