Reinventing Discovery: The New Era of Networked Science

The Engine of Scientific Discovery: How New Methods and Tools Spark Major Breakthroughs

Abstract. How do we spark new scientific discoveries? Why do some breakthroughs seem even accidental? And most importantly, how can we accelerate them and

Infinite Researchers | AI-Powered Scientific Discovery

What happens to the speed of discovery if we have infinite researchers? Explore AI experiments accelerating breakthroughs.

Governing by dismantling: tech oligarchy and the stifling of public data infrastructure

Published in Science as Culture (Ahead of Print, 2026)

How AI Agents are transforming scientific discovery

AI agents are starting to reshape science, from proposing novel hypotheses to writing code. Learn what comes next for scientists and policymakers.

Inventing New Nature

Defining the Protocol Institute's research mission

Coordination Tech in Science: Letters, Journals, and Whatever Comes Next | shishyko!

To modernize our scientific infrastructure, we need new contextualization and coordination technologies that decouple trust from legacy branding — shifting from gatekeeping on write to algorithmic contextualization on read.

Rebuilding the Architecture of Science

Science built the modern world. It’s time to rebuild the world of science.

Sensemaking Networks: Project Introduction - Cosmik Labs

Incorporating science social media into the scientific process

Index Network: Discovery Protocol

Finding people living in New York who listen to avant-garde jazz and curious about the semantic web, or discovering the latest events attended by peo...

Open Science Network

Reclaim scientific discourse with federated digital spaces where researchers shape their own conversations, data, and collaborations

Kempner Researchers Create Social Network for “AI Scientists” to Collaborate - Kempner Institute

Science rarely advances exclusively through lone researchers. Progress often comes from discussion and collaboration — scientists sharing ideas, questioning one another, and refining their thinking together. Now, a team of […]

A Vision of Metascience

How does the culture of science change and improve? Many people have identified shortcomings in core social processes of science, such as peer review, how grants are awarded, how people are selected to become scientists, and so on. Yet despite often compelling criticisms, strong barriers inhibit widespread change in such social processes. The result is near stasis, and apathy about the prospects for improvement. People sometimes start new research institutions intended to do things differently; unfortunately such institutions are often changed more by the existing ecosystem than they change it. In this essay we sketch a vision of how the social processes of science may be rapidly improved. In this vision, metascience plays a key role: it deepens our understanding of which social processes best support discovery; that understanding can then help drive change. We introduce the notion of a metascience entrepreneur, a person seeking to achieve a scalable improvement in the social processes of science. We argue that: (1) metascience is an imaginative design practice, exploring an enormous design space for social processes; (2) that exploration aims to find new social processes which unlock latent potential for discovery; (3) decentralized change must be possible, so outsiders with superior ideas can't be blocked by established power centers; (4) ideally, change would align with what is best for science and for humanity, not merely what is fashionable, politically popular, or media-friendly; (5) the net result would be a far more structurally diverse set of environments for doing science; and (6) this would enable crucial types of work difficult or impossible within existing environments. For this vision to succeed metascience must develop and intertwine three elements: an imaginative design practice, an entrepreneurial discipline, and a research field. Overall, it is a vision in which metascience is an engine of improvement for the social processes and ultimately the culture of science.

The Scientific Contribution Graph: Automated Literature-based Technological Roadmapping at Scale

Sir Isaac Newton famously wrote, “If I have seen further, it is by standing on the shoulders of giants”. Scientific contributions are rarely developed in isolation, but build upon prior contributions, such as problem framings, experimental methods, and empirical findings. Understanding these prerequisite relationships is important for studying scientific progress, and for automated scientific discovery systems that must reason about which existing capabilities can be used to develop new ones (e.g. Lu et al., 2024; Jansen et al., 2025b; Baek et al., 2025).