Incident Data Visualization with Event Map and Swimlane Views
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Solution Overview
Problem
Current methods for analyzing and visualizing incident data are inefficient, lacking comprehensive tools for investigators to effectively process and annotate data from various sources, such as communications, video recordings, and sensor data, which hinders thorough incident investigation and post-incident discussions.
Innovation Solution
A system comprising a database, data processing computer system, and display module that allows users to select, annotate, and visualize incident data through a graphical user interface (GUI) with features like event list view and swimlane view, enabling users to create tags, collections, and adjust time intervals for enhanced data manipulation and visualization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If multiple data sources are collected for incident analysis, then the quantity and comprehensiveness of data increases, but the complexity of data processing and analysis increases
Solution Approach 1:
The system segments incident data from multiple sources into distinct data sets, each representing a specific source (e.g., communications, video recordings, sensor data). This segmentation allows investigators to organize and analyze data from different sources independently while maintaining the ability to correlate events across sources through the common event structure (timestamp, source, content).
Solution Approach 2:
The patent introduces an intermediary processing layer that standardizes data from various sources into a unified event format. This intermediary structure (with standardized fields for timestamp, source, and content) acts as a mediator between diverse data sources and the analysis tools, simplifying the complexity of handling heterogeneous data while preserving the quantity and diversity of incident data.
2Measurement precision
If investigators manually analyze and annotate incident data, then the precision of analysis can be maintained, but the time required for investigation increases
Solution Approach 1:
The system performs preliminary organization and structuring of incident data before detailed analysis. By automatically collecting data from multiple sources and organizing it into standardized event structures with timestamps and source identifiers, the system prepares the data in advance for analysis. This preliminary action reduces the time investigators need to spend on data preparation while maintaining their ability to perform precise manual analysis and annotation of the organized data.
Solution Approach 2:
The system provides feedback mechanisms that allow investigators to annotate events and receive immediate visual updates in the timeline and event lists. This feedback loop enables investigators to efficiently refine their analysis by seeing the impact of annotations in real-time, reducing the iterative time required for precise incident reconstruction and understanding.
3Loss of information
If detailed event annotations are added to each incident event, then the depth of analysis improves, but the complexity of data visualization increases
Solution Approach 1:
The patent adds a temporal dimension to the visualization by displaying annotated events on a timeline. This dimensional approach allows detailed annotations to be organized chronologically, enabling investigators to see both the depth of individual event annotations and their position in the overall incident sequence. The timeline dimension helps manage visualization complexity by providing a natural organizing framework for detailed information.
Solution Approach 2:
The system implements a nested visualization structure where event details and annotations are nested within the timeline framework. Each event on the timeline can contain multiple layers of information (basic event data, annotations, related events), similar to nested dolls. This nesting allows detailed analysis information to be organized hierarchically, improving depth of understanding while managing visualization complexity through structured nesting rather than flat presentation.
Data Source
AI summary
Apparatus and method for investigating an analyzable incident for a period of time has a database to receive and store data sets, coupled to a data processing computer system that operates upon the data sets, and a display module comprising a graphical user interface (“GUI”). Each data set comprises a series of events comprising a timestamp, a source, and a content about the analyzable incident. The GUI comprises an event map, a control panel, and an annotation panel viewable in an event list view or a swim lane view. The event list view has a tabular list of the timestamp, source, and the content of each event. The swim lane view comprises a graphical representation of the timestamp and the source of each event, and a user selectable icon associated with the content of each event.