A non-digital service example of working in the open

Matt has recently been blogging and speaking about "working in the open" in public service roles. Giles has written a lot about working in the open too, most recently collecting examples of teams who are doing open for different purposes, e.g. for remembering and thinking out loud. I've worked in the open on software and … Continue reading A non-digital service example of working in the open →

“AI-Ready Data” is the wrong framing

A paper was published this week by Stefaan Verhulst, Andrew Zahuranec and Hannah Chafetz called "Moving Toward the FAIR-R principles: Advancing AI-Ready Data". The paper sets out to do two things: Make the case that we are in a "Fourth Wave" of open data in which it is critical that data is made useful for … Continue reading “AI-Ready Data” is the wrong framing →

Falsehoods this programmer believed about energy meters

This is the second part to a post I published earlier this week in which I summarised some things I learned about working with half-hourly energy data. I'll be updating that shortly with a few extra details and clarifications. This post will be a summary of some things I've learned about energy meters and metering. … Continue reading Falsehoods this programmer believed about energy meters →

What does community-driven data governance look like?

Some idle thoughts for a Friday afternoon. I was just taking a look at Source.Plus a dataset of public domain images for training Foundation models. It's a project of Spawning.ai which is working to build "data governance for generative AI". I have some thoughts on the tools they're building, but that's not what I'm writing … Continue reading What does community-driven data governance look like? →

Comments on “A data for AI taxonomy”

Jack Hardinges and Elena Simperl recently published a taxonomy to describe the data relevant to AI models and systems. Their goal is to help to better distinguish between the different types of data relevant to developing, using and monitoring AI models and systems to help to better distinguish them and thereby add some nuance to … Continue reading Comments on “A data for AI taxonomy” →

Acceptable answers only

It can be hard to comment on a lot of tech news without coming across like Apu taking a bullet for a big tech platform. But a few aspects to the current debate around the new StackOverflow deal with OpenAI have irked me, as reported in TechCrunch and The Register and debated on Mastodon. So … Continue reading Acceptable answers only →

Design organisations not licences

There's an article in the Register this week about Bruce Perens' "Post-Open Zero Cost Licence". In brief, Perens is aiming to try to fix one problem that some people have with open source. Specifically finding a way for maintainers to get paid to continue to develop software. I'm being careful not to write "fix open … Continue reading Design organisations not licences →

A basis for better definitions of “open”

There's been a lot of discussion around what is means to be "open" recently. I think this has largely been driven by issues and concerns around the development and deployment of Large Language Models and claims for at least some of those models to be "open". What does it mean for an LL or other … Continue reading A basis for better definitions of “open” →

What datasets have been classified as Digital Public Goods?

Update: 2024-04-14, I've updated this post with some corrections. See below A couple of years ago I wrote a short series of posts looking at some different approaches for assessing data infrastructure. It includes this post on the Digital Public Goods standard and registry. Digital Public Goods are defined as: open-source software, open data, open … Continue reading What datasets have been classified as Digital Public Goods? →