Method multi-layer tree map
Comparison of analogue and digital crime
Why is it relevant to communicate uncertain events to consumers?
Why is it problematic to communicate uncertain events to consumers?
The method of the multi-layer tree can be used for risk problems, i.e. when reliable numbers are available about how often certain events occur. The method is supposed to give consumers an understanding of the probability of occurrence of certain events and enable them to draw comparisons. The multi-layer tree map offers the possibility to graphically communicate absolute frequencies of uncertain events to the user. Larger tiles stand for more frequent events and thus greater probabilities of occurrence, and smaller tiles for rarer events. Multi-level tree maps that have multiple levels of depth, for example, if you want to break a category down into different subcategories, use level navigation to map hierarchies.
The interactive and dynamic visualisations are designed to help inform consumers and to be appealing at the same time.
Proof of effectiveness
First results of the RisikoAtlas communication studies with multi-layer tree maps show that they are better received and more likely to be explored than tables with the same information. This information is extracted and remembered as well as with traditional tables.
- Garcia-Retamero, R., & Galesic, M. (2010). Who proficts from visual aids: Overcoming challenges in people’s understanding of risks. Social Science & Medicine, 70(7), 1019–1025.
- Stasko, J., Catrambone, R., Guzdial, M., & McDonald, K. (2000). An evaluation of space-filling information visualizations for depicting hierarchical structures. Int. J. Human-Computer Studies, 53, 663–694.
Option 1: You can embed the given visualisation
<iframe frameborder="0" height="650px" src="https://static.risikoatlas.de/visualisations/crime/crime.html" width="1024px"></iframe>
Comparison of analogue and digital crime
Crime is as widespread in the digital world as it is in our analog everyday lives. However, as the digital world evolves dynamically and rapidly, you usually have less experience of how your behaviour on the Internet can affect the risk of becoming a victim of digital crime. In addition, many people have only limited knowledge of the full range of digital crime risks and the extent to which they can affect them. Click through our tree map for an overview and comparison!
What does the chart show?
The tree map shows the frequency of offences from the point of view of those affected to become victims of analogue and digital offences. In order to convey the relationship between the various criminal offences, the frequencies of analogous criminal offences from victim statistics by the police are compared with the registered cases of computer crime. The visualisation does not take into account digital risks through institutional surveillance, e.g. customer profiling.
By clicking on the tiles you can dive into the respective categories of criminal offences. By clicking on the arrow that appears in the upper left corner, you can always return to the start page. All figures refer to the total population of Germany. If available, separate bars on the right-hand side provide additional information on how often different age groups or men or women became victims. Since different age groups and genders often entail different levels of risk, the horizontal axis (x-axis) of the diagram goes as far as the group-specific risk maximum.
Where are the numbers coming from?
All numbers represent registered crime victims from the past. They were taken from the Police Crime Statistics 2016.
What is the quality of the data?
It is only possible to draw limited conclusions about future years from a year in the past. However, the proportionality of the various risks of becoming a victim of certain crimes is roughly the same in the future. How many consumers really are affected is not equally well understood for analogue and digital crimes. Not only are the unreported numbers for digital crimes much higher than for "classic" crimes, but the diversity and constantly new types of crime as well as transnational networks also make it difficult to record them. Improved digital crime registration suggests an increase in these numbers in the future.