Discourse Graphs

Information Model

Discourse Graphs are an information model that enables researchers and communicators to map their ideas and arguments in a modular, composable graph format.

Distinguishing evidence (the empirical observation) from claim (the proposed answer) leaves space for multiple interpretations.

Better Infra for Communication

Discourse Graphs allow researchers to break the scientific research process into its atomic elements in a way that can be shared, remixed, and updated.

Distinguishing evidence (the empirical observation) from claim (the proposed answer) leaves space for multiple interpretations.

Synthesize and Update

Discourse Graphs enable researchers to exchange knowledge in a form that makes it straightforward to construct, update, and find.

Like Lego™️ bricks, the modular components of the Discourse Graphs data model make it easy to choose which parts of a scientific project you wish to share and build upon.

Liberate your findings

Rather than being organized hierarchically, discourse graphs adopt a grassroots organization, which better matches the iterative and nonlinear process of knowledge generation.

The schema adds enough structure for you to revisit "high signal" findings as "the minimal shareable insight" for others to build on.

As such, discourse graphs provide a needed coordination layer for decentralized science.

Client-Agnostic & Researcher-Aligned

Discourse Graphs are a decentralized knowledge exchange protocol designed to be implemented and owned by researchers — rather than publishers — to share results at all stages of the scientific process.

Discourse Graphs are client-agnostic with decentralized push-pull storage & and can be implemented in any networked notebook software (Roam, Notion, Obsidian, etc.), allowing researchers to collaborate widely while using the tool of their choice.

Discourse Graphs support and incentivize knowledge sharing by making it easy to push to and pull from a shared knowledge graph — and to claim credit for many more types of contributions.

Discourse Graphs are like github for scientific communication.

Snapshot of MATSU lab Discourse Graph

The natural OS for a Cloud Laboratory

The flexible Discourse Graph framework has been adapted to coordinate and share active research, helping to lower the barrier for interdisciplinary collaboration.

Lab Discourse Graphs can be used to support:

• identifying gaps in knowledge and tractable "starter projects" for new researchers
• faster onboarding to existing research projects
• grassroots generation of knowledge between researchers
• modular communication and attribution of research findings