Researching a Rigged Game: Digital Approaches to Tracing the Illicit Trade in Cultural Objects

The illicit trade in cultural heritage is a serious transnational crime that deprives communities of their history and identity, erodes public trust, and undermines public institutions. To respond to this multifaceted challenge, researchers must operate at the intersection of law, archaeology, art history, digital forensics, and data science. This has brought renewed attention to the value and complexity of digital approaches for mapping the illicit trade of cultural objects. Increasingly, digital data has proven a valuable resource in studying the physical and digital movement of objects, as well as the social networks underpinning them, and their potentially illicit and unethical entanglements. This volume foregrounds these digital approaches, including but not limited to open data, open-source intelligence (OSINT), open-access scholarship, computational forensics, and archival digitisation, as core tools in a growing, interdisciplinary effort to combat the illicit trade of cultural objects.

Intelligence is a powerful resource that is not only the exclusive prerogative of police, armed forces and government agencies, but it is also a valuable asset for analysts working in the private sector. The aim of this chapter is to provide an overview of open-source intelligence (OSINT) and its challenges and opportunities as part of a private sector analyst’s operational experience applied to the analysis of companies and people. The sources, tools and techniques described can indeed be applied in many areas and contexts, including the analysis of actors and entities involved in the trafficking of cultural heritage. Furthermore, it presents an OSINT methodology suitable for practitioners and researchers who do not have access to law enforcement sources or classified information.

Open-source information is everywhere—potential data sources continuously surround us. Yet, as the volume of available sources grows, the ability to effectively use and understand their contents becomes a struggle. One way to address this need to balance depth of understanding with breadth of collection is to quantify the open-source data into a dataset or database. Synthesizing diverse open sources systematically can create robust and reliable data. In turn, those data can make it easier to process large quantities of information and facilitate analyses of entirely new sets of questions. This chapter presents an instructional account of one method of quantifying open-source data, based on the Berkeley Protocols on Digital Open-Source Investigations and experience from the CURIA lab. It argues that a process that prioritizes transparency, triangulation, metadata, and sustainability ensures a robust and reliable result. It demonstrates this method in the creation of a spatiotemporal dataset of cultural violence in the Syrian Conflict from 2014 to 2017 and discusses some of the applications for the resulting quantitative data.

Although understudied in the past, archaeological looting is now closely monitored constantly prompting new research. This chapter outlines a new methodological approach to the study of looting through the analysis of open-access satellite imagery and the statistical processing of the results obtained. Building on three regional case studies in Syria, Iraq, and Afghanistan, the chapter proposes a typology of looting and summarizes its main trends. The multiscale and multitemporal approaches highlighted in this chapter also enable intra-site case studies to be considered in a new light, as shown through an analysis of looting at Tell Senkereh-Larsa, a site located in southern Mesopotamia devastated by illegal excavations. This chapter demonstrates that by using archaeological methodologies and analysing looting pits, as if they were archaeological objects or structures themselves, allows for a more nuanced and detailed analysis of looting practices. Borrowing from spatial analysis, morpho-typologies and statistical analysis methods, it contributes to a greater understanding of the movements and targets of looters and how they operate from a social science perspective.

The European Union-funded project RITHMS (Research, Intelligence and Technology for Heritage and Market Security) offers a network-focused approach to tackling cultural heritage crime, particularly trafficking. The project brings together a consortium of researchers, data analysts, law enforcement agencies, and scientific institutes across Europe to integrate interdisciplinary data in a platform to address the illicit trade using social network analysis (SNA). Data have been gathered from a range of open sources to enable reconstruction and examination of a sprawling network of actors involved in the circulation of cultural goods. Analysis of this network has the potential to reveal valuable information and insights about the circulation of cultural goods and the character of individual transactions. This chapter first offers theoretical background for the core concepts at the root of the project, namely trafficking, SNA, and the collection of open data. It then explores three case studies that highlight diverse approaches to data analysis which emphasise the value of open-source intelligence and promising methods for intelligence-led policing of and research into cultural goods crimes. This research reinforces the importance of an interconnected analysis among isolated datasets and encourages a broader approach to studying the circulation of cultural goods using these open sources.

This chapter presents an innovative computational method for detecting possible deception in the provenance texts of artworks. This is important because false ownership histories can conceal the kind of textual “red flags” that alert experts to potentially looted art. The first section presents the study’s scope, context and approach to automating the detection of Nazi-looted art by analysing provenance texts and explains the urgency of solving the problem of deception. The second part presents provenance datasets, and a digital tool developed for counting words linked to unreliability, uncertainty or anonymity, which may indicate potentially deceptive language. The third part analyses the strengths and weaknesses of this methodology, exploring lessons learned. Benefits of the methodology described here include transparency, objectivity and replicability, as well as the generation of quantitative and Boolean metadata for artworks that can be fed into ranking applications, recommender systems, knowledge graphs, and AI, in order to potentially quantify deception within the art market. Challenges include optimization of ranking methods and the tension between open data and closed archives, which complicates the verification of the artworks flagged. The chapter concludes with opportunities for future developments in different domains.

