PDF Tagging Tool

The PDF Tagging Tool provides a workflow to assign structured metadata to PDF documents. It targets content teams, librarians, researchers, and archives managers who manage large PDF catalogs and require consistent tagging, especially when metadata is missing or inconsistent. By embedding metadata into PDFs or exporting a machine-readable sidecar, organizations can standardize tagging across collections and improve discovery while maintaining compatibility with existing metadata standards.
Conceptually, the tool ingests a PDF, extracts visible text and, when needed, performs OCR on image-only pages. It then applies taxonomy-based tagging rules to populate fields such as title, author, keywords, subject, and description. It supports standard schemas like Dublin Core and XMP and can enforce custom taxonomies via field mappings. Outputs include an embedded metadata block in the PDF and a JSON or CSV sidecar that can drive downstream indexing and analytics.
Benefits and use cases: academic libraries tagging research papers, publishers tagging content metadata for distribution, legal teams tagging contract PDFs for compliance metadata, and enterprises organizing internal documents. Batch tagging scales to thousands of files, with provenance data for audit trails and reproducibility. Multi-language tagging enables non-English PDFs to be correctly indexed, while quality checks identify missing fields and low-confidence extractions for review.
Unique value: configurable taxonomies, batch processing, and dual output (embedded PDF metadata plus sidecar) for interoperability; OCR fallback and language-aware processing; and governance features such as field validation and audit trails that support compliance reporting and catalog hygiene.