Modular Visualization Update via Hierarchical Data Segmentation
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Solution Overview
Problem
Existing data visualization systems require extensive resources to rebuild the entire hierarchy when hierarchy data is modified, and they struggle with different data formats and malformations, leading to inefficiencies and communication issues.
Innovation Solution
The system implements modular updating of hierarchical data, where only affected portions of the hierarchy are updated, using a data transform to change data formats and apply changes through a one-directional chain of stages, allowing for efficient resource allocation and format normalization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the entire hierarchy is rebuilt whenever hierarchy data is modified, then the visualization remains up-to-date, but system resources are excessively consumed
Solution Approach 1:
The patent divides the hierarchy into separate nodes and segments, allowing individual nodes to be updated independently rather than rebuilding the entire hierarchy. Each node can be modified, added, or removed without affecting the reconstruction of other nodes, thus reducing system resource consumption while maintaining visualization accuracy.
Solution Approach 2:
The system dynamically determines which portions of the hierarchy need updating based on change notifications received from data sources. Instead of static full-rebuild behavior, the system adapts by cascading updates only to affected nodes and their descendants, optimizing resource usage based on actual data changes.
2Adaptability or versatility
If different hierarchy data formats are supported, then system adaptability improves, but complexity of data processing increases
Solution Approach 1:
The patent introduces a format-agnostic node structure as an intermediary layer between different hierarchy data formats and the visualization engine. Data from various formats (JSON, XML, CSV, etc.) is transformed into this standardized node representation, which then feeds into the modular update mechanism. This intermediary abstraction handles format diversity without increasing the complexity of the core update logic.
3Productivity
If hierarchical data is normalized to a standard format, then data processing efficiency improves, but data transformation overhead increases
Solution Approach 1:
The system performs format normalization and transformation into the standard node structure as a preliminary action during initial data loading and subsequent change notifications. By preparing data in the standardized format upfront, the actual update and visualization processes can proceed efficiently without repeated transformation overhead, as the modular update mechanism operates directly on the pre-normalized node structure.
Data Source
AI summary
The modular updating of visualizations is provided. Elements of a visualization (e.g., graphical representations of data series, axes, titles, etc.) are only updated within the visualization when the hierarchical data defining that element is changed, thus reducing the processing load on the system providing the visualization. According to an aspect, the changes in the data are accurately translated from an arbitrary hierarchy format into a normalized hierarchy format so that a data visualization platform modularly update the hierarchical data that defines the visualization. According to an aspect, modular updating of hierarchy data enables updating a visualization in pieces (i.e., modularly), such that portions of the visualization that are not affected by the change to the data are not updated and do not need to be recalculated for rendering.