Tag Archives: figshare

What’s new around Open Access and Open Science? [updated]

In the last year I was not very much interested into Open Access and Open Science. There are several reasons, I shall explain them. But before: what’s new?

My reasons were that:

  • I’m a supporter of OA, but not under the banner of gold OA. You know that I have a very bad impression about the whole BOAI thing, which introduced the false distinction between gold which is publication and green which is archival. They succeeded to delay the adoption of what researchers need (i.e. basically older than BOAI inventions, like arXiv) and the recognition that the whole academic publication system is working actively against the researchers interests. Academic managers are the first to be blamed about this, because they don’t have the excuse that they work for a private entity which has to make money no matter the price. Publishers are greedy, OK, but who gives them the money?
  • Practically, for the working researcher, we can now publish in any place, no matter how close or anachronically managed, because we can find anything on Sci-Hub, if we want. So there is no reason to fight for more OA than this. Except for those who make money from gold OA…
  • I was very wrong with my efforts and attempts to use corporate social media for scientific communication.
  • Bu still, I believe strongly in the superiority of validation over peer-review. Open Science is the future.

I was also interested in the implications for OA and OS of the new EU Copyright Directive. I expressed my concern that again it seems that nobody cares about the needs of researchers (as opposed to publishers and corporations in general) and I asked some questions which interest me and nobody else seems to ask: will the new EU Copyright Directive affect arXiv or Figshare?  The problem I see is related to automatic filters, or to real ways the researchers may use these repositories.  See for example here for a discussion.  In   Sept 2018 I filed requests for answers to arXiv and to Figshare. For me at least the answers will be very interesting and I hope them to be as bland as possible, in the sense that there is nothing to worry about.

So from my side, that’s about all, not much. I feel like except the gold OA money sucking there’s nothing new happening. Please tell me I’m very wrong and also what can I do with my research output, in 2019.

UPDATE: I submitted two days ago a comment at Julia Reda post Article 13 is back on – and it got worse, not better. About the implications for the research articles repositories, the big ones, I mean, the ones which are used millions of times by many researchers. I waited patiently, either for the appearance of the comment or for a reaction. Any reaction. For me this is a clear answer: pirates fight for the freedom of the corporation to share in its walled garden the product of a publisher. The rest is immaterial for them. They pirates not explorers.

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Chemlambda strings

I uploaded Chemlambda strings at Figshare.

“Chemlambda is an asynchronous graph rewrite automaton which uses a carefully selected family of graph rewrites of the kind encountered in Interaction Nets (IN). In this article is given a version of the graphs and rewrites which is more chemistry friendly. It is argued that real chemistry has enough place for accomodating chemlambda. The use of IN rewrite patterns in real chemistry, as templates of concrete chemical reactions, is an unexplored direction towards molecular computers. The simulations which validate chemlambda as a toy chemistry show that there is a big potential in this direction.”

The article is paired with the needs repository.  Look down the first page of the article for contact mail.

So what’s new with respect to chemlambda?

1. It is conservative. I said previously that it can be done, but here is the proof now.

2. It is open to vast generalization. I explained previously that there is not much lambda in chemlambda, as a proof see Turing machines, chemlambda style. Now it has the form (can be easily put into the form) of a permutation automaton. A permutation automaton is simply a program which takes as input a (maybe huge) permutation, probably with decorations on it (i.e. is a permutation of some big set, specified, not only a permutation of 1, …, N) and then it applies (randomly) pre-defined templates of permutations, whenever it detects a pattern into the permutation and moreover the random number generator produces an output of a certain difficulty 🙂

3. The paired needs repository contains already the main program. You can figure out how it functions, even if I have not added yet the functions libraries.

4. It is chemically friendly… Read the article.

 

Why chemlambda strings?

Because now we think about chemlambda molecules as being made by lists with sticky ends. These are the strings.

Each list (string) has two ends. So if there are N strings, then there are 2N nodes (ends of strings) and 3N edges. An edge is given by the fact that every list end appears in another list (interior).

Attention, it is not forbidden (actually happens, but not for graphs associated to lambda terms)  to also have loops. A loop is a list which you take and cut it’s start and end then you glue it back.

So if you take such a structure then you shall have a succ and pred functions, as well as a function gamma which taked a list end and gives you the list end place into another list.

For simplicity one can duplicate the nodes (so that now we have 4N nodes instead of 2N) and think about gamma as connecting the node which is an end of a list with the node which is an element of another (or the same) list.

Tell me if that rings a bell to you!

 

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
https://doi.org/10.6084/m9.figshare.4747390.v1

[2] Synthesis from a tape
https://plus.google.com/+MariusBuliga/posts/Kv5EUz4Mdyp

[3] The library of chemlambda molecules
https://github.com/chorasimilarity/chemlambda-gui/tree/gh-pages/dynamic/mol

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

Bitcoin, figshare, dropbox, open peer-review and hyperbolic discounting

Thinking out loud about the subject  of models of OA publication

  1. which are also open peer-review friendly,
  2. which work in the real world,
  3. which offer an advantage to the researchers using them,
  4. which have  small costs for the initiators.

PeerJ  is such an example, I want to understand why does it work and find a way to emulate it’s success, as quickly as possible.

You may wonder what difference is between 2 (works in real world) and  3(gives advantage to the user). If it gives an advantage to the user than it should work in real life, right? I don’t think so, because the behaviour of real people is far from being rational .

A hypothesis for achieving 2 is to exploit hyperbolic discounting.  I believe that one of the reasons PeerJ works is not only that it is cheaper than PLOS, but it also exploits this human behaviour.

It motivates the users to  review and to submit and it also finances the site (buys the cloud time, etc).

How much of the problem 4 can be solved by using the trickle of money which comes from exploiting hyperbolic discounting? Some experiments can be made.

What else? Let’s see, there is more which intrigues me:

  • the excellent figshare   of Mark Hahnel. It’s a  free repository,  which provides a DOI and collects some citation and use data.
  • there is a possibility to make blogs on dropbox. I have to understand well, but it seems that Scriptogr.am offers this service, which is an interesting thing in many ways. For example can one use a dropbox blog for sharing the articles, making it easy to collect reactions to them (as comments), in parallel with using figshare for getting a DOI for the article and for depositing versions of the article?
  • tools like git.macropus.org/twitter-viewer  for collecting twitter reactions to the articles (and possibly write other tools like this one)
  •  what is a review good for? a service which an open review could bring to the user is to connect the user with other people interested in the same thing. Thus, by collecting “social mentions” of the article, the author of the article might contact the interested people.
  • finally, and coming back to the money subject (and hyperbolic discounting), if you think, there is some resemblance in the references of an article and the block chains of bitcoin.  Could this be used?

I agree that these are very vague ideas, but it looks like there may be several sweet spots in this 4 dim space

  • (behavioral pricing , citing as  block chain)
  • (stable links like DOI , free repository)
  • (editor independent blog as open article)
  • (APIs for collecting social mentions as reviews)

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