Tiered Data Views for Law Enforcement Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for presenting and analyzing large datasets, particularly in law enforcement investigations, are inefficient and lack effective tools for generating and visualizing multiple views of data, hindering the analysis process.
Innovation Solution
The system generates and presents multiple views of data, including minimized, active, and small views, allowing users to interactively overlay and resize these views to enhance data visualization and analysis efficiency, using processors to manage and render these representations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If multiple views of data are generated and presented simultaneously, then data visualization completeness is improved, but system complexity increases
Solution Approach 1:
The data presentation system is segmented into multiple independent view components (minimized view, active view, small view) that can be generated and managed separately. Each view represents a distinct segment of the data presentation functionality, allowing the system to handle complex visualization requirements through modular, manageable units rather than a monolithic structure.
Solution Approach 2:
Multiple views are nested within a hierarchical structure where minimized views contain references to active views, which in turn contain references to small views. This nested organization allows comprehensive data visualization across multiple levels while maintaining a manageable system architecture, as each nested level builds upon the previous one rather than requiring independent management of all views simultaneously.
2Productivity
If tiered views with multiple sizes are implemented, then data analysis efficiency is improved, but interface complexity increases
Solution Approach 1:
Different view sizes (minimized, active, small) are assigned to different functional contexts within the interface. Each view type has optimized characteristics suited to its specific purpose: minimized views for overview, active views for detailed analysis, and small views for supplementary information. This local optimization of view properties enhances data analysis efficiency while keeping the interface manageable through context-appropriate design.
Solution Approach 2:
The view hierarchy implements dynamic transitions between different view states and sizes. Users can dynamically expand minimized views to active views, collapse active views to small views, and navigate between different levels of detail as needed. This dynamic adaptability allows the interface to respond to user needs in real-time, improving analysis efficiency without requiring a static, overly complex layout.
3Ease of operation
If interactive overlay and resize functions are added, then user interaction capability is improved, but processing requirements increase
Solution Approach 1:
The system pre-generates multiple view representations (minimized, active, small views) before user interaction occurs. By preparing these views in advance and establishing their hierarchical relationships beforehand, the system reduces the processing burden during actual user interactions. When users perform overlay or resize operations, the system manipulates pre-computed view data rather than generating representations from scratch, thereby improving ease of operation while managing processing requirements.
Data Source
AI summary
Systems are disclosed including, for example, one or more processors configured to execute the instructions and perform operations including receiving data from one or more data sources; generating, by one or more processors, a plurality of tiers of views for the received data, the plurality of tiers of views including a minimized view, an active view, and a small view; and rendering, by the one or more processors, a representation of the received data, the representation including an active view of a first set of data in the received data and a small view of a second set of data in the received data.