ABSTRACT
In the era of big data, safety management systems will have to be designed in alignment with information technology development practices. This facilitates processing large quantities of data related to safety that cannot be meaningfully analyzed by humans to make decisions or uncover complex trends that may indicate the presence of hazards. Automated techniques for mining these data are required to provide better understanding of our systems and the environment within which they operate. Big data risk analysis is a research program that investigates techniques to develop sensible data systems for safety management and discusses the basic constituents of them: data, ontology, visualization, and enterprise architecture. This work paves the way for the comprehensive design of digitally enabled decision support for safety and risk management.
