Tag Archives: Open Science

Update the Panton Principles please

There is a big contradiction between the text of The Panton Principles and the List of the Recommended Conformant Licenses. It appears that it is intentional, I’ll explain in a moment why I write this.

This contradiction is very bad for the Open Science movement. That is why, please, update your principles.

Here is the evidence.

1. The second of the Panton Principles is:

“2. Many widely recognized licenses are not intended for, and are not appropriate for, data or collections of data. A variety of waivers and licenses that are designed for and appropriate for the treatment of data are described [here](http://opendefinition.org/licenses#Data). Creative Commons licenses (apart from CCZero), GFDL, GPL, BSD, etc are NOT appropriate for data and their use is STRONGLY discouraged.

*Use a recognized waiver or license that is appropriate for data.* ”

As you can see, the authors clearly state that “Creative Commons licenses (apart from CCZero) … are NOT appropriate for data and their use is STRONGLY discouraged.”

2. However, if you look at the List of Recommended Licenses, surprise:

Creative Commons Attribution Share-Alike 4.0 (CC-BY-SA-4.0) is recommended.

3. The CC-BY-SA-4.0 is important because it has a very clear anti-DRM part:

“You may not offer or impose any additional or different terms or conditions on, or apply any Effective Technological Measures to, the Licensed Material if doing so restricts exercise of the Licensed Rights by any recipient of the Licensed Material.” [source CC 4.0 licence: in Section 2/Scope/a. Licence grant/5]

4. The anti-DRM is not a “must” in the Open Definition 2.1. Indeed, the Open Definition clearly uses “must” in some places and “may” in another places.  See

“2.2.6 Technical Restriction Prohibition

The license may require that distributions of the work remain free of any technical measures that would restrict the exercise of otherwise allowed rights. ”

5. I asked why is this here. Rufus Pollock, one of the authors of The Panton Principles and of the Open Definition 2.1, answered:

“Hi that’s quite simple: that’s about allowing licenses which have anti-DRM clauses. This is one of the few restrictions that an open license can have.”

My reply:

“Thanks Rufus Pollock but to me this looks like allowing as well any DRM clauses. Why don’t include a statement as clear as the one I quoted?”


“Marius: erm how do you read it that way? “The license may prohibit distribution of the work in a manner where technical measures impose restrictions on the exercise of otherwise allowed rights.”

That’s pretty clear: it allows licenses to prohibit DRM stuff – not to allow it. “[Open] Licenses may prohibit …. technical measures …”


“Marius: so are you saying your unhappy because the Definition fails to require that all “open licenses” explicitly prohibit DRM? That would seem a bit of a strong thing to require – its one thing to allow people to do that but its another to require it in every license. Remember the Definition is not a license but a set of principles (a standard if you like) that open works (data, content etc) and open licenses for data and content must conform to.”

I gather from this exchange that indeed the anti-DRM is not one of the main concerns!

6. So, until now, what do we have? Principles and definitions which aim to regulate what Open Data means which avoid to take an anti-DRM stance. In the same time they strongly discourage the use of an anti-DRM license like CC-BY-4.0. However, on a page which is not as visible they recommend, among others, CC-BY-4.0.

There is one thing to say: “you may use anti-DRM licenses for Open Data”. It means almost nothing, it’s up to you, not important for them. They write that all CC licenses excepting CCZero are bad! Notice that CC0 does not have anything anti-DRM.

Conclusion. This ambiguity has to be settled by the authors. Or not, is up to them. For me this is a strong signal that we witness one more attempt to tweak a well intended  movement for cloudy purposes.

The Open Definition 2.1. ends with:

Richard Stallman was the first to push the ideals of software freedom which we continue.

Don’t say, really? Maybe is the moment for a less ambiguous Free Science.

The price of publishing with GitHub, Figshare, G+, etc

Three years ago I posted The price of publishing with arXiv. If you look at my arXiv articles then you’ll notice that I barely posted on arXiv.org since then. Instead I went into territory which is even less recognized as serious by a big part of academia. I used:

The effects of this choice are put in front of my homepage, so go there to read them. (Besides, it is a good exercise to remember how to click on links and use them, that lost art from the age when internet was free.)

In this post I want to explain what is the price I paid for these choices and what I think now about them.

First, it is a very stressful way of living. I am not joking, as you know stress comes from realizing that there are many choices and one has to choose. Random reward from the social media is addictive. The discovery that there is a way to get out from the situation which keeps us locked into the legacy publishing system (validation). The realization that the problem is not technical but social. A much more cynical view of the undercurrents of the social life of researchers.

The feeling that I can really change the world with my research. The worries that some possible changes might be very dangerous.

The debt I owe concerning the scarcity of my explanations. The effort to show only the aspects I think are relevant, putting aside those who are not. (Btw, if you look at my About page then you’ll read “This blog contains ideas from the future”. It is true because I already pruned the 99% of the paths leading nowhere interesting.)

The desire to go much deeper, the desire to explain once again what and why, to people who seem either lacking long term attention capability or having shallow pet theories.

Is like fishing for Moby Dick.

