TL;DR: OpenDataLoader’s auto-tagging engine analyzes the document’s layout, detecting headings by visual text properties, identifying tables by grid patterns, recognizing lists by bullet positions and then writes this structural information directly into the PDF’s internal structure tree.
PDF accessibility begins with mapping document content (headings, paragraphs, tables, lists) into a logical structure tree that assistive technologies can navigate. Manual tagging is slow, error-prone, and impractical for large document volumes.
⁉️ How OpenDataLoader Implements Tag Writing
OpenDataLoader is the first open-source tool which adds tags directly into the initial PDF file without altering the visual appearance of the document. The AI analyzes document structure, distinguishes components such as titles, tables, lists, and images, and inserts the corresponding tags into the source PDF.
Key characteristics of OpenDataLoader’s approach:
- No proprietary SDK dependency: most existing tools rely on commercial SDKs for the tag-writing step;
- #OpenDataLoader does it all under Apache 2.0 license.
- On-premise processing : sensitive documents never leave your network
- No page caps or watermarks unlimited use without document quantity restrictions
OpenDataLoader’s auto-tagging was built in collaboration with the
Dual Lab (Member of PDF Association, supports veraPDF, developers of
PDF4WCAG Accessibility checker.
OpenDataLoader’s auto-tagging preserves visual integrity by design. The technology adds semantic structure without touching the presentation layer, follows industry specifications validated by PDF accessibility experts, and has been built specifically to solve the accessibility problem without creating new ones.
Read more https://opendataloader.org/accessibility
GitHub:
https://github.com/opendataloader-project/opendataloader-pdf
Top comments (0)