Dimension-Based Visual Elements for Hierarchical Map Data Exploration
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Solution Overview
Problem
Current mapping technologies lack effective methods for visualizing and interacting with data categorized by multiple dimensions on maps, particularly in providing granular and hierarchical representations of data, which limits user insight and data exploration capabilities.
Innovation Solution
A system and method that generate dimension-based visual elements on maps, allowing users to query and render data from a dataset, aggregate records by location, and interact with visual elements to drill down into hierarchical dimensions, using a combination of visible and invisible elements for input detection and data presentation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If data is categorized by multiple dimensions on maps, then data exploration capability is improved, but device complexity increases
Solution Approach 1:
The patent segments data into multiple hierarchical dimensions (e.g., geographic regions, product categories, time periods) that can be independently explored. Each dimension is represented as a separate visual element on the map, allowing users to drill down through different levels of granularity without overwhelming the system with monolithic data processing.
Solution Approach 2:
The patent adds visual dimensionality to map data by rendering multi-dimensional datasets as layered visual elements (such as heat maps, bubble charts, or stacked bars) overlaid on geographic locations. This transforms abstract multi-dimensional data into spatially representable visual forms that enhance exploration capability while maintaining manageable system complexity through standardized rendering pipelines.
2Measurement precision
If granular data representation is provided, then measurement precision is improved, but information overload increases
Solution Approach 1:
The patent applies local quality by allowing different levels of data granularity to be displayed at different geographic locations or map regions based on user interaction. High-granularity detailed data is presented only when users drill down into specific areas of interest, while broader aggregate data is shown at higher zoom levels, preventing information overload while maintaining measurement precision where needed.
Solution Approach 2:
The patent implements dynamic data representation where the level of granularity automatically adjusts based on user interaction, map zoom level, and selected time periods. Users can dynamically drill down from aggregate regional data to specific location-level metrics, and the system responds by loading and displaying appropriately granular data only when required, balancing detail with information management.
3Ease of operation
If interactive visual elements are implemented, then ease of operation is improved, but device complexity increases
Solution Approach 1:
The patent implements universal interactive visual elements that serve multiple functions across different dimensions. For example, clicking on a geographic marker can simultaneously filter data by location, open a detail panel, and adjust time period filters, all through a single standardized interaction pattern. This multi-functionality enhances ease of operation while avoiding the need for separate complex interaction mechanisms for each data dimension.
Solution Approach 2:
The patent introduces intermediary control elements such as filter panels, legend overlays, and context menus that mediate between user interactions and complex data processing. These intermediaries provide a simplified interface layer that translates user actions into structured data queries, enhancing ease of operation while shielding users from the underlying system complexity through standardized interaction protocols.
Data Source
AI summary
In some embodiments, a program generates a query for a set of data from a dataset. The dataset includes a set of measures and a plurality of dimensions for categorizing the set of measures. The set of data includes a set of locations and measure values for a measure in the set of measures categorized according to a dimension in the plurality of dimensions. The program further sends the query to a computing system configured to manage the dataset. The program also receives the set of data from the computing system. The program further renders a visualization comprising a set of visual elements. Each visual element is configured to present a set of measure values for the measure associated with a location in the set of locations. The set of measure values are categorized according to the dimension. The program also presents the visualization on a display of the device.