Who Will Keep Research Data Infrastructure Open and Running?

The scientific community must consider the longevity of open research infrastructure—why it might fail and how to prevent it.

Who Will Keep Research Data Infrastructure Open and Running?

The scientific community must consider the longevity of open research infrastructure—why it might fail and how to prevent it.

Doing Data Science on the Shoulders of Giants: The Value of Open Source Software for the Data Science Community

Open source software is ubiquitous throughout data science, and enables the work of nearly every data scientist in some way or another. Open source projects, however, are disproportionately maintained by a small number of individuals, some of whom are institutionally supported, but many of whom do this maintenance on a purely volunteer basis. The health of the data science ecosystem depends on the support of open source projects, on an individual and institutional level.

Doing Data Science on the Shoulders of Giants: The Value of Open Source Software for the Data Science Community · Issue 2.2, Spring 2020

Open source software is ubiquitous throughout data science, and enables the work of nearly every data scientist in some way or another. Open source projects, however, are disproportionately maintained by a small number of individuals, some of whom are institutionally supported, but many of whom do this maintenance on a purely volunteer basis. The health of the data science ecosystem depends on the support of open source projects, on an individual and institutional level.

Software Stewardship Lab

A non-profit research lab dedicated to ensuring the stability of the Open Source ecosystem we all rely on.

FOSS funding, co-operation, and the Digital Life Collective

Free open-source software (FOSS) is the bedrock of our digital world. This is a story about getting funding for FOSS engineering…

The Money In Open-Source Software | TechCrunch

It’s no secret that open-source technology -- once the province of radicals, hippies and granola eaters -- has gone mainstream. According to industry estimates, more than 180 young companies that give away their software raised roughly $3.2 billion in financing from 2011 to 2014. Despite the growing popularity of open-source software, though, many open-source companies are not financially healthy.

Prosperous Software Movement | Open Source Observer

Bringing sustainable funding to public goods by revenue-sharing towards dependencies

Open Source Endowment — World's First Endowment Fund for OSS

The Open Source Endowment provides truly sustainable funding for critical open source software through a community-driven endowment model.

Using X-Labs to Unleash AI-Driven Scientific Breakthroughs | IFP

How to adapt our science funding mechanisms to the unique infrastructure needs of large-scale AI projects

The $70B Open Source Software Paradox

It’s no news that over the last 10-15 years, particularly noticeable in the last 5 years, the enterprise software industry has gradually transformed from complex, expensive, closed-source (proprietary) software stacks to extensible/configurable,...

The New Deal for the Open Source Community

Building the Economic Layer to our Digital Infrastructure

Scientific Publishing: Enough is Enough

Why we're no longer funding journal publications

Scientific Publishing: Enough is Enough

Why we're no longer funding journal publications

This morning, I had the distinct honour of giving the opening keynote at #RSECon26: "Where does the rigour go? Research software and the future of trustworthy science" The core argument: AI is… | Arfon Smith

This morning, I had the distinct honour of giving the opening keynote at #RSECon26: "Where does the rigour go? Research software and the future of trustworthy science" The core argument: AI is making it dramatically cheaper to produce plausible scientific outputs, without necessarily making them cheaper to check. The scarce resources are shifting towards attention, judgment, and verification.  This is no doubt a disruptive time for research software engineers and research more generally. For Research Software Engineers specifically I think that creates some important new opportunities around: encoding domain judgment, building verification infrastructure, connecting agents to reality, and helping ensure that the emerging verification layer for science remains open. Thanks to everyone at RSECon26 for the thoughtful discussion, and especially to the many people whose work and ideas I that heavily influenced this talk. Link to slides in first comment

Linking the world's research to the code it runs on - OpenAlex blog

Research relies on software. Software written by scientists, for science, runs through the entire modern research stack: NumPy and SciPy, R and ggplot2, Jupyter, BLAST, ImageJ, AlphaFold. Yet in the scholarly record, that software is nearly invisible. Software is not usually cited formally in publications and is usually just mentioned in the text, which means […]