OwnershipTracker: a visual analytics approach to uncovering historical book ownership patterns

Journal article

Ownership relationships of early printed books from the 15th century reveal complex patterns of distribution and possession, offering valuable insights for historical research. This paper presents OwnershipTracker, a visual analytics application developed to explore and trace these relationships using data from the Material Evidence in Incunabula (MEI) database. OwnershipTracker integrates bibliographic records, copy-specific data, and book provenance and ownership details, enabling users to uncover intricate ownership sequences over time. The application combines several visualization techniques, including network graphs to map connections between owners, timelines for temporal analysis, chord diagrams to quantify transfer patterns, and a distinctive, collaboratively designed spiderweb-like diagram highlighting converging and dispersing ownership transfers through specific owners. Developed iteratively with input from historical book researchers, the application underwent multiple refinements to align with domain research requirements. A summative evaluation with domain experts showcased the tool's ability to address the defined requirements and tasks. The final version of OwnershipTracker is deployed and accessible at: https://booktracker.nms.kcl.ac.uk/ownership.

Authors: Xing, Y; Ji, M; Dondi, C; Abdul-Rahman, A

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: IEEE
• Journal: IEEE Transactions on Visualization and Computer Graphics
• Volume: 32
• Issue: 1
• Pages: 966-976
• Publication date: 2025-11-19
• Acceptance date: 2025-07-15
• DOI: 10.1109/tvcg.2025.3634653
• EISSN: 1941-0506
• ISSN: 1077-2626
• Language: English
• Keywords: human-centered design; data visualization; visual analytics; collaboration; testing; libraries; iterative methods; visual databases; market research; marine vehicles; complexity theory; design study; visualization application