# Micropublications: a Semantic Model for Claims, Evidence, Arguments and Annotations in Biomedical Communications

arXiv: https://arxiv.org/abs/1305.3506 · HTML: https://mlsanity.com/paper/1305.3506/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 15 May 2013.

## Built on by (most cited first, 6 of 6)

- [F(AI)2R: Who Did What, and Who Checked? Verifiable AI Provenance as an Executable Skill](https://mlsanity.com/paper/2607.25637/) (2026)
- [EviGraph: Evidence-Guided Autonomous Research Agents](https://mlsanity.com/paper/2608.04738/) (2026)
- [Toward an Engineering of Science: Rebalancing Generation and Verification in the Age of AI](https://mlsanity.com/paper/2605.10425/) (2026)
- [Provenance-Enhanced Statements in Knowledge Graphs](https://mlsanity.com/paper/2606.15246/) (2026)
- [Towards a new paradigm of scientific discovery with socialized artificial intelligence](https://mlsanity.com/paper/2608.02775/) (2026)
- [Semantic Knowledge Technologies: what the Semantic Web lost sight of, and what it never had](https://mlsanity.com/paper/2609.14121/) (2026)

## 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.