What technical and behavioural methods that can be used to improve the quality of data within police systems, including to reduce the burden on users and correct inputs by staff to reduce human error?
Background
"Analytics is the ability to synthesise information to draw insights that can lead to actionable decisions, often in combination with other information and at scale.
The value of analytics to policing rests on the quality of the data on which it can draw. We are therefore interested in technical and behavioural methods that can be used to improve the quality of data within police systems. Our core interests relate to reducing the burden on users, correcting inputs, measuring data quality, and enriching data from other sources where it is legal and proportionate to do so. There are near-term opportunities through Robotic Process Automation, but we are equally interested in novel solutions and system changes that advance how we create, store, and utilise our diverse data sources."
Next steps
"We welcome your engagement with our ARIs in the following ways:
• If you have evidence that completely or partly supports or answers one of our ARIs, we invite you to share that with us. For any ongoing research relevant to policing and crime reduction, we encourage you to register your research on the College of Policing’s research projects map, which has been designed to promote collaboration and support requests for participants.
• If you are, or plan to be, carrying out research that relates to one of our ARIs, we’d like to hear about it. While we cannot respond to speculative approaches for research funding, we will where possible act to support your ambitions, including finding you policing partners where possible.
• If you are submitting a funding or grant application that aligns with one of our ARIs, we hope that referencing policing’s ARIs will help to strengthen your case for the possible public impact of the research.
• We will use the ARI document to structure our academic engagement, prioritise events and build new connections with external partners. We will be using our ARIs in our engagement with UKRI, and we will publish any opportunities for funding via our website https://science.police.uk/
Please send any correspondence and questions to [email protected], including ‘ARI’ in the subject heading."
Source
This question was published as part of the set of ARIs in this document:
Related UKRI funded projects
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A Research Network to Explore the Use and Regulation of Predictive Analytics in Policing
Advances in big data, information processing technology, and artificial intelligence are purported to confer immense benefits to law enforcement agencies when investigating crimes and administering criminal justice, incl...
Funded by: AHRC
Lead research organisation: University of Sheffield
Why might this be relevant?
Partially relevant as it focuses on predictive analytics in policing, but does not directly address data quality improvement.
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Policing Academic Centre of Excellence
Context & challenge: The Scottish Policing Academic Centre of Excellence (SPACE) brings together interdisciplinary academic expertise in three key substantive themes: Safety, Prevention, and Analytics; underpin...
Funded by: ESRC
Lead research organisation: Edinburgh Napier University
Why might this be relevant?
The project focuses on improving data quality within policing systems, including analytics, but does not specifically address reducing burden on users or correcting inputs.
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Bournemouth University Higher Education Corporation and Bluestar Software Limited KTP 23_24 R3
To develop novel Artificial Intelligence solutions for law enforcement agencies to automatically assess the value of evidential material to assist in the investigative process and improve the detection of crime. To exten...
Funded by: Innovate UK
Lead research organisation: BOURNEMOUTH UNIVERSITY HIGHER EDUCATION CORPORATION
Why might this be relevant?
The project focuses on developing AI solutions for law enforcement agencies, which could potentially address data quality issues and reduce human error.