Discourse graph refers to an information model which represents scientific discourse by distilling "traditional publication down into more granular, formalized knowledge claims, linked to supporting evidence and context through a network or graph... knowledge claims ... as the central unit".
Why? "Standardizing the representation of scientific claims and evidence in a graph model can support machine reasoning... the potential of discourse graphs to accelerate human synthesis work... and thereby accelerate innovation and scientific discovery "
Decentralising discourse graphs allow the work to be carried out by many people, fulfilling many roles (What community roles are necessary in a decentralized knowledge graph? ): primary research, develop frameworks and theories, determine directions to explore, annotate and/or rank others' work, "connecting the conversation between various fields", etc.
Love this: "While tools like Roam Research and Obsidian enable people to develop advanced discourse graphs for themselves, over time they may end up with a system that is so complicated that maintaining it becomes work. Why not split up the effort...?"
cf Social Knowledge Graphs, in my PKGBook chapter.
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See also: Digital Transformation