PubMed-OCR: PMC Open Access OCR Annotations
Abstract
PubMed-OCR is an OCR-centric corpus of scientific articles derived from PubMed Central Open Access PDFs. Each page image is annotated with Google Cloud Vision and released in a compact JSON schema with word-, line-, and paragraph-level bounding boxes. The corpus spans 209.5K articles (1.5M pages; ~1.3B words) and supports layout-aware modeling, coordinate-grounded QA, and evaluation of OCR-dependent pipelines. We analyze corpus characteristics (e.g., journal coverage and detected layout features) and discuss limitations, including reliance on a single OCR engine and heuristic line reconstruction. We release the data and schema to facilitate downstream research and invite extensions.
Fields of Study & Subjects
Handwritten Text Recognition Techniques
Information Systems and Technology Applications
Biomedical Text Mining and Ontologies
Publication details
- Journal / source
- arXiv (Cornell University)
- Publication date
- 16 January 2026
- Document type
- Preprint