Multi-Criteria Data Organizer Using Nested Tables
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Solution Overview
Problem
Current data display technologies, such as tree and pivot tables, are inadequate for efficiently navigating and classifying large, complex data sets, as they primarily rely on single criteria and lack the ability to expand/collapse data in multiple directions, limiting user interaction and data exploration.
Innovation Solution
The development of a graphical user interface (GUI) that utilizes multi-descriptions and nested-table displays, allowing users to prioritize and apply multiple classification criteria, with direction-sensitive navigation control icons to browse data hierarchically and visually, enabling the creation of human-readable displays from data items.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional single-criteria data display methods (tree tables, pivot tables) are used, then the display structure is simple and easy to implement, but the ability to navigate and classify large complex data sets is insufficient
Solution Approach 1:
The patent implements nested tables where inner tables are embedded within outer tables, allowing multiple levels of data classification simultaneously. Each nested table represents a different classification criterion, enabling users to explore data through multiple dimensions without leaving the current view context.
Solution Approach 2:
The patent transitions from traditional single-dimension data display to multi-dimensional display by introducing nested tables that represent different classification dimensions. This allows data to be organized and navigated along multiple criteria simultaneously, effectively adding dimensional depth to the display structure.
2Productivity
If multiple classification criteria are applied simultaneously, then data exploration capability is enhanced, but the difficulty of navigating and understanding the data structure increases
Solution Approach 1:
The patent segments the complex multi-criteria data structure into hierarchical nested tables, where each table represents a specific classification criterion. This segmentation allows users to navigate through data step-by-step using direction-sensitive icons, breaking down the complex navigation task into manageable directional movements.
Solution Approach 2:
The patent introduces direction-sensitive navigation icons as intermediaries between the user and the complex nested table structure. These icons provide intuitive visual cues for navigation directions, mediating the interaction between users and the multi-dimensional data structure, thereby simplifying navigation despite the complexity of multiple classification criteria.
3Loss of information
If data is displayed in a comprehensive tabular form with multiple criteria, then information completeness is improved, but the readability and visual clarity of the display deteriorates
Solution Approach 1:
The patent uses nested tables to organize comprehensive multi-criteria data in a hierarchical structure. This nesting allows complete information to be displayed while maintaining visual clarity through progressive disclosure - users can see the overall structure at outer table levels and drill down into inner tables for detailed information, preventing information overload at any single view level.
Data Source
AI summary
A user interface includes a first display area which includes a first control widget representative of a first attribute group and a second control widget representative of the second attribute group, and a second display area in which a first measure of a first portion of a plurality of data items can be displayed in response to a user activating the first control widget. A first classification attribute from a first attribute group and a second classification attribute from a second attribute group are associated with each data item of the plurality of data items. A multi-description is generated for each data item, the multi-description including a list of pairs of the first classification attribute and the second classification attribute.