Collection databases, like the collections they record, are continuously changing entities shaped by human decisions and their cultural, economic and political contexts. Although analogous with collections, these databases have historically been used as management tools or for searching and sorting information related to objects. Over the past 20 years, recognition of the value of using collection data as a research tool for historical research, including provenance and the trade in cultural heritage, has grown. Through a comparative examination of projects that have used collection data within this context, this chapter will critically reflect on the ethical challenges and considerations of data integrity and data absence when working with museum collection databases. It will review projects based in the United Kingdom and Europe, that have engaged with diverse cultural heritage collections and their databases, timescales and perspectives, but share a common interest in looking across collections at scale. This chapter highlights the potential of large-scale analyses to augment what we can understand about museum collections and the wider art and antiquities market. Nevertheless, I argue that this potential is limited by the bias within, instability of and ultimately access to museums’ digital collection records.

In recent decades, an ever-increasing number of institutional collections have begun to comprehensively digitise their collections and make the resulting catalogues available freely online. These online catalogues have brought to light a number of objects that may have previously never been displayed and have allowed scholars to better understand the nature and scope of collections around the world. As such, they are a valuable source of open access data for those interested in the trade in cultural heritage and history of collecting. Focussing on forged papyri, this chapter considers the communication of (in)authenticity in online collection catalogues to better understand the reliability of the information they provide. It will be shown that although issues with authenticity appear to be recorded more often than current research would perhaps suggest, the reasons for presenting material as either authentic or inauthentic are frequently not made clear. As such, when forgeries are mistakenly presented as authentic in these online catalogues, their authenticity appears secure and there is little indication to anyone working from the catalogue that there might be some form of issue.

While auction data provides an accessible, long-term source of quantifiable market data, recent scholarship has emphasised the need for contextualisation of sales data to gain a more comprehensive understanding of external and internal market dynamics. But how and with what data? This chapter proposes digitised historical newspapers as a viable choice for contextualising both auction data and the market for cultural heritage. An overview of the use of auctions and their records as data is presented alongside some potential blind spots in their analysis. This will be followed by a comprehensive overview of digitised newspapers as a complementary qualitative source of data for auctions, including methodological approaches, tools, resources and technological, ethical and legal considerations. Using my doctoral research, which investigates Tutankhamun blockbuster museum exhibits and the market for Egyptian material as a case study, I will illustrate how a systematic survey of newspaper coverage of both auctions and exhibitions contextualises auction data and the market for Egyptian material.

This chapter details the Chandigarh Chairs project’s collection and analysis of online auction data during the COVID-19 pandemic. Collection and analysis of online auction data is presented as a successful method to remotely study items of modernist furniture from the Indian city of Chandigarh in lieu of more traditional design historical techniques. The method utilized by the project research team is presented, alongside research insights related to the objects of furniture themselves, as well as the broader market within which these objects are bought and sold. The chapter concludes by advocating further utilization of online auction data within the design historical field as both a tool for the generation of greater object knowledge and greater understanding of markets for objects of design.

Investigative journalism has been and continues to be an important open source of information about the antiquities trade. It should be borne in mind, however, that the aims of the investigative journalist are not necessarily concordant with those of the academic researcher or policymaker. To date, there has been no examination of any inherent weaknesses, deficiencies or biases embodied within those aims. With reference to the reporting of thefts during the 2010s of ancient gems from the British Museum, this chapter explores some possible shortcomings of investigative journalism but also demonstrates how it constitutes a valuable resource for academic research and policymaking.

Over the past century, the United States has implemented five cultural property policies and currently maintains over thirty bilateral agreements with individual foreign powers aiming to fight the illicit antiquities trade. Despite these initiatives to combat the issue, the illegal trade of cultural antiquities remains a veiled, multi-million-dollar market predominantly driven by United States collectors and institutions. In a discipline ridden with ethical concerns and research restrictions, this chapter presents one way of researching the illicit trade and explores potential methods of quantification and prevention. By examining prosecuted cases of antiquities trafficked from the Middle East and North Africa into the U.S. since the Gulf War, this chapter outlines a database framework for examining the impact cultural property policies have on combating the illicit trade from the demand side of the market. By utilizing publicly available sources to gather case documents, the database categorically and statistically analyzes prosecutions alongside object provenience, provenance, and related stakeholders. Adaptable across different jurisdictions, the methodology examined here presents a quantifiable, non-financial means of measuring the impact of the illicit trade in cultural objects alongside an assessment of the application and effectiveness of a country’s cultural property policies, which could contribute to more effective prevention measures.