PhD dissertation project
Supervisors: Prof. Annalisa Pelizza (Universoty of Bologna), Prof. Stefan Kuhlmann and Dr. Ir. Maurice van Keulen (University of Twente).
This dissertation investigates the intricate interplay between data matching technologies, identification practices, and transnational commercialized security infrastructures, particularly within migration management and border control. The study was driven by a curiosity about the interplay between identity data matching and the ‘blind spots’ faced by authorities in identifying individuals, even when faced with incomplete data, aliases, and other uncertainties. The study sets out to answer the overarching question: How are practices and technologies for matching identity data in migration management and border control shaping and shaped by transnational commercialized security infrastructures?
The dissertation starts by outlining the existing literature on the connections between data matching technology, which is utilized in various sectors, and its association with the internationalization, commercialization, securitization, and infrastructuring of identification. This overview notes a noticeable gap in understanding how data matching influences the meaning of the interconnected data and shapes relationships between organizations that utilize it. The dissertation proposes using data matching as both a research topic and a resource for answering specific sub-questions.
First, the dissertation focuses on how data models play a crucial role in categorizing individuals and determining connections between different data models to match data. The Ontology Explorer is introduced as an innovative method for analyzing the knowledge and assumptions embedded in data models. When applied to national and transnational security infrastructures, this method reveals the complexities of authorities’ imaginaries on people-on-the-move. The data models’ categories of data emerge as a significant way for gaining insights into how authorities enact people in distinct ways.
Next, the dissertation delves into re-identifying applicants at a government migration agency. Re-identification is conceptualized as including the continuous use and interconnection of data from various sources to confirm whether multiple sets of identity data belong to a single real-world individual. The chapter draws insights from interview data to explore the integration of data matching tools for re-identification. While data matching intends to alleviate data friction in re-identification, it also comes with certain costs and often results in unexpected challenges that the agency’s staff encounter in their daily activities.
Lastly, this study investigates the development of a commercial data matching system used for identification and security purposes from a sociotechnical perspective. The chapter presents heuristics to identify moments that highlight the system’s design contingencies. Various actors and entities have played a crucial role in influencing the system’s design, leading to its evolution from a generic data matching system to a specialized tool used for identification and security purposes. The research highlights the interconnections between software suppliers, integrators, and customers and how knowledge and technology for matching identity data are circulated and shared across organizations.