MDPI (Multidisciplinary Digital Publishing Institute)
Accelerating scientific discovery through AI-enhanced open access publishing and peer-review automation.
The pioneer in open, post-publication peer review and transparent scholarly publishing.
F1000Research is a leading open research publishing platform that leverages a unique post-publication peer review model to accelerate the dissemination of scientific knowledge. Unlike traditional scholarly journals, F1000Research publishes articles immediately following a rigorous pre-publication sanity check, allowing the global research community to access findings without the delays of conventional editorial cycles. As of 2026, the platform has matured its technical stack to include AI-driven metadata enrichment and automated compliance validation for FAIR (Findable, Accessible, Interoperable, and Reusable) data standards. The technical architecture supports a versioning system that treats research as a living document, enabling authors to update their findings in response to reviewer feedback and new data. This transparent approach ensures that all reviewer comments, author responses, and previous versions are permanently archived and citable. F1000Research is part of Taylor & Francis and is widely recognized for its high-integrity standards, mandated open data policies, and integration with major scholarly indexes including PubMed, Scopus, and Google Scholar. It serves as a critical infrastructure for researchers who prioritize transparency, reproducibility, and speed in the scholarly communication lifecycle.
Uses a persistent DOI system where each revision receives a new version suffix, maintaining a clear lineage of scientific evolution.
Accelerating scientific discovery through AI-enhanced open access publishing and peer-review automation.
Empowering the global research community through open-access scientific publishing and a proprietary XML-first workflow.
Verified feedback from the global deployment network.
Post queries, share implementation strategies, and help other users.
Enforces a policy where all source data must be hosted in external, citable repositories and linked via the Data Availability Statement.
Reviewer identities and their full reports are published alongside the article, linked via unique DOIs.
Uses AI to extract and tag entities like chemicals, genes, and proteins within the text for better discoverability.
Algorithmic matching of manuscript keywords against a global database of expert profiles and publication history.
Real-time monitoring of social media mentions, news coverage, and policy document citations.
Supports Plotly and other interactive visualization embeds directly within the HTML article view.
Traditional journals take months to publish, which is too slow during a pandemic or health crisis.
Registry Updated:2/7/2026
Developers often find it difficult to get formal academic credit for the software they build.
Publication bias leads journals to reject studies where the hypothesis was not proven.