Made a little poster to "sell" my free software

#opensource #openscience #reproducibility #automation #devops

"Is it really bad that only 50% of social science papers are reproducible?"

#SocialScience #reproducibility

https://blogs.lse.ac.uk/impactofsocialsciences/2026/05/18/is-it-really-bad-that-only-50-of-social-science-papers-are-reproducible/

Я хотел повторить Growing Neural CA за вечер. Ушёл месяц

Месяц назад я прочитал на Хабре статью про нейронные клеточные автоматы. Маленькие нейросети управляют клетками на сетке, клетки сами собираются в букву T или крест, и всё это обучается без учителя через что‑то вроде эволюции. Я подумал: круто, повторю за пару вечеров, посмотрю, как себя ведёт. Эта статья — о том, что было дальше. Спойлер: пара вечеров превратилась в месяц, я провёл 22 эксперимента, упёрся в потолок IoU 0.44 на простой букве T, и главное, чему научился — вообще не о нейросетях.

https://habr.com/ru/articles/1039694/

#neural_cellular_automata #neuroevolution #genetic_algorithms #neural_networks #claude_code #ml_engineering #research #pytorch #optuna #reproducibility

I am excited that my submission at JOSE (Journal of Open Science Education; https://jose.theoj.org/) has now been assigned an editor and a first reviewer! 🥳

🚨 We are still looking for a second reviewer: https://github.com/openjournals/jose-reviews/issues/347! 🚨

Would you like to review a tutorial on #Quarto for research (with a special focus on #humanities researchers with no programming background)? If so, sign up as a reviewer here: https://docs.google.com/forms/d/e/1FAIpQLScll1kTfY3tcdL23TIv1pWXKuXUcnwrXk_bIl5fkLQnGbqb7A/viewform! This is a really different (and I personally think better!) reviewing experience than traditional academic publishing: reviews follow a checklist principle and reviewers' contributions are public.

#OpenPeerReview #OER #OpenScience #reproducibility

Now available: written transcripts of our #OpenScience Bites #podcast episodes!

Prefer reading over listening, or want to quickly revisit key insights? You can now access full transcripts alongside the episodes.

🔗 https://www.rug.nl/research/openscience/podcast/ (via the drop-down menu)

#OpenScience #OpenEducation #PublicEngagement #Reproducibility #OpenResearch #Accessibility

Brilliant talk about #reproducibility by Emmanuel Boakye (AREN), during the latest #jrfrr2026.

A few key ideas and new and relevant aspects of his work as coordinator of an important network of research.

https://jrfrr-2026.sciencesconf.org/resource/page/id/3

„Have you developed some tools?“

Today I had the pleasure to meet interesting people from all around the #NFDI at the 4th NFDI Berlin-Brandenburg network meeting (https://events.hifis.net/event/3380/).
The event was about #provenance and #reproducibility and people represented diverse fields, spanning astronomy, medicine, chemistry and history.

I am always impressed by the wealth of practical solutions and tools, e.g., to document workflows and create metadata. I too enjoy coding, but sticking to the critical discussion is definitely a comfort zone in sociology…

PS thanks @wikimediaDE for hosting the event. Sitting on a wooden box and having some mate is the most Berlin thing I have done recently…

Version 3.0 of the tdda library and command-line tools has shipped:

python -m pip install -U tdda

or the usual variations.

Source: https://github.com/tdda/tdda.git
Docs: https://tdda.readthedocs.io/en/latest/
Book: https://book.tdda.info
Book 20% discount code: 26SMA1 at https://www.routledge.com/Test-Driven-Data-Analysis/Radcliffe/p/book/9781032897158

- Command-line tools for data validation (including constraint inference from training data)
- Reference testing (semantic testing of complex results)
- Automatic test-generation (any language)
- Format and utilities for working more safely with flat files (e.g. CSV files) with tdda.serial metadata and/or CSVW, Frictionless. Conversion utilities and format inference available.
- Utilities for unicode text (glyph counting and TK normal form, which goes beyond NFKC and NFKD)

3.0 includes
- Support for Pandas 3.0 (original, numpy_nullable, and pyarrow backends)
- Support for Polars in most areas
- Comprehensive parquet suport (replacing feather)
- Man pages for all commands
- Upgraded help docs for the whole library
- Associated book with the methodology
- 22 checklists for methodological support in areas unsuitable for code support.

#tdda #python #data #dataanalysis #ml #AI #rlang #datascience #testing #book #books #reproducibility #reproducibleresearch