Visual analytics for text-based railway incident reports. (November 2016)

• Record Type: Journal Article
• Authors: Figueres-Esteban, Miguel; Hughes, Peter; van Gulijk, Coen
• Is Part Of: Safety science. Volume 89(2016)
• Page Start: 72
• Page End: 76
• Publication Date: 2016-11
• Subjects: Close call -- Visual analytics -- Railway safety -- Risk analysis -- Network text analysis; Industrial accidents -- Periodicals; Accident Prevention -- Periodicals; Safety -- Periodicals; Travail -- Accidents -- Périodiques; 363.11
• DOI: 10.1016/j.ssci.2016.05.009
• Languages: English
• ISSNs: 0925-7535

Abstract

Highlights: Visual analytics to perform Close Call text analysis for risk analysis. Identification of risk scenarios using network text analysis. Insight into railway-personnel's perception of risky situations during their daily work. Rethinking the traditional methods to represent safety scenarios. Abstract: The GB railways collect about 150, 000 text-based records each year on potentially dangerous events and the numbers are on the increase in the Close Call System. The huge volume of text requires considerable human effort to its interpretation. This work focuses on visual text analysis techniques of Close Call records to extract safety lessons more quickly and efficiently. This paper treats basic steps for visual text analysis based on an evaluation test using a pre-constructed test set of 150 Close Call records for "Trespass", "Slip/Trip hazards on site" and "Level crossing". The results demonstrate that visual text analysis can be used to identify the risks in a small-scale test set but differences in language use by different cohorts of people interferes with straightforward risk identification in larger sets. This work paves the way to machine-assisted interpretation of text-based safety records which can speed up risk identification in a large corpus of text. It also demonstrates how new possibilities open up to develop interactive visualisations tools that allow data analysts to use text analysis techniques for risk analysis.