Scholarly Knowledge Graphs (SKGs) support literature search, scientific discovery, and agent-assisted research. Yet, most approaches to SKG construction pre-specify the knowledge unit to be represented, typically named scholarly entities or contribution-level statements, and retain only the publication content expressible through that unit.
This choice produces two dominant yet distinct paradigms: concept-centric SKGs that preserve entities and local relations, and statement-centric SKGs that capture high-level discourse in sentences.
In both cases, the graph reflects a chosen extraction target rather than how a paper constructs and communicates knowledge.
We introduce SUDO, the Scholarly Upper Discourse Ontology, which defines how knowledge elements are organized and related to form a paper's research narrative, namely its scholarly discourse.
Using linguistic principles that generalize across fields and tasks, SUDO enables each publication's scholarly discourse to be constructed from the bottom up as a coherent, source-grounded representation.
Applied consistently across papers, the same structure connects their research narratives into a global scholarly discourse without discarding local context or provenance.
We demonstrate SUDO's capabilities across a comprehensive suite of scholarly knowledge-modeling use cases and performance improvements on a downstream Large Language Model (LLM)-based scientific QA task.