Central Registry for Digitized Objects: Linking Production and Bibliographic ControlRalf StockmannGöttinger Digitization Center
As things are now• Huge ventures in – Digitization • Google • Microsoft • National programs • Local centers – Accessibility • World Digital Library • European Digital Library • National portals • Google Book Search
As things are now• We just face the dawn of mass digitization – Leaving behind the state of manufacturing – Entering industrialization – Scanning Robots – Accessible Full Text (OCR)
Lack of …• Coordination in digitization activities – Who scans what where when in which quality and how will it be accessible • How is “quality” defined? • Do we agree on “what”?
Facing the Consequences Technical Improvements Costs Waste of RessourcesCosts / Value Additional Benefit Number of digitized items per volume
The Solution• Central registry for digitized objects• Focused on the production context (no user frontend)• API driven – Application Programming Interface – Query / Ingest – Simple implementation into existing workflow-tools• Batch mode (lists)• Open Source / free service• Matching on volume level – Score / probability
Implementation Backend Services EROMM / EDL / OCLC / … Registry / Meta Data Store Aggregator / Normalizer / Mapping API Query Ingest Ingest Ingest ? ? ? ! ! !Present Collections Running Project Notice of Intent
Metadata Store• Bibliographic – Title – Author – Date – Place of publication Matching / Score – Number of Pages (?) „what“ – Language – Print / Format – Edition• Technical – Resolution – Color depth – File type / compression• Accessibility Additional Judging – Institution „who, where, which – Persistent identifier quality, how – Rights accesible“ – URL• Status – Digitized – In Progress Decisive Factor – Intended (Timeline?) „when“ – Requested?
Obstacles• (open source) Tools for automated matching / scoring?• Interface for manual comparison / decision making• Multivolume works: low rate of uniformity (near 50% of physical SUB stock before 1900)• Unicode• Transliteration tables• Random bound books• Reliable identifier – ISBN for old books?• Anticipated rate of accuracy: 50 – 70 %
Appreciation of Values• The goal is NOT to build a reliable database in terms of library standards• But to prevent further waste of resources.• If we manage to archive just 50% precision,• We saved a min. 50% of founding!
Work Packages• Define metadata model• Set up database• Implement mapping tools• Define API calls• Implement API• Build some connectors to popular mass digitization workflow tools (e.g. “Goobi”)• Establish ISBN workflow• Harvest existing sources• Start with a community of actual projects• Get some (!) founding• Estimated schedule plan: 6 months