by Isaelle Donatz-Fest
Donatz-Fest, I. (2024). The ‘doings’ behind data: An ethnography of police data construction. Big Data & Society, 11(3). https://doi.org/10.1177/20539517241270695
Data are the lifeblood of algorithmic systems. But data are often taken for granted by public organizations who see them as something just lying around, ready to use. Such is the case with police reports, which are increasingly used as data for algorithmic applications for policing worldwide.
But there are ‘doings’ behind data. Data are created in unexpected places—like the front seat of a speeding police car or the desk of an overworked detective. Material factors and human actors interact behind-the-scenes, informing data creation and interpretation.
I spent ~200 hours (ethnographically) observing how street-level employees at the Netherlands Police translate events to police reports. What I found was that data work is deeply embedded in policing, shaped by personal values, organizational context, and practical considerations.
Structured data often clashes with the officers' understanding of a situation. Registration software demands incidents are fit into predefined categories, but the messy world that we live in rarely fits neatly into such boxes. Unstructured data provides more flexibility and richness but introduces complexities for standardization and (algorithmic) interpretation. Open text fields open the door to linguistic nuances, inconsistencies, and what I term 'voice,' the various identities present in the text.
I saw officers wrestle with these limitations, sometimes bending rules, sometimes choosing the path of least resistance. These choices reflect officer values and the pressures they face. Whether it’s a commitment to justice, a desire to help a colleague, or the need to quickly move on to the next call, the context impacts the data directly.
This work offers new empirical insight on the data underpinning public sector algorithms. By understanding the doings behind data, we can begin to question how we use them in algorithmic systems, which is particularly relevant in fields as impactful and powerful as policing.
