How are data-driven policing systems constructed through systems of data gathering, classification, and categorisation?

1.识别在英国数据驱动的警务系统中捕获的数据类型，并创建一个表示此的数据地图。2.批判性地评估这些数据来自何处、如何使用以及用于何种目的。3.确定和评估影响数据从创建到警察系统/应用的过程中的摩擦和转换的不同点。4.探索和比较与收集、分类和归类有关的不同数据方法是如何发生的，并调查这些方法的意义和推论。评估这些数据实践和流程如何重新配置警务。该项目采用多方法方法，将货车Es和de Lange（2020）的数据行走思想结合起来，作为研究数据、数据化和数据化基础设施的一种方式，并与数据旅程的思想相结合（Bates等人，2016年第2页），以跟踪数据从其在“生产场所”的初始创建到“数据实践场所”，同时确定数据发生的变化（可变性），然后确定数据后来如何分发或使用。通过文件分析、访谈和观察实践的混合，将创建一个数据地图，该地图将可视化数据在进入数据驱动的警务系统之前如何在各个组织和机构之间传播。关键领域：数据共享、数据调查、犯罪前、数据驱动的警务、分类、分析

1. To identify the types of data captured within a data-driven policing system in England and create a data map which represents this.2. To critically assess where such data has come from, how it is being used, and for what purpose(s).3. To identify and assess the different points of friction and translation that affects data on its journey from creation to police system/application.4. To explore and compare how different data approaches relating to collection, categorisation and classification are occurring and to investigate the meaning and inferences made because of such approaches.5. To assess how these data practices and processes are reconfiguring policing. This project is taking a multi-methods approach combining van Es and de Lange's (2020) idea of datawalking as a way to study data, datafication, and infrastructures of datafication, merged with the idea of data journeys (Bates et al., 2016 p.2) to track data from its initial creation at "sites of production" and through "sites of data practice", whilst identifying the changes that occurred to the data (mutability), and then how the data was later distributed or used. Through a mixture of document analysis, interviews, and observant practice a data map will be created that will visualise how data travels around and through various organisations and institutions before entering a data-driven policing system.Key Areas: Data-sharing, Dataveillance, pre-crime, data-driven policing, classification, profiling