<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Docker on DANDI</title><link>https://about.dandiarchive.org/tags/docker/</link><description>Recent content in Docker on DANDI</description><generator>Hugo</generator><language>en</language><lastBuildDate>Fri, 21 Aug 2026 10:12:52 -0400</lastBuildDate><atom:link href="https://about.dandiarchive.org/tags/docker/index.xml" rel="self" type="application/rss+xml"/><item><title>DANDI Notebooks: Persistent, Executable Companions to Neurophysiology Data</title><link>https://about.dandiarchive.org/blog/2026/08/20/dandi-notebooks/</link><pubDate>Thu, 20 Aug 2026 00:00:00 +0000</pubDate><guid>https://about.dandiarchive.org/blog/2026/08/20/dandi-notebooks/</guid><description>&lt;p>A dataset on DANDI is most useful when it comes with code that shows how to read it and
what can be done with it. For several years we have collected such notebooks at
&lt;a href="https://notebooks.dandiarchive.org">notebooks.dandiarchive.org&lt;/a>: walkthroughs of
individual dandisets, tutorials from workshops, and in a growing number of cases,
notebooks that reproduce specific figures from the paper a dataset was published with.&lt;/p>
&lt;p>The difficulty with notebooks has always been keeping them runnable. A notebook that
worked when it was written depends on a particular set of package versions, and those
versions drift. Within a year or two, a reader who tries to run it often finds that a
dependency has changed its API, a default has moved, or a package no longer installs at
all. The code is still there, but the ability to execute it has quietly evaporated.&lt;/p></description></item></channel></rss>