We’re proud to announce that Cosmik has been awarded a total of $1M in grant funding from Open Philanthropy and the Astera Institute! These generous 2-year grants will support the next chapter of Cosmik and our work at the intersection of next-generation collaborative knowledge tools, AI and science social media.

Specifically, the grants will support the development of Semble, a micro-knowledge sharing and discovery network for researchers on Bluesky/ATProto. Semble is rooted in the idea of the ensemble, where diverse contributions harmonize to create richer, more nuanced understanding than any single perspective could achieve alone.

Think of Are.na combined with Goodreads for research, re-imagined for decentralized social networks and user-owned data.

In March we wrote that the stars are aligning for new kinds of social media for researchers, and that opportunity has only grown stronger since.

Altmetric recently reported that Bluesky now regularly eclipses Twitter in terms of the amount of research being shared, despite being much smaller.

The importance of this trend cannot be overstated. But we also need more than just Twitter clones - to really flourish, we need new social media experiences tailored to the specific needs of researchers, as we discuss below. The size of Science Bluesky, coupled with its decentralization and the extensibility of its underlying ATProtocol, make Bluesky/ATProto fertile soil in which to grow an ecosystem of transformative new open science tools.

One area we are particularly excited to innovate in is the very concept of feeds. On one hand, we love the configurable feed ecosystem Bluesky is enabling, but at the same time, we, along with many others, feel we are running up against the limits of the medium. Feeds are inherently one-dimensional, ephemeral, and biased towards virality, creating attention dynamics where nuanced takes and valuable insights get buried beneath the posts with the most engagement. More importantly, they're optimized primarily for passive consumption rather than the active, non-linear and iterative process that knowledge building actually requires.

Collaborative tools for thought like Are.na point toward what becomes possible when we design for more flexible forms of knowledge creation and curation instead: researchers can make lists of related papers (like playlists on Spotify), share assessments (imagine Goodreads for science), and organize shared collections around research questions. These aren't just different interfaces - they're fundamentally different modes of eliciting knowledge and engaging with it that feeds are not designed to support.

The interoperable nature of ATProto makes this experimentation particularly exciting. Rather than choosing between feeds and curation tools, we can build systems where they reinforce each other. Semble can draw from the rich data already flowing through Bluesky while feeding structured knowledge back into the ecosystem to improve discovery and connections across apps.

Curation tools also offer a natural route to sustainability through paid subscriptions for premium features, as demonstrated by apps like Are.na and Sublime.

These new approaches to knowledge creation also connect directly to timely and important opportunities around nano/micropublishing. These concepts have of course been around for a while (we refer to "micro-knowledge" and nano/micropublishing interchangeably here), but they are recently seeing an exciting surge in interest. Progress in AI reasoning agents is driving the realization that models need access not just to “sanitized” papers, but also the messy thought processes by which we arrived at them. As Astera co-founder Seemay Chou recently wrote,

Scientists should probably be putting out shorter narratives, datasets, code, and models at a faster rate, with more visibility into their thinking, mistakes, and methods. In this age of the internet, almost anything could technically be a “publishable unit.” […] AI agents can’t learn scientific reasoning based on a journal record that presents only the glossy parts of the intellectual process, and not actual human reasoning. We are shooting ourselves in the foot.

That said, nanopublication is still quite niche and faces steep adoption challenges: there is still a critical lack of incentives for scientists to actually engage in such knowledge sharing. We think social media is a key piece of the incentive puzzle: as we’ve previously observed, researchers posting on social media are actually already nanopublishing but don’t know it yet. In other words, social media reveals the incentives that actually motivate researchers, for example engagement, reach, and meaningful interaction with peers. Framing also matters - as we discovered in our first experiment with the social media-to-nanopub autoposter, explicitly treating social media posts as "nanopublications" can actually deter researchers from participating (v1 in the diagram).

We think the key is finding the sweet spot combining the benefits of informal social sharing with the benefits of more formal publication, such as FAIR data. Or in other words, as depicted in the diagram below, the goal is to create apps that are delightful for both humans and machines (top right quadrant). Great UX is always a challenge, but there is a large space to explore here, full of promising yet-to-be-discovered tools. Importantly, ATProto provides an excellent testing ground for this experimentation, offering the technical flexibility to explore new experiences while building on the social networks researchers are already using.

Where does all this leave Science Twitter? When we started the project, “way back” in early 2024, Twitter was the center of gravity for science social media, and we had been focused on “liberating” tweets from the platform by converting them to Nanopublications. A lot has changed in the last year, and Science Twitter has shrunk considerably. The user experience for those who remained has deteriorated considerably and the developer experience is even worse. Given the current platform turbulence, Science Twitter’s future is not clear.

With all that said, Science Twitter is currently still a significant community and it still harbors valuable discourse. We aren’t abandoning Science Twitter, but we are changing our priorities and approach to it.

One direction we’re particularly excited about is a collaboration with Community Archive, a wonderful project also focused on Twitter data liberation. Currently, users need to manually upload their data to the Archive, but tools to automate this process are also under development. An interesting potential collaboration interface could be an Archive - Cosmik - ATProto integration to enable public archiving while respecting user data sovereignty.

From the outset, we’ve recognized the need for ecosystems, beyond products. Since then, this recognition has only been sharpened by recent developments.

By the emergence of AI coding tools making product development more accessible than ever before.

By the increasing precarity of doing science in a fragmented, atomized and extractive system where researchers compete for dwindling resources while their labor enriches platforms and publishers that give little back to the scientific community.

By inspiring collaborations with other Open Science builders who share our conviction, like Rowan Cockett at the Continuous Science Foundation:

We started a movement because we need a place big enough to imagine something different—and small enough to actually build it together. Modular science isn’t just a technical shift, it’s a cultural one. And that starts with community.

By our collaboration with Ida Josefiina at The Agency, who helped us realize we’re building a movement. Products “can’t inspire people to feel like they are part of a cause they believe in. That’s what movements do.”

The real magic will happen when our systems help researchers stop feeling like isolated competitors and start experiencing themselves as part of a movement - a living, evolving collective intelligence. When unique insights don't disappear into the void but become building blocks for others, when our data trails trigger serendipitous connections between minds that would never have met - this is where breakthroughs will emerge.

Join the movement 🤝