Data-driven ballast layer degradation identification and maintenance decision based on track geometry irregularities

Ballast layer defects are the primary cause for rapid track geometry degradation. Detecting these defects in real-time during track inspections is urgently needed to ensure safe train operations. To achieve this, an indicator, the track degradation rate (TDR) was proposed. This rate is calculated using track geometry inspection data to locate...

Diagnosing and Addressing Emergent Harms in the Design Process of Public AI and Algorithmic Systems

Algorithmic and data-driven systems are increasingly used in the public sector to improve the efficiency of existing services or to provide new services through the newfound capacity to process vast volumes of data. Unfortunately, certain instances also have negative consequences for citizens, in the form of discriminatory outcomes, arbitrary...

Data science for service design: An introductory overview of methods and opportunities

To support effective and successful projects, Service Design practitioners rely on insights that mainly build on qualitative research methodology. The literature on data science promises to help transform how design research is done, adding sophisticated quantitative analyses, complementing existing methods with the power of machines. Due to...

Editorial: Frontiers in water: Rising stars 2021

Editorial: Data Science Applications to Inverse and Optimization Problems in Earth Science

Cybersecurity via Intermediaries: Analyzing Security Measurements to Understand Intermediary Incentives and Inform Public Policy

Research in the field of information security economics has clarified how attacker and defender incentives affect cybersecurity. It has also highlighted the role of intermediaries in strengthening cybersecurity. Intermediaries are organizations and firms that provide the Internet’s infrastructure and platforms. This dissertation looks at how...

Mass Media Musical Meaning: Opportunities from the Collaborative Web

In the digital domain, music is usually studied from a positivist viewpoint, focusing on general ‘objective’ music descriptors. In this work, we strive to put music in a more social and cultural context, looking into ways to unify data analysis methods with thoughts from the humanities on musical meaning and significance. More specifically, we...