Abstract Visualisation and presentation of complex, feature rich data is often neglected within the area of quantitative risk assessment when, in reality, a clear representation of the data may greatly support the understanding of complex results and increase acceptance of results among risk managers. Feature rich data containing many explanatory variables can be very challenging to visualise effectively in a single graphic as the message can become cluttered when using two, or more, variables. As part of the international SPARE project (SPARE project team, 2018), a generic quantitative risk assessment (QRA) combining multiple routes and routes of entry was developed (Simons et al., 2019). The risk assessment provides an overall risk score for entry and exposure of three different pathogens into individual European Union (EU) countries: Classical swine fever (CSF), Bluetongue virus (BTV) and classical rabies. This paper describes the development of an application with graphical user interface (GUI) that allowed users, in particular risk managers, to explore the data and calculations behind the QRA. The aim was to produce an application that clearly illustrates the data and communicates the information without biasing their opinion in any way. To reach as wide an audience as possible the application should be easily accessed and understood without requiring the user to have detailed technical computing knowledge to use it. Development of the application followed a set of design principles focused on: context, software, data inputs and interactivity. This produced an application designed for a particular audience, written in a suitable language that allowed the user to explore the data within the context of a clearly defined risk question. Accessibility options for users with visual challenges was also considered and included within the design phase.
Communicating outputs from risk assessment models: A picture paints a thousand words
C. Cook,R. Simons,V. Horigan,A. Adkin,G. Ru,M. de Nardi
Published 2019 in Microbial Risk Analysis
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- Publication year
2019
- Venue
Microbial Risk Analysis
- Publication date
2019-12-01
- Fields of study
Computer Science, Engineering, Environmental Science
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Semantic Scholar
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