The contemporary world is rife with opportunities and challenges in the fields of security and transportation. Urbanization, globalization, digitalization, and population growth have all contributed to creating dynamic, complicated problems that need creative, practical solutions. Large and complex data sets generated in these domains can be analyzed, understood, and used with the help of solid tools provided by data science, which includes a wide range of techniques, including computer vision, machine learning, deep learning, statistics, natural language processing, etc. In fact, data science can potentially improve society’s safety and wellbeing as well as the effectiveness and performance of security and transportation systems. In this sense, some reflections linked to the Research Topic are raised, such as how data science can contribute to improving transport management and what is the impact of road infrastructure, urban design and transport systems in developing more sustainable and safer mobility for citizens? Or can data science identify which variables influence users’ driving decisions and behaviours? Consequently, this Research Topic aims to respond to these issues and demonstrate the state-of-the-art research and advances in data science that can address real-world problems in transportation, security and beyond.