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Visualizing the Linked Manuscript Archive: A Linked Open Data Approach to Analyzing Special Collections Data Cover

Visualizing the Linked Manuscript Archive: A Linked Open Data Approach to Analyzing Special Collections Data

By: Maisie Jones  
Open Access
|Jan 2026

Abstract

Linked Open Data (LOD) has found significant use across several rare book and manuscript (RBM) digital archives in recent decades. LOD methodologies for processing institutional or cross-institutional collections enable practitioners to link objects on both an individual and collections level within a relational semantic knowledge base. LOD approaches to collections metadata also enable representing various organizational and descriptive features of digital manuscripts. In the vein of this work, the Digital Scriptorium (DS), a LOD-based digital pre-modern and early modern manuscript catalog, operates as a cross-institutional repository of RBM objects from over 50 member institutions. DS has applied LOD principles to establish relational metadata and bespoke knowledge base for a cross-institutional manuscript collection. This article represents research born from the LIS Education and Data Science Integrated Network Group (LEADING) Research Fellowship into how implementing LOD in a RBM environment impacts searchability and usability of manuscript data and represents how those data exist within the collection. This work included direct collaborations and mentorship from the University of Pennsylvania Schoenberg Institute for Manuscript Studies DS team. This article discusses the creation, analysis, and visualization of catalog data following the publication of DS’s multi-year LOD redevelopment project.

DOI: https://doi.org/10.5334/johd.444 | Journal eISSN: 2059-481X
Language: English
Submitted on: Oct 27, 2025
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Accepted on: Jan 9, 2026
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Published on: Jan 23, 2026
Published by: Ubiquity Press
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2026 Maisie Jones, published by Ubiquity Press
This work is licensed under the Creative Commons Attribution 4.0 License.