It's a good time to test your #Guix profile if everything of #NumPy dependents works well

https://codeberg.org/guix/guix/issues/2977

#reproducibleresearch
#openscience

I'm happy to see code and data shared in a recent paper I read. And while I am very supportive of the authors' sharing code, the README is much better as a Markdown file than a PDF called "README.pdf" and the repository should ideally be archived with osf.io or better zenodo.org, which integrates seamlessly with GitHub w/ a DOI minted

Still, sharing this is a HUGE improvement over doing nothing. These are small ways that would improve the reproducibility and accessibility. #ReproducibleResearch

I'm happy to see code and data shared in a recent paper I read. And while I am very supportive of the authors' sharing code, the README is much better as a Markdown file than a PDF called "README.pdf" and the repository should ideally be archived with osf.io or better zenodo.org, which integrates seamlessly with GitHub w/ a DOI minted

Still, sharing this is a HUGE improvement over doing nothing. These are small ways that would improve the reproducibility and accessibility. #ReproducibleResearch

It's a good time to test your #Guix profile if everything of #NumPy dependents works well

https://codeberg.org/guix/guix/issues/2977

#reproducibleresearch
#openscience

@khinsen Thanks for your encouragement! Whereas I'd at first thought of Maslow's hierarchy as just a basic pattern to follow, I now think there may be a kind of 'isomorphism' here:

Physiologic Needs: any part of the analytic pipeline (from data to results) that isn't fully scripted à la #reproducibleresearch is effectively DEAD.

Safety Needs: scripts not under source control, unstructured analysis data sets (spreadsheets≈crime), and indeed all unnecessarily imperative pipeline elements (e.g., shell scripts instead of makefiles) create an UNSTABLE and UNSAFE environment for analytic work. (Where applicable, safeguarding sensitive data also belongs in this tier.)

Love & Belonging: code reviews, documentation [incl. tests, pace Dijkstra], preregistration, conference presentations, preprints, and peer review at all stages of the work; using and crediting community-contributed software.

Esteem: contributing reusable code, bug reports, bug fixes, etc. to a community of scientific software users; contributing thoroughly reproducible and criticizable analyses in peer review.

Self-Actualization: At this stage, the values achieved have to be one's own, I think. Examples might be achieving technical transcendence by doing the whole project in #CommonLisp, #Guix or (for me) ISO #Prolog 🧘, or formally proving correctness of algorithms. Another example would be that others extend & improve upon your work. Finally, #scicomm could be regarded as a true pinnacle.

Reading a paper this morning https://onlinelibrary.wiley.com/doi/10.1002/pds.4295 that follows Nosek & Errington (2017) https://elifesciences.org/articles/23383.pdf in muddling the distinction between #replicability as a broader scientific aim vs #reproducibility as captured in the narrow (purely 'computational') idea of #reproducibleresearch discussed e.g. in a #Guix context here https://guix.gnu.org/cookbook/en/html_node/Reproducible-Research.html.

This mistake is not uncommon, and leads (in this present paper, at least) to insufficient stress on computational reproducibility as a sine qua non of any higher-order quality attribute.

Implementing #reproducibility into daily #research practices hinges on pilots, projects, experiments and #collaborative efforts.
Do you have an idea on how to foster more #reproducibleResearch? Or are you already implementing a tool, exercise, standard procedure at your workplace?

You are invited to present your projects (or project ideas) during our poster and/or pitch session:

https://reproducibilitynetwork.nl/event/annual-symposium-2026/

Foto Credits: Robert Kroonen

@khinsen A well though-out Maslow's Hierarchy style graphic to convey this idea would be useful to me right now, putting [computational] reproducibility as a basic 'physiologic' need.
https://en.wikipedia.org/wiki/Maslow's_hierarchy_of_needs

I also see this 'feature grid' type of treatment https://co-analysis.github.io/coding-guide/workflow/rap/#code-maturity, which however does not underscore the #reproducibleresearch concept quite as I'd like.

Do you use any graphical summaries of this kind in your talks?

Reading a paper this morning https://onlinelibrary.wiley.com/doi/10.1002/pds.4295 that follows Nosek & Errington (2017) https://elifesciences.org/articles/23383.pdf in muddling the distinction between #replicability as a broader scientific aim vs #reproducibility as captured in the narrow (purely 'computational') idea of #reproducibleresearch discussed e.g. in a #Guix context here https://guix.gnu.org/cookbook/en/html_node/Reproducible-Research.html.

This mistake is not uncommon, and leads (in this present paper, at least) to insufficient stress on computational reproducibility as a sine qua non of any higher-order quality attribute.

I managed to find an easy solution to have reproducible environment using #Guix time-machine while still coding at the comfort of my own IDE.

I wrote a very short blog post about how to set it up in about 5 minutes along with example codes for R and etc.:

https://mehrad.ai/posts/20251106-reproducible-r-enviroment-using-guix/

This can be used for virtually any programming language and software stack.

#ReproducibleResearch #BlogPost #RStats

I managed to find an easy solution to have reproducible environment using #Guix time-machine while still coding at the comfort of my own IDE.

I wrote a very short blog post about how to set it up in about 5 minutes along with example codes for R and etc.:

https://mehrad.ai/posts/20251106-reproducible-r-enviroment-using-guix/

This can be used for virtually any programming language and software stack.

#ReproducibleResearch #BlogPost #RStats

Dear @zimoun , thank you for such a rich meeting and sharing your experience with #ReproducibleResearch and #guix for this #tem25 thesis . :)

#orgmode Babel (blocks of code calling anything integrated with the text and images) are great for #LiteraryProgramming and reprod. research.

Also, thank you for your mention of #ggplot2 that @ansate nailed too a little later. :)

Thanks also to @bzg too. 🙏

Re #PeerGovernance, I'd be delighted to share my experience with the guix community anytime.

Pleasure to meet you @ieure !
Yay, me too! We must talk at some time, I'm sure @ansate (thank you for the introduction) already told you about the #ReproducibleResearch thesis in #orgmode Iḿ doing right now... 😊 #tem25

Also, regarding #mechanical_keyboards; what are you using now? I enjoy everyday a Keyboardio M100 (https://shop.keyboard.io/products/model-100) with Linear A keycaps. Because if we don't look at them to type, at least in this way they are interesting. ;P

Upcoming talk by me on packing #ScryerProlog in #guix in Dusseldorf, November.

https://hsd-pbsa.de/veranstaltung/scryer-prolog-meetup-2025/

Emphases from me will cover the importance of #ReproducibleResearch and the gains from how Guix is well suited to not only providing precision for configuring but longevity of software stacks

#PackageManagement #prolog

Dear Emacsers.
I need some help w/ #elisp for my #LiterateProgramming + #ReproducibleResearch thesis (an exploration of meaningful abilities to operate outside academia).
I'd like it as completely self contained in -and sustained by- #Emacs (yes, I'm a geek and I'm proud) as possible and, while going forward, I've found my #elisp fu limiting.
Can anyone share some time to help me with this thesis and show the power of Emacs and #FreeSoftware? I'd gladly share my abilities back.
1e^3.Thxs