Integration of Kitodo and OCR-D for Productive Mass-Digitisation

Implementation Project Kitodo / OCR-D

• Participants
  • Sächsische Landesbibliothek –
    Staats- und Universitätsbibliothek Dresden (SLUB)
  • Universitätsbibliothek der TU Braunschweig (UBBS)
  • Universitätsbibliothek Mannheim (UBMA)
• Volume: 8 man-years
• Duration: 2 years
• Start: October 2021

Prior Work

• SLUB staff: OCR-D coordination / module project (2018/19)
• UBMA: OCR-D module project (2018/19)
• SLUB, UBMA: OCR-D pilot libraries (2019/20)
• SLUB: Kitodo development (since 2012)
• UBBS: Kitodo testing, documentation, migration
• all: experienced OCR-D and Kitodo users

Premises

• Kitodo: Workflow Management System for libraries

  • Open-source, community-driven
  • Modules:
    • Kitodo.Production (digitisation workflows)
    • Kitodo.Presentation (DFG viewer etc.)
  • OCR: only via commercial plugins (black box, license costs)

• OCR-D: operative single-workstation command-line prototype

  • no network interfaces for distribution/scaling yet
  • no error recovery and dynamic workflow execution yet
  • no result quality estimation and runtime evaluation yet
  • no assisted/automatic workflow configuration yet

Goals (OCR-D)

1. Implement OCR-D as Web-based distributed system

   • easily scalable
   • easily deployable

2. Develop quality based workflow optimisation for OCR-D

   • use heuristics and models for quality estimation of interim results
     during preprocessing, segmentation and recognition
   • weight interim result quality relative to contribution to overall result (follow-up steps, other pages)
   • when insufficient, switch to alternative configuration for segment/page/document automatically, or abort computation
   • offer a set of empirically optimised, dynamically quality-controlled workflow configurations for various materials

Goals (Kitodo)

3. Implement OCR-D as OCR module in Kitodo.Production

   • import images, meta-data and structure data
   • track and visualise result progress/quality
   • error handling, versioning
   • export, validate and ingest results
   • edit and manage workflow configurations

4. Extend Kitodo.Presentation and DFG Viewer

   • user evaluation of results, versioning
   • user prioritisation of (re-)OCR tasks (On-Demand-OCR)

Goals (further)

• close collaboration with OCR-D coordination project

• cooperation with other OCR-D implementation/module projects

• Kitodo community workshops (disseminate and query requirements)

• Kitodo community OCR-D service (test operation)

System Architecture

• Kitodo with OCR-D "backend" as distributed system
• strong integration of data and process management
• generic/agnostic on both sides
  

Project Plan

• AP1 (SLUB): coordination and communication
• AP2 (UBBS): management of Kitodo community
• AP3 (SLUB): detailled technical specification
• AP4 (SLUB): OCR-D server implementation
• AP5 (SLUB): concept for automatic process control
• AP6 (SLUB): implement automatic process control
• AP7 (SLUB): develop quality estimation metrics & models
• AP8 (UBBS): set up OCR-D service for Kitodo community
• AP9 (SLUB): integrate OCR-D into Kitodo.Production
• AP10 (UBMA): integrate OCR-D into Kitodo.Presentation
• AP11 (UBMA): data storage, ingest and versioning
• AP12 (SLUB): run and test DFG Viewer with OCR on Demand
• AP13 (UBBS): evaluation and documentation with Kitodo community

Synergies and Interfaces

• extending the processor CLI for error handling/signalling and parallelism
• molding the final OCR-D Web API
• providing reference implementations for server components
• providing reference implementations for module containers
• definining an evaluator CLI (analogous to processor CLI)
• generalising the OCR-D workflow format for evaluators and switches
• running & evaluating workflow experiments systematically
• compiling optimised workflow configurations
• defining quality metrics for workflow steps

Q & A

Thank you!