A personal exploration of 4,900+ projects from the Linux Foundation Leaderboards
I started by sketching out ideas in my notebook...
It began with a simple question: What does the open source universe actually look like? Not the famous stars we all know—Linux, Kubernetes, VS Code—but the entire cosmos. The quiet projects maintained by three people. The hidden gems with incredible contributor diversity. The projects on the edge of burnout.
I'd been playing with the Linux Foundation's Leaderboards data for weeks, pulling down JSON files, sketching radial layouts on napkins during lunch breaks. The data surprised me because it told stories I didn't expect—stories about dedication, about community health, about what makes projects thrive or fade.
Efficiency: David vs. Goliath
We're calculating the Commits per Contributor ratio. A high ratio means a small, elite team (or highly automated bots) doing massive work. A low ratio means a large community where each person contributes a little—the "Bazaar" model.
Let's see who the "Special Forces" of open source are.
Each star represents a project. Brightness = commits per contributor. Size = total commits.
This is where things got interesting... I tried a bar chart first, but it felt too cold, too corporate. These aren't just numbers—they're communities of people shipping code. So I tried something different: what if each project was a star in a constellation?
The brightest stars are projects with incredible efficiency—small teams doing massive work. Look at CBT Tape at the center: just 3 contributors produced 1,138 commits each. That's dedication you can see.
Technically, I used D3's force simulation to let the stars find their natural positions, then added a radial gradient to give that soft glow effect. The colors shift from warm coral for the most efficient to cool teal for the larger community projects.
Finding "Hidden Gems" (Corporate Darlings)
One of my favorite discoveries came from a conversation about what makes a project truly "healthy." It's not just about commits—it's about who's contributing. A project with contributors from 40 different organizations is more resilient than one dominated by a single company.
We look for a high Organizational Diversity Ratio (Organizations / Contributors). A high ratio means many companies care about this, but few people write the code—often critical infrastructure libraries. A low ratio means a massive community project where contributor count dwarfs the org count.
Smaller projects with remarkably diverse contributor bases
I wanted the colors to feel like actual gemstones—so I chose an amethyst-to-emerald gradient. Each gem is sized by the number of contributing organizations, creating this beautiful cluster where you can immediately spot the most diverse communities.
ko stands out: 43 organizations contributing among just 68 people. That's a 63% diversity ratio! These are the projects that survive company pivots, layoffs, and changing priorities.
Burnout Risk: The "Red Alert" List
This one was hard to make. Not technically—emotionally. These are projects that were once thriving, now showing signs of contributor fatigue. The momentum score compares recent commits to historical activity. A steep negative slope means the fire is going out.
We looked at projects with high productivity scores that have seen a massive drop in momentum. If you depend on these, check on them.
I chose to visualize this as flames—bright at the base (historical productivity), fading toward the top (current state). It felt more honest than a clinical bar chart.
Historical productivity vs. current decline. Hover to see the stories.
The "Bus Factor" Watchlist: Small Teams, Massive Output
Every data story needs its celebrities. VS Code with 24,000+ contributors. Home Assistant with its passionate home automation community. Kubernetes powering the cloud-native revolution. But here's the twist: bigger isn't always better.
These projects have ≤50 contributors but generate massive commit volumes. Risk: High output from a small group means if one key person leaves, the project could stall. These are the "David" projects of the ecosystem—impressive, but fragile.
Look at the efficiency ratio—commits per contributor. The giants are actually quite inefficient by this metric! That's not a flaw—it's a feature. These projects are gateways. They turn newcomers into open source contributors. A small fix to VS Code might be someone's first PR ever.
Size = Contributors. Color intensity = Commits per contributor.
The "Triage Trap": Speed vs. Quality
Hypothesis: If a project responds instantly to issues, they probably fix them faster too, right?
Here's where my hypothesis broke. I assumed faster response times would correlate with higher resolution rates. I was wrong. The correlation? A mere 0.031. That's basically zero.
Spoiler Alert: Fast bots saying "Thanks for your issue!" doesn't mean the bug gets fixed.
This scatter plot shows why. There's no pattern. Fast responders can have low resolution. Slow projects can resolve everything. It's chaos—beautiful, organic, human chaos.
Each dot is a project. Hover to explore the outliers.
Growth vs. Maintenance
We compare Commit Activity against Codebase Size. High Commits + Low Size = High maintenance/refactoring. The team is working hard to keep things running or cleaning up technical debt. High Commits + High Size = Massive expansion.
Projects like Model Context Protocol (MCP) appeared here with huge activity but small size— classic signs of a new, rapidly iterating standard or heavy refactoring.
Codebase size vs commit activity. High maintenance projects in warm colors.
The "Churn" Trap: Motion vs. Progress
We calculated a Churn Ratio: Commits per Net Line of Code Change.
Projects with high churn are working hard but not necessarily growing.
Building this visualization taught me something I didn't expect. Open source isn't just code—it's a living ecosystem. Projects breathe, grow, sometimes struggle.
I started with questions about efficiency and ended up with a meditation on sustainability. The "best" projects aren't the biggest or fastest—they're the ones that keep burning, year after year, through changing trends and technologies.
Data doesn't lie, but it does whisper. You just have to listen closely.
If you've made it this far, you're my kind of person. This data is public—all from the Linux Foundation Leaderboards. I encourage you to explore, fork the code, find your own stories.
Maybe you'll find a hidden gem that needs contributors. Maybe you'll discover a project at risk of burnout and decide to help. The beauty of open source is that the next commit could be yours.