Editorial Snapshot: Research papers after the PDF: How AI, machine-readable data, and automated peer review are changing how publications are shared
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- Published: 2026/09/16
For generations, the scientific manuscript has been optimized primarily as a human-readable narrative: structured text containing an abstract, introduction, methods, results, figures, tables, and references, accompanied by supplementary files where necessary. Although journals may ultimately convert accepted manuscripts into PDFs and other publication formats, the material submitted by authors is increasingly more complex than a document alone. Modern research can generate vast datasets, sophisticated computational workflows, versioned code, and machine-learning models, while researchers increasingly rely on AI systems to search and synthesize the literature. The manuscript is therefore becoming less a self-contained narrative and more an interface to a network of interconnected research objects. Standards such as NISO's Journal Article Tag Suite (JATS) illustrate how journal content can be represented in structured, machine-readable form, while the FAIR Principles emphasize that research data should be findable, accessible, interoperable, and reusable.