Dynamic Investigation Timeline for Entity Data Visualization
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Solution Overview
Problem
Conventional data investigation systems provide static data visualizations, limiting investigators' ability to understand the evolution of a case and the relationships between entities over time, requiring navigation through multiple interfaces and data processing systems, which can lead to incomplete or missed data sources and relationships.
Innovation Solution
A data investigation system that utilizes dynamic data visualizations to create a network topology of entities and events, allowing investigators to view an investigation timeline, recalculate risk alerts based on changed data points in time, and access enriched entity details, using risk scores and key performance indicators to identify relevant data points and relationships.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If static data visualizations are used, then data processing systems can maintain simplicity and stability, but investigators cannot understand the evolution of cases and relationships over time
Solution Approach 1:
The patent implements dynamic data visualizations that allow investigators to interact with and navigate through data over time. The system provides temporal navigation capabilities enabling users to move between different time points, view historical changes, and understand evolution of cases and relationships, transforming static displays into interactive temporal explorations.
Solution Approach 2:
The patent adds a temporal dimension to data visualizations, allowing investigators to view data not only spatially but also chronologically. This dimensional addition enables understanding of evolution over time by layering time as a fourth dimension alongside traditional spatial data presentation.
2Productivity
If investigators navigate through multiple interfaces and data processing systems, then comprehensive data can be accessed, but the process becomes time-consuming and inefficient
Solution Approach 1:
The patent merges multiple data processing systems and interfaces into a unified platform. By consolidating data sources and processing functions into a single integrated system, investigators can access comprehensive data without navigating between multiple separate interfaces, significantly reducing time and improving efficiency.
Solution Approach 2:
The patent creates a universal data processing system that performs multiple functions within a single interface. The system can process, visualize, and analyze data from various sources simultaneously, eliminating the need for investigators to switch between specialized systems and improving overall productivity.
3Reliability
If conventional data systems are used, then system stability is maintained, but relevant data sources and relationships may be missed
Solution Approach 1:
The patent implements feedback mechanisms that automatically detect and highlight relevant data sources and relationships based on the investigation context. The system provides intelligent guidance and recommendations, helping investigators discover pertinent information that might otherwise be missed while maintaining ease of operation through automated data relevance filtering.
Data Source
AI summary
A system is provided for a data investigation system that is adapted to provide optimized data viewing for investigations using a network topology of relations between entities. The system includes a processor and a computer readable medium operably coupled thereto, to perform operations which include receiving, from a computing device, an investigation of a first entity having a first set of attributes, determining, based on the first set of attributes, a plurality of related entities associated with a plurality of events, determining whether each of the plurality of events meets or exceeds a risk threshold for the investigation of the first entity, generating a first relations graph of the first entity to one or more of the plurality of related entities based on one or more of the plurality of events meeting or exceeding the risk threshold, and displaying, on the computing device, the first relations graph.