From Provenance Statements to Antiquities Trafficking Networks: A Privacy-Aware Workflow Using Repatriation and OSINT Data

It is difficult to capture the realities of the illicit antiquities market because of the lack of accessible, unsiloed data from underground trade networks. Despite existing literature on social network analyses and machine-learning experiments with antiquities data, there is a gap in simple open-source methodologies accessible to the non-academic public. By using a provenance-based analysis, we present a case study of the Italian antiquities trafficking networks that more fully captures their complexity. This study culls provenance data from repatriated antiquities gathered in the Museum of Looted Antiquities’ dataset to create a network visualization for analysis. Using open-source provenance and repatriation data from 1950 to July 2025, we built a dataset of 233 repatriation events with 15.858 objects to produce a network that reveals central actors, roles, and locations while staying within ethical privacy limits. This study captures large portions of the trafficking network by using accessible data and produces a reproducible, ethically framed workflow.