Since mid 2013 more than 25k Tweets were published. These human-readable short messages are transformed into machine-readable data using latest text-mining algorithms. Messages are classified if they relate to the same event. Events are the basis for more detailed analysis.
Aggregated statistics about reasons, involved train lines, and involved stations provide a general understanding of the stability of the rail network. For example, the identification of most affected stations can help to detect hot spots in the rail network.
Interactive Visualization Tool
Our S-Bahn Analyzer provides an interactive data exploration tool. Thus, more detailed analysis are possible, e.g. to answer specific hypotheses of service planners, maintainers, or service operators. The analysis includes the complete history of events and the user can filter the data using individual criteria. As there is no dedicated database expertise required, even inexperienced users can gain new insights easily.
Through the real-time analysis of historic event data, the duration and impact of a current event can be predicted. For example, the following diagram helps to predict the duration of a current event at Station “Schöneweide” based on details about historic events. This builds the foundation for timely and more accurate communication of the expected impact to passengers, which is crucial to identify appropriate alternatives at an early stage.
Real-time Event Map
Passengers get a real-time overview of the complete rail network when accessing our S-Bahn Analyzer prior to traveling. It shows latest events and therefore help to select an appropriate route based on the current network state. The map can also be used to explore historic events in a time lapse resulting in an animation of all events.