A New Kind of Town Hall

Open source software is everywhere. It powers scientific discovery, financial systems, climate models, and the AI tools reshaping every industry. But ask most people who built those tools whether they can tell you how many people depend on their work, and you’ll often get a shrug.

That’s what the Best of Open Source Software (b.o.s.s.) town hall series wants to address. Launched by NumFOCUS in early 2026, b.o.s.s. is a new quarterly education series led by partners and community members. It gives NumFOCUS Sponsored and Affiliated Projects a high-visibility platform to showcase what they’ve built and learn from their community.

The challenge isn’t technical. It’s structural. As James Bednar, Senior Director of Professional Services at Anaconda, put it during the Q&A session, commercial software companies have customers and direct relationships with those customers. Open source tools are just picked up—through word of mouth, through imperfect discovery, sometimes for the wrong reasons. There’s no feedback loop, no direct channel, no easy way to tell your story to the people who most need to hear it.

“Our goal with b.o.s.s. programming is to offer our community a high-visibility platform to learn how to communicate value, impact, and find collaborators for your projects.”
— MK (Mariel Kanene), Project Resource Mobilization Lead, NumFOCUS

The theme of the first session was centered on marketing as a soft power for open source scientific computing projects—the intentional, strategic work of communicating impact, finding collaborators, and building the kind of visibility that sustains a project over time.

Marketing Starts With Strategy

Marc Ostertag, NumFOCUS Senior Director of Development, put it plainly: marketing requires both a strategy and the right tools to execute it. Most projects, he observed, reach for the tools first and miss the strategy.

“Marketing is, above all, a strategy—one that needs to be carefully thought through and evaluated before turning to the tools that will bring visibility, energy, and momentum to your campaign.”
— Marc Ostertag, Senior Director of Development, NumFOCUS

The fact is that projects grow when they master both strategy and the right tools, and right now, some projects may struggle to juggle that with everything else they need to do to keep their work moving forward, leading to things getting lost in an oversaturated market.

What NumFOCUS Offers Projects Today

In this market, how do you get started with marketing your OSS project? Kelby Lorenz, NumFOCUS Digital Marketing Specialist, walked through the existing marketing infrastructure for Sponsored and Affiliated projects.

Monthly project updates: Every month, NumFOCUS compiles project news—bug fixes, releases, announcements, anything worth sharing—into a blog post, social media posts for each project, and an email newsletter. The reach: over 800 blog subscribers, nearly 40,000 followers across LinkedIn, X, and Bluesky, and approximately 27,000 email subscribers.

“It’s a really great opportunity to share what you’re doing in a very low-effort way. You just send over the notes, and we take care of the rest.”
— Kelby Lorenz, Digital Marketing Specialist, NumFOCUS

Social media management resources: NumFOCUS has a detailed slide deck available to all of their Sponsored and Affiliated projects covering target audience research, content calendar setup, analytics interpretation, and visual creation.

One-on-one support from the NumFOCUS digital team: Whether projects are starting from scratch on social media, trying to understand which platforms make sense for their audience, or struggling to interpret what their analytics are telling them, the NumFOCUS team is available to help—from platform selection and content strategy to sitting down and walking through the data together.

Coming Soon: Submit Your Project to the NumFOCUS YouTube Channel

NumFOCUS operates two YouTube channels—one dedicated to PyData conference content, and a second NumFOCUS channel—with a combined subscriber base of over 170,000 and approximately 10,000 views per week.

Projects can now submit short demos and visually engaging content for a regular feature on the NumFOCUS YouTube channel. More details on the submission process and requirements will be available soon. For NumFOCUS projects looking to get started promoting their work, this is an easy way to reach a large audience.

You Can’t Tell a Story You Can’t Measure

Anaconda.org hosts open source packages that power enormous amounts of scientific and data work, but right now, maintainers have limited visibility into that usage. Download counts are flat numbers. There’s little insight into downstream dependencies, geographic reach, or adoption patterns across versions. Without that data, making a case for continued investment—to funders, to employers, to potential contributors—is needlessly hard.

Daina Bouquin, Senior Developer Relations Engineer at Anaconda, has spent her career working on exactly this problem. Before Anaconda, she worked in academia with astronomers and astrophysicists, and she routinely collaborated with groups like Force11 to develop machine-actionable citation principles that enable software contributions to be tracked and credited the same way journal articles are.

“If you can’t answer how many people actually depend on what you built, you’re going to have a hard time making a case for yourself.”
— Daina Bouquin, Senior Developer Relations Engineer, Anaconda

Watch Anaconda's Lightning Talk

What Anaconda Is Building with Community Input

Daina walked through several initiatives currently in development—all still being shaped with community input, which she emphasized is deliberate.

Dedicated analytics dashboard: A package and channel maintainer view offering real-time monitoring of what’s happening with a package—architecture breakdown, Python version mix, top-dependent packages, and more. This is explicitly intended to be co-built with the community, and its shape will be informed by what maintainers actually find actionable.

Trusted publishing via OIDC: This top-requested roadmap item will improve publishing pathways for maintainers. Trusted publishing makes it easier to publish packages while maintaining security.

Open API for Anaconda.org: This would make package data accessible in a much more flexible way, allowing maintainers to build custom dashboards, integrate stats into READMEs, and power their own reporting.

AI integrations: As more developers begin their research with AI agents and LLMs, Anaconda is exploring how to surface packages when developers need them, making discoverability part of the infrastructure.

