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Cloud-based digitization workflow with rich metadata acquisition for cultural heritage objects

Krzysztof Kutt, Luiz do Valle Miranda, Jakub Gomułka, Grzegorz J. Nalepa

TL;DR

The paper presents a cloud-based digitization workflow that enables domain experts to acquire rich metadata for cultural heritage objects using familiar Microsoft 365 tools, culminating in a linked data knowledge graph (TAO) populated from Excel-based metadata. It combines The Knowledge Matrix (TKM), the Standard Entries Catalog (SEC), and a Mapping system (MAP) with Office Script and Python validators, stored in SharePoint and extended into an OWL-based TAO ontology. Evaluation across two pilots and two workshops demonstrates the approach's practicality, yielding a large, queryable knowledge base and confirming usability for the Jagiellonian Library while remaining compatible with existing workflows. The work offers a scalable, accessible methodology for GLAM institutions to enrich metadata and enable interoperable, RDF-based representations of their collections.

Abstract

In response to several cultural heritage initiatives at the Jagiellonian University, we developed a new digitization workflow in collaboration with the Jagiellonian Library (JL). The solution is based on easy-to-access technological solutions -- Microsoft 365 cloud with MS Excel files as metadata acquisition interfaces, Office Script for validation, and MS Sharepoint for storage -- that allows metadata acquisition by domain experts regardless of their experience with information systems. The ultimate goal is to create a knowledge graph that describes the analyzed collections, linked to general knowledge bases, as well as to other cultural heritage collections, so careful attention is paid to the high accuracy of metadata and proper links to external sources. The workflow was evaluated in two pilot studies and in two workshops, which allowed for its refinement and confirmation of its correctness and usability for JL. The knowledge graph created as a result of these pilot studies was made available in a public git repository. As the proposed workflow does not interfere with existing systems or domain guidelines regarding digitization and basic metadata collection in a given institution, but extends them in order to enable rich metadata collection, not previously possible, we believe that it could be of interest to all GLAMs.

Cloud-based digitization workflow with rich metadata acquisition for cultural heritage objects

TL;DR

The paper presents a cloud-based digitization workflow that enables domain experts to acquire rich metadata for cultural heritage objects using familiar Microsoft 365 tools, culminating in a linked data knowledge graph (TAO) populated from Excel-based metadata. It combines The Knowledge Matrix (TKM), the Standard Entries Catalog (SEC), and a Mapping system (MAP) with Office Script and Python validators, stored in SharePoint and extended into an OWL-based TAO ontology. Evaluation across two pilots and two workshops demonstrates the approach's practicality, yielding a large, queryable knowledge base and confirming usability for the Jagiellonian Library while remaining compatible with existing workflows. The work offers a scalable, accessible methodology for GLAM institutions to enrich metadata and enable interoperable, RDF-based representations of their collections.

Abstract

In response to several cultural heritage initiatives at the Jagiellonian University, we developed a new digitization workflow in collaboration with the Jagiellonian Library (JL). The solution is based on easy-to-access technological solutions -- Microsoft 365 cloud with MS Excel files as metadata acquisition interfaces, Office Script for validation, and MS Sharepoint for storage -- that allows metadata acquisition by domain experts regardless of their experience with information systems. The ultimate goal is to create a knowledge graph that describes the analyzed collections, linked to general knowledge bases, as well as to other cultural heritage collections, so careful attention is paid to the high accuracy of metadata and proper links to external sources. The workflow was evaluated in two pilot studies and in two workshops, which allowed for its refinement and confirmation of its correctness and usability for JL. The knowledge graph created as a result of these pilot studies was made available in a public git repository. As the proposed workflow does not interfere with existing systems or domain guidelines regarding digitization and basic metadata collection in a given institution, but extends them in order to enable rich metadata collection, not previously possible, we believe that it could be of interest to all GLAMs.
Paper Structure (10 sections, 4 figures)

This paper contains 10 sections, 4 figures.

Table of Contents

  1. Introduction and motivation
  2. Cultural heritage collections and digitization landscape at Jagiellonian University
  3. Related work
  4. Objectives and requirements
  5. Methods and tools
  6. Designing TKM, SEC, and MAP
  7. Data validation scripts
  8. TAO ontology population
  9. Evaluation
  10. Conclusions

Figures (4)

  • Figure 1: Metric sheet of the TKM containing general information of the whole unit (in Polish), i.e., the metadata that will be converted to MARC 21 format to create records in library catalog (title, card number, format, etc).
  • Figure 2: Main sheet of the TKM with one row per document in a given unit (in Polish). One can see the result of the Office Script (errors marked with red color, fields not used in a given category marked with gray background) and the "OK?" button that triggers the script.
  • Figure 3: SEC sheet with person-related metadata (in Polish).
  • Figure 4: The digitzation workflow in practice.