Spatiotemporal Visualization for Temporal Pattern Analysis
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Solution Overview
Problem
Conventional data analysis tools provide snapshot representations of key performance indicators (KPIs) that do not convey performance over time, making it difficult for analysts to identify key patterns across time and space, leading to a less powerful analysis experience and increased frustration.
Innovation Solution
The system generates and displays spatiotemporal visualizations, such as light streak charts, that convey changes in KPIs over time, enabling analysts to understand 'how' performance evolved rather than just 'what' has happened, by using a client-server system with a query engine, calculation engine, and renderer to create interactive and intuitive visualizations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If conventional snapshot representations of KPIs are used, then the representation is simple and easy to generate, but the ability to convey performance over time is lost
Solution Approach 1:
The patent transforms traditional 2D static chart representations into 3D spatiotemporal visualizations by adding a temporal dimension. This allows performance data to be visualized across multiple time points simultaneously, enabling analysts to observe trends and patterns over time without requiring multiple separate snapshots. The third dimension represents time progression, allowing the visualization to convey temporal patterns while maintaining intuitive graphical representation.
2Productivity
If spatiotemporal visualizations are implemented, then the analysis capability is enhanced, but the system complexity increases
Solution Approach 1:
The system is divided into distinct functional modules: a data processing module that handles temporal data aggregation, a visualization generation module that creates spatiotemporal representations, and an interaction module that manages user queries. This segmentation allows each component to be optimized independently, reducing overall system complexity while maintaining enhanced analytical capabilities.
Solution Approach 2:
The patent introduces an intermediary visualization layer between the raw data and the user interface. This intermediary spatiotemporal representation layer processes complex temporal patterns into intuitive visual forms, shielding users from underlying system complexity while providing powerful analytical insights. The intermediary layer acts as a buffer that simplifies the interface between data processing and user interaction.
Data Source
AI summary
Techniques of providing spatiotemporal visualizations are disclosed. In some example embodiments, a spatiotemporal visualization of at least a portion of data of a dataset is generated and displayed to a user in a graphical user interface of a device. An embodiment comprises receiving data comprising a plurality of measures and a plurality of dimensions; calculating a minimum and maximum magnitude of velocity for measures in the data; defining intervals in a range defined by the minimum and maximum velocity; selecting configuration settings for rendering a spatiotemporal visualization corresponding to the data and the intervals; generating the spatiotemporal visualization, the spatiotemporal visualization comprising a graphical representation of at least a portion of data comprising at least one of the measures and at least one of the dimensions over the defined intervals; and causing display of: the spatiotemporal visualization, and a plurality of selectable interaction controls corresponding to the spatiotemporal visualization.