“This data is meaningfully yours. We want to make sure it’s useful so that you can take your package data, build dashboards, generate shareable content, and integrate stats with your README and other reporting requirements.”
— Daina Bouquin, Anaconda

Anaconda’s commitment: if something they build doesn’t work for you, they want to know. Developer and maintainer feedback is sent directly to the product team.

Lightning Talks from the NumFOCUS Community

The best proof that this work matters is seeing it in practice. Two NumFOCUS-supported projects presented at the inaugural b.o.s.s. town hall—one from Jiangsu, China, and one from Valencia, Spain—demonstrating the community’s global reach and the range of problems it tackles.

SciML

Erik, a researcher within the SciML (Scientific Machine Learning) ecosystem, presented work funded in part by NumFOCUS. His focus: GPU-accelerated boundary value problem (BVP) solvers—a technically demanding but high-impact extension of the SciML project’s existing GPU-accelerated ODE and SDE solver capabilities.

“With the support of NumFOCUS, we can not only complete key technical milestones, but also ensure that these advancements are accessible, well-documented, and sustainable within the open source ecosystem.”
— Erik, SciML / Samuel Organization

The downstream impact of this work is wide-ranging. Improved BVP solvers open the door to large-scale parameter estimation, symbolic-numerical code generation through ModelingToolkit.jl, and tighter integration with modeling ecosystems like OpenModelica and domain-specific toolchains in the engineering and sciences. The work also advances differentiable programming and optimal control workflows that bridge traditional differential equation solving with modern optimization pipelines.

Support from NumFOCUS makes it possible to take this work from a research prototype to a production-ready tool that’s truly usable and maintainable by the broader community.

Watch Now

Blosc + Caterva2 + LLMs

Francesc Alted, lead developer of Blosc and CEO of Iron Array, presented alongside his colleague Pau to demo Caterva2—an open-source project built on top of Blosc2 that tackles a fundamental physics problem in data science: at the scale of hundreds of terabytes, you simply cannot download your data to a local machine to process it. The data has to stay where it is, and the compute has to come to it.

Caterva2 makes this practical. It’s an open-source server that supports Blosc2 and HDF5 formats for large dataset storage, with computation, visualization, and filtering capabilities exposed through a REST API, a Python API, and a web interface. The web interface supports running Jupyter notebooks against remotely stored data fully in-browser, with no installation required.

“The user doesn’t need to install anything. Everything is available right in the browser.”
— Francesc Alted, Lead Developer, Blosc / CEO, Iron Array

The headline feature of the demo was an LLM-powered agent that lets users query datasets using plain natural language. Rather than writing code, a user can ask the agent things like ‘give me the statistical information about this dataset’ or ‘give me a 10×10×10 slice of this array,’ and the agent automatically selects and chains the right underlying Caterva2 tools. Francesc and Pau also walked through more advanced options, including exposing the agent’s internal reasoning so researchers can see exactly which operations are being performed.

On the roadmap: expanded natural language querying across tables and visualizations, prebuilt LLM skills for common scientific computational tasks, and—notably—a Model Context Protocol (MCP) server designed to feed optimal compression parameters across different LLM services. That last item threads directly into the broader ecosystem trend Anaconda raised in the previous section: making open source tools findable and usable at the point where AI agents are doing the work.

Watch Now

Lessons from the Q&A

The sessions above covered strategy, infrastructure, and cutting-edge demos, but the Q&A brought it back to a practical question: once you know you need to tell your story better, what do you actually do?

Daina pointed to the AstroPy and SunPy communities as a concrete example. Rather than hoping users would acknowledge the software in papers, they specified exactly what that acknowledgment should look like: ‘AstroPy Collaboration,’ placed in a particular section of a paper, in a particular format. They made it easy, specific, and trackable so tools like Google Scholar could automatically detect and count those citations.

The lesson for open source projects outside academia: if you want to be found and credited, don’t just ask people to acknowledge you. Give them the exact language and format, and make it as easy as possible to do it right.

“It wasn’t just storytelling to say, ‘Look how impactful we are.’ They went and said: if you want to credit the AstroPy project, say ‘AstroPy Collaboration’—and this is where we want you to put it in your paper.”
— Daina Bouquin, Anaconda

A practical starting point: CITATION.cff files

These machine-actionable citation files live in a project’s repository and specify exactly how the software should be cited—in a format that Google Scholar, Zenodo, and others can automatically read and process. Low effort to add; meaningful increase in the likelihood your work gets captured and attributed.

The equity dimension is worth naming directly: the ability to self-advocate isn’t equally distributed. Projects with strong leadership or institutional backing are better positioned to do this work. Many aren’t. That’s part of what makes infrastructure investments like Anaconda’s analytics initiative meaningful beyond convenience—when usage data is surfaced automatically, you don’t have to already know how to advocate for yourself to start telling a data-driven story.

Getting Involved

The gap between the impact open source projects have and the visibility they receive is not inevitable. It’s a solvable problem, and it’s being actively worked on.

NumFOCUS is building the marketing infrastructure and platform access to help projects amplify their work. Anaconda is building the data infrastructure to give maintainers the metrics to back up their stories. The projects presented at b.o.s.s. are doing the hard technical work and, increasingly, finding the language to talk about why it matters.

What all of this requires from projects themselves is the willingness to invest in the strategy side—to think about who their audience is, what story they’re telling, and how to make it easy for the people who depend on their work to say so. The tools are there. The audience is there. The support is there.

b.o.s.s. will continue quarterly, with new partners, new project demos, and new themes. If you’re a NumFOCUS project and want to participate as a presenter, a future spotlight, or simply as an engaged community member, we’d love to hear from you.

What’s Coming Next: