Visualising Close Call in railways: a step towards Big Data Risk Analysis

In the Big Data era new data sources are available to get insight from human factors in railways. Close Call System (CSS) is one of the data sources which are being researched in the Big Data Risk Analysis (BDRA) project to... [ view full abstract ]

In the Big Data era new data sources are available to get insight from human factors in railways. Close Call System (CSS) is one of the data sources which are being researched in the Big Data Risk Analysis (BDRA) project to extract valuable information for risk management. One of the key challenges of BDRA is the visualisation of a large amount of information into a simple and effective display to risk analysis and making-decisions. In this paper we present the research in converting the free text from Close Call data into a spatial representation of networks of words and perform the text visual analysis in order to identify risk categories. For a small number of Close Call records related to level crossings, trespasses and slips, falls and trips, it was possible to identify the different scenarios. Moreover, the results provide an understanding of how Close Call events are described and how it might influence safety on the railways.