How to use the chemlambda collection of simulations

The chemlambda_casting folder (1GB) of simulations is now available on Figshare [1].

How to use the chemlambda collection of simulations? Here’s an example. The synthesis from a tape video [2] is reproduced here with a cheap animated gif. The movie records the simulation file 3_tape_long_5346.html which is available for download at [1].

That simple.

If you want to run it in your computer then all you have to do is to download 3_tape_long_5346.html from [1], download from the same place d3.min.js and jquery.min.js (which are there for your convenience). Put the js libs in the same folder as the html file. Open the html file with a browser, strongly recommend Safari or Chrome (not Firefox which blocks with these d3.js animations, for reasons related to d3). In case your computer has problems with the simulation (I used a macbook pro with safari) then slow it like this: edit the html file (with any editor) and look for the line starting with

return 3000 + (4*(step+(Math.random()*

and replace the “4” by “150”, it should be enough.

Here is a longer explanation. The best would be to read carefully the README [4].
“Advanced”: If you want to make another simulation for the same molecule then follow the steps.

1. The molecule used is 3_tape_long_5346.mol which is available at the library of chemlambda molecules [3].

2. So download the content of the gh-pages branch of the chemlambda repository at github [4] as explained in that link.

3. then follow the steps explained there and you’ll get a shiny new 3_tape_long_5346.html which of course may be different in details than the initial one (it depends on the script used, if you use the random rewrites scripts then of course the order of rewrites may be different).

[1] The Chemlambda collection of simulations

[2] Synthesis from a tape

[3] The library of chemlambda molecules

[4] Chemlambda repository (readme) https://github.com/chorasimilarity/chemlambda-gui/blob/gh-pages/dynamic/README.md

The chemlambda collection is a social hack, here’s why


People from data deprived places turn to available sources for scientific information. They have the impression that Social Media may be useful for this. Reality is that it is not, by design.

But we can socially hack the Social Media for the benefit of Open Science.

Social Media is not fit for Open Science by design. They are Big Data gatherers, therefore they are interested not in the content per se, but in the metadata. The huge quantity of metadata they suck from the users tells them about the instantaneous interests and social links or preferences. That is why cat pics are everywhere: the awww moment is data poor but metadata rich.

Open Science has as aim to share scientific data and rigorous validation means. For free! Therefore Open Science is data rich. It is also, by design, metadata poor, because at least if a piece of research is not yet popular, there is not much interaction (useful for example to advertisers or to tech companies or govenrnments) to be encoded in

The public impression is that science is hard and many times boring. There are however many people interested in science, like for example smart kids or creative people living in data deprived places. There are so many people with access to the Social Media so that, in principle, even the most seemingly boring science project may gather the attentions of tens of thousands of them. If well done!

Such science projects may never see the light of the media attention because classical media works with big numbers and very low level content. Classical media has still to adapt to the new realities of the Net. One of them is that the Net people are in such a great number that there is no need to adapt a message for a majority of people which is not, generically, interested in science.

Likewise, Social Media is by design driven by big numbers (of metadata, this time). They couldn’t care less about the content provided that it generates big data exhaust (Zuboff, Big other: surveillance capitalism and the prospects of an information civilization).

They can be tricked!

This was the purpose of the chemlambda collection: beautiful animations, data rich content hidden behind for those interested. My previous attempts to use classical channels for Open Science gave only very limited results. Indeed, the same is true for a smart kid or a creative person from Africa.

If you are not born in the right place, studied at the right university and made the right friends then your ideas will not spread through the classical channels, unless your
ideas are useful to a privileged team. You, smart kid or creative person from Africa, will never advance your ideas to the world unless they are useful first not to you, but to privileged people from far away places. If this happens, the best you can expect is to be an useful servant for them.

So, with these ideas and experiences, I tried to socially hack the Big Data gatherers. I presented short animations (under 10s) obtained from real scientific simulations. I chose them among those which are visually appealing. Each of them can be reproduced and researched by anybody interested via a GitHub repository.

It worked. The Algorithmic Gods from Google decided to make chemlambda a featured collection. I had more than 50 000 followers and more than 50 millions views of these scientific, original simulations.

To compare, another collection, dedicated to censorship on social media, had no views!

I shall make, acording to my access to data, which is limited, an analysis of people who saw the collection.

It seems to me that there were far more women that men. Probably the algorithms used the prior that women, stupid as they are, are more interested in pictures than text. Great, let’s hack this stupid prior and turn it into a chance to help Women access to science 🙂

There were far more people from Asia and Africa than from the West. Because, of course, they are stupid and don’t speak the language (English), but they can look at the pictures. Great, let’s turn this snobbery into an advantage, because they are the main public which could benefit from Open Science.
The amazing (for me) popularity of this experiment showed that there is something more to dig in this direction!
Science can be made interesting and remain rigorous too.

Science and art are not as different as they look, in particular for this project the visual arts.

And the chemlambda project is very interesting, of course, because it a take on life at molecular level done by a mathematician. The biologists need this, not only mathematical tools, but also mathematical minds. Biologists, as the Social Media companies, sit on heaps of Big Data.

