Open Art Data
Laurel Zuckerman’s work currently focuses on the art world and the Holocaust. She explores how linked open data, natural language processing, network analysis and the digital tools and techniques of investigative data journalism can be used to identify patterns in false provenances in Nazi-looted art and duress sales.
Talks and Events
The Error is the Message: Extracting Insights from Deceptive Data for Nazi looted art
Turning dross into gold. Knowledge graphs, with their capacity for surfacing vast hidden networks, can help detect looted art from the ownership history – or provenance – of artworks. The cultural heritage sector and art industry have explored named entity recognition with an event-based approach using CIDOC-CRM. However, Nazi-looted art poses a particular challenge, in part due to the passage of time, and in part due to unreliable data, as attempts to conceal and distort information which began in the Nazi era continue into the digital age. Missing, confusing or badly coded entities, false dates, names, events, places, the mixing of speculation and fact occur with such frequency in Nazi-looted art that it is useful to view errors, not as anomalies to be cleansed from the dataset, but as primary features to be analyzed. This presentation focuses on strategies and methods to quantify, classify, code and exploit this unreliable information in order to detect looted art and the patterns and networks which underly its commercialisation.
Track: Business Use-Cases
- Business Use Cases
- Data Quality
- Data Governance