English Edition: How can we preserve data not for years, but for centuries, perhaps even millennia? Meet the Arctic World Archive (AWA), located on the Norwegian island of Spitzbergen part of the Svalbard archipelago. I met with the 2 co-founders, Rune Bjerkestrand and Katrina Leon to find out what's behind AWA and how data can be preserved for the longterm.

Links

• https://arcticworldarchive.org
• https://piql.com the PIQL way of storing data on film
• https://archiveprogram.github.com/faq/ GitHub is on AWA
• https://www.seedvault.no/ The Global Seed Vault on the same island
• https://unlocked.microsoft.com/sealed-in-glass/ Storing data in glass - Microsoft's Project Silica
  • https://www.nature.com/articles/s41586-025-10042-w
• https://en.wikipedia.org/wiki/Antikythera_mechanism the Antikythera mechanism - an object found in 1901 and seemingly an ancient (analog) computer

Get in touch

Thank you for listening! Merci de votre écoute! Vielen Dank für´s Zuhören!

Contact Details/ Coordonnées / Kontakt:

• Email mailto:peter@code4thought.org
• UK RSE Slack (ukrse.slack.com): @code4thought or @piddie
• Bluesky: https://bsky.app/profile/code4thought.bsky.social
• LinkedIn: https://www.linkedin.com/in/pweschmidt/ (personal Profile)
  • LinkedIn: https://www.linkedin.com/company/codeforthought/ (Code for Thought Profile)

This podcast is licensed under the Creative Commons Licence: https://creativecommons.org/licenses/by-sa/4.0/

English edition: As part of our ByteSized series, we are going through some of the (many) aspects of AI assisted coding with my guests Robert Chatley (Imperial College London, UK), Reece Walsh (Newcastle Uni., UK) and Faruk Diblen (eScience Centre, Amsterdam, NL).

Links:

• https://missing.csail.mit.edu/2026/agentic-coding/ A good run-through of agentic coding by MIT/USA
• https://martinfowler.com/bliki/AgenticProgramming.html Martin Fowler on agentic coding
• https://github.blog/ai-and-ml/generative-ai/agent-pull-requests-are-everywhere-heres-how-to-review-them/ here's GitHub's suggestions on how to deal with AI generated pull requests
• https://github.com/fdiblen/rseng-agent-skills Faruk Diblen's set of SKILLS for research software engineering
  • https://ai-declaration.org and here is Faruk's AI declaration website and tool
• https://modelcontextprotocol.io/docs/2026-07-28/getting-started/intro Model Context Protocol (MCP) by Anthropic
• https://rdr.ucl.ac.uk/articles/report/AI-Assisted_Software_Development_Policy_for_UCL_Advanced_Research_Computing/34070631?file=69660984 an example policy of how to deal with AI assisted coding tools - from UCL (University College London, UK)

ByteSized dRTP is part of the STEP-UP project and I would like to thank them for supporting this show.

Get in touch

Thank you for listening! Merci de votre écoute! Vielen Dank für´s Zuhören!

Contact Details/ Coordonnées / Kontakt:

• Email mailto:peter@code4thought.org
• UK RSE Slack (ukrse.slack.com): @code4thought or @piddie
• Bluesky: https://bsky.app/profile/code4thought.bsky.social
• LinkedIn: https://www.linkedin.com/in/pweschmidt/ (personal Profile)
  • LinkedIn: https://www.linkedin.com/company/codeforthought/ (Code for Thought Profile)

This podcast is licensed under the Creative Commons Licence: https://creativecommons.org/licenses/by-sa/4.0/

English Edition: scikit-learn is THE open source programming library for all things machine-learning. And since 2024, it is the core part of a company called :probabl.

What this means for the millions of users of scikit-learn and the many contributors is something we find out in this episode, where I talk to Marie Sacksick (skore), Arturo Amor (skolar) and Yann Lechelle (president and co-founder of :probabl.).

Links:

• https://www.probabl.ai Home page for :probabl.
• https://probabl.ai/skore Skore
  • https://github.com/probabl-ai/skore GitHub repo for skore
• https://scikit-learn.org/stable/about.html scikit-learn Python library
• https://blog.probabl.ai/intel-and-probabl-announce-collaboration-to-accelerate-scikit-learn-on-intel-hardware Collaboration between Intel and :probabl.
• https://scikit-learn-central.probabl.ai/#/catalog The central catalogue
  • https://github.com/probabl-ai/scikit-learn-central GitHub repo
• https://skolar.probabl.ai/ skolar, the certification programme
• https://inria.github.io/scikit-learn-mooc/ the INRIA MOOC for scikit-learn
• https://skrub-data.org/stable/ skrub (another project at :probabl.)
  • https://github.com/skrub-data/skrub

Get in touch

Thank you for listening! Merci de votre écoute! Vielen Dank für´s Zuhören!

Contact Details/ Coordonnées / Kontakt:

• Email mailto:peter@code4thought.org
• UK RSE Slack (ukrse.slack.com): @code4thought or @piddie
• Bluesky: https://bsky.app/profile/code4thought.bsky.social
• LinkedIn: https://www.linkedin.com/in/pweschmidt/ (personal Profile)
  • LinkedIn: https://www.linkedin.com/company/codeforthought/ (Code for Thought Profile)

This podcast is licensed under the Creative Commons Licence: https://creativecommons.org/licenses/by-sa/4.0/