Data Science & Crime

The Data Science & Crime research line focuses on combining various digital tools such as explainable AI and web-harvesting/OSINT to collect and process data. This can be applied to cold-cases, environmental crime and the guarding and security sector.

Key themes in the research:

Explainable AI (XAI) research: XAI aims to make AI models more transparent, allowing users to interpret how complex algorithms produce specific outcomes or predictions. This is crucial in safety and security applications as it ensures transparency and accountability in decision-making processes.

OSINT involves the collection and analysis of publicly available information from various sources, such as websites, social media and public records, to gather intelligence, track criminal activity and identify threats.

Web-harvesting refers to the use of software tools to collect specific information from web pages, which can then be analysed.

Geo-information refers to data relating to the geographical location and characteristics of natural or man-made features on Earth. This information is used to analyse spatial relationships, predict patterns, monitor locations and make informed decisions for effective planning and response. Remote sensing enables more efficient real-time (or near real-time) data collection in inaccessible or large areas and helps monitor and detect illegal activities.