[Vp-reproduce-subgroup] "Models are not consistently licensed"
Alexander Kulesza
alexander.kulesza at novadiscovery.com
Sun Jan 2 05:47:54 PST 2022
Dear all,
in regard of licensing I agree a bit with the reviewer that "requiring" CC0
to make a model public, will not foster publishing them in a reproducible
and repeatable way. The reason for absence of a "a one for all" license is
the different purposes, aims, and dependencies of a model. For example, if
the model is calibrated against data that is licensed with a CC-BY-SA-ND-NC
license, the model cannot be published under CC0.(?)
I suggest to state that
"
We therefore recommend that models and their associated data should be
published under a Creative Commons license which provide a simple,
standardized way to give permission to share and use creative work. For
maximizing reproducibility and integration, we suggest that the most
permissive licence possible should be chosen. In that regard the CC0
license would be the ideal choice (effectively waiving interests of the
creator in their works and therefore emulating the public domain in
jurisdictions where this is necessary.
"
I have NOT yet incorporated this suggestion to the manuscript, as I am not
leading the revision of that section. I really feel that being more
flexible on the licensing issue is important. I hope that you can agree to
my suggestion.
Kind regards
Alexander
On Sat, 1 Jan 2022 at 13:25, William Waites <wwaites at ieee.org> wrote:
> I agree with Sheriff’s sentiment but find the voice confusing.
> For example, most of the authors of *this* paper were not
> involved in “our reproducibility study”. It is also unclear if
> “we decided to continue with CC0” refers to BioModels or the
> present paper.
>
> I would prefer an explanation from first principles with
> BioModels as a good example. Something like the text below.
>
> (Aside #1. I removed the word “sophisticated” from Sheriff’s
> text. Feel free to put it back. I’ve observed the pattern,
> particularly around the pandemic, of pointing to complicated
> models as better evidence of something than can be got with
> simpler models. As though being complicated is a virtue. This
> is more akin to the original meaning of the word sophisticated
> which is a scientific anti-pattern. That’s not what Sheriff
> meant, but I’d like to avoid using that word at all, especially
> in a context that suggests it’s something good.)
>
> (Aside #2. For software, I personally prefer copyleft licenses
> and not usually public domain. In the academic sphere this
> *should* not pose a problem because of the norm that says you
> have to make your code available otherwise the paper that
> crucially relies on it isn’t worth the bits it’s encoded in.
> However it’s not at all obvious that it’s enough to rely on
> good practice for this since there’s plenty of bad practice
> out there. There is some progress with journals and funders
> enforcing better practice. This is just an alternative mechanism
> to the legal jiu-jitsu of copyleft.)
>
> Best wishes for the new year,
> -w
>
>
>
> —
>
> There are practical and moral reasons why models should be
> freely available. To ensure a high standard of scientific
> work, it is important to be able to reproduce and verify
> results. This requires software and data for models to be
> freely available and that the barriers to running them
> be minimal. To facilitate scientific progress, it is
> ideal to be able to build upon the work of others. This
> requires not only that software and data are available but
> that reuse and modification is allowed. Finally, there is
> a moral argument that work produced using public funds
> should be publicly available. This concept is well embedded
> in some segments of the community, for example in the case
> of federally funded work in the United States, but we hold
> it as a general principle.
>
> Models are a combination of software and data. The legal
> treatment of these differs across jurisdictions with software
> generally subject to copyright law and data subject to database
> rights. This is not universal. The common denominator is the
> maximally permissive concept of “public domain” which exists
> in some jurisdictions where no restrictions are placed on use,
> reuse, modification and creation of derivative works, and,
> crucially, combination of multiple (possibly derivative) works
> into a new whole. However, the public domain does not exist
> as a concept in all jurisdictions and in others it is not
> possible to simply place a work in it. To solve this problem,
> the CC0 license (formulated with respect to copyright law
> and database rights) emulates the public domain in jurisdictions
> where this is necessary. We therefore recommend that models,
> and their associated data are published under CC0 terms.
>
> An example of this approach is the BioModels database. BioModels provides
> model curation and annotation service, where the models’
> reproducibility is assessed and annotated with controlled
> vocabularies. BioModels aims to make models discoverable. The
> BioModels database offers search engines to search and locate
> models and model components (
> https://www.ebi.ac.uk/biomodels/parameterSearch). The BioModels
> reproducibility study ( Tiwari et al. 2021,
> https://doi.org/10.15252/msb.20209982), strongly recommends
> that authors make their models public, but more specifically
> through public repositories such as BioModels (
> https://www.ebi.ac.uk/biomodels).
> We also recommend that authors submit model codes, parameter sets,
> and simulation conditions needed to reproduce simulation
> studies. Overall this will greatly facilitate model reuse.
>
> We further recommend that models published in this way should
> not require proprietary software or resources in order to be
> used. Requiring such resources greatly hampers reproducibility,
> verification and reuse. To achieve these goals, such
> dependencies typically require rewriting the models ab initio
> with the original model code serving the much less useful
> (but still not worthless) function of documentation. While
> there are benefits to reformulating existing models — a
> reimplementation might be more efficient or clearer and more
> elegant — a hard requirement to do so in all cases simply
> leads to wasted resources.
>
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--
Alexander Kulesza
Team leader
Modeling & simulation / Biomodeling
alexander.kulesza at novadiscovery.com
+33 7 82 92 44 62
nova
DISCOVERY
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