Finally, there is the following question I’d like to ask.
Scientific data is, in bits, a tiny proportion of the Big Data gathered everyday. Is tiny, ridiculously tiny.

Question: where to put it freely, so that it stays free and is treated properly, I mean as visible and easy to access as a cat pic? Would it be so hard to dedicate something like 1/10 000 of the servers used for Big Data in order to keep Open Science alive? In order to not let it rot along with older cat pics?

Open peer review is something others should do, Open science is something you could do

This post follows Peer review is not independent validation, where it is argued that independent validation is one of the pillars of the scientific method. Peer review is only a part of the editorial process. Of course that peer review is better than nothing, but it is only a social form of validation, much less rigorous than what the scientific method asks.

If the author follows the path of Open science, then the reader has the means to perform an independent validation. This is great news, here is why.

It is much easier to do Open science than to change the legacy publishing system.

Many interesting alternatives to the legacy publishing have been proposed already. There is green OA, there is gold OA (gold is for $), there is arXiv.org. There are many other versions, but the main problem is that research articles are not considered really serious unless they are peer reviewed. Legacy publishing provides this, it is actually the only service they provide. People are used to review for established journals and any alternative publishing system has to be able to compete with that.

So, if you want to make an OA platform, it’s not serious unless you find a way to make other people to peer review the articles. This is hard!

People are slowly understanding that peer review is not what we should aim for. We are so used with the idea that peer review is that great thing which is part of the scientific method. It is not! Independent validation is the thing, peer review is an old, unscientific way (very useful, but not useful enough to allow research finding to pass the validation filter).

The alternative, which is Open science, is that the authors of research findings make open all the data, procedures, programs, etc, everything they have. In this way, any other group of researchers, anybody else willing to try can validate those research findings.

The comparison is striking. The reviewers of the legacy publishing system don’t have magical powers, they just read the article, they browse the data provided by the very limited article format and they make an opinion about the credibility of the research findings. In the legacy system, the reviewer does not have the means to validate the article.

In conclusion, it is much simpler to do Open science than to invent a way to convince people to review your legacy articles. It is enough to make open your data, your programs, etc. It is something that you, the author can do.

You don’t have to wait for the others to do a review for you. Release your data, that’s all.

Peer review is not independent validation

People tend to associate peer review with science. As an example, even today there are still many scientists who believe that an arXiv.org article is not a true article, unless it has been peer reviewed. They can’t trust the article, without reading it first, unless it passed the peer review, as a part of the publishing process.

Just because a researcher puts a latex file in the arXiv.org (I continue with the example), it does not mean that the content of the file has been independently validated, as the scientific method demands.

The part which slips from the attention is that peer review is not independent validation.

Which means that a peer reviewed article is not necessarily one which passes the scientific method filter.

This simple observation is, to me, the key for understanding why so many research results communicated in peer reviewed articles can not be reproduced, or validated, independently. The scale of this peer reviewed article rot is amazing. And well known!

Peer review is a part of the publishing process. By itself, it is only a social validation. Here is why: the reviewers don’t try to validate the results from the article because they don’t have the means to do it in the first place. They do have access only to a story told by the authors. All the reviewers can do is to read the article and to express an opinion about it’s credibility, based on the reviewers experience, competence (and biases).

From the point of view of legacy publishers, peer review makes sense. It is the equivalent of the criteria used by a journalist in order to decide to publish something or not. Not more!

That is why it is very important for science to pass from peer review to validation. This is possible only in an Open Science frame. Once more (in this Open(x) fight) the medical science editors lead. From “Journal Editors To Researchers: Show Everyone Your Clinical Data” by Harlan Krumholz, a quote:

“[…] last Wednesday, the editors of the leading medical journals around the world made a proposal that could change medical science forever. They said that researchers would have to publicly share the data gathered in their clinical studies as a condition of publishing the results in the journals. This idea is now out for public comment.

As it stands now, medical scientists can publish their findings without ever making available the data upon which their conclusions were based.

Only some of the top journals, such as The BMJ, have tried to make data sharing a condition of publication. But authors who didn’t want to comply could just go elsewhere.”

This is much more than simply saying “peer review is bad” (because is not, only that it is not a part of the scientific method, it is a part of the habits of publishers). It is a right step towards Open Science. I repeat here my opinion about OS, in the shortest way I can:

There are 2 parts involved in a research communication:   A (author, creator, the one which has something to disseminate) and R (reader). The legacy publishing process introduces a   B (reviewer).  A puts something in a public place, B expresses a public opinion about this and R uses B’s opinion as a proxy for the value of A’s thing, in order to decide if A’s thing is worthy of R’s attention or not.  Open Access is about the direct interaction of A with R, Open Peer-Review is about transparent interaction of A with B, as seen by R and Validation (as I see it) is improving the format of A’s communication so that R could make a better decision than the social one of counting on B’s opinion.

That’s it! The reader is king and the author should provide everything to the reader, for the reader to be able to independently validate the work. This is the scientific method at work.