Micropublications: a Semantic Model for Claims, Evidence, Arguments and Annotations in Biomedical Communications
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Abstract (arXiv)
The Micropublications semantic model for scientific claims, evidence, argumentation and annotation in biomedical publications, is a metadata model of scientific argumentation, designed to support several key requirements for exchange and value-addition of semantic metadata across the biomedical publications ecosystem. Micropublications allow formalizing the argument structure of scientific publications so that (a) their internal structure is semantically clear and computable; (b) citation networks can be easily constructed across large corpora; (c) statements can be formalized in multiple useful abstraction models; (d) statements in one work may cite statements in another, individually; (e) support, similarity and challenge of assertions can be modelled across corpora; (f) scientific assertions, particularly in review articles, may be transitively closed to supporting evidence and methods. The model supports natural language statements; data; methods and materials specifications; discussion and commentary; as well as challenge and disagreement. A detailed analysis of nine use cases is provided, along with an implementation in OWL 2 and SWRL, with several example instantiations in RDF.
Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). First posted on arXiv 15 May 2013.
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Citing papers per year: 2026: 6.
6 papers.
- 2026F(AI)2R: Who Did What, and Who Checked? Verifiable AI Provenance as an Executable Skillcited by 1
- 2026EviGraph: Evidence-Guided Autonomous Research Agentscited by 1
- 2026Toward an Engineering of Science: Rebalancing Generation and Verification in the Age of AIcited by 0
- 2026Provenance-Enhanced Statements in Knowledge Graphscited by 0
- 2026Towards a new paradigm of scientific discovery with socialized artificial intelligencecited by 0
- 2026Semantic Knowledge Technologies: what the Semantic Web lost sight of, and what it never hadcited by 0
- 2026Semantic Knowledge Technologies: what the Semantic Web lost sight of, and what it never had12 Sep 2026
- 2026EviGraph: Evidence-Guided Autonomous Research Agents5 Aug 2026
- 2026Towards a new paradigm of scientific discovery with socialized artificial intelligence3 Aug 2026
- 2026F(AI)2R: Who Did What, and Who Checked? Verifiable AI Provenance as an Executable Skill28 Jul 2026
- 2026Provenance-Enhanced Statements in Knowledge Graphs13 Jun 2026
- 2026Toward an Engineering of Science: Rebalancing Generation and Verification in the Age of AI11 May 2026