Visualization Contract Schema for Automated Graph Data Updates
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Solution Overview
Problem
Existing visualization tools require manual updating and are time-consuming when underlying structured source data changes, and they often lack flexibility in handling different data formats and allowing user customization of visualizations.
Innovation Solution
The method involves using contracts with schemas to map data from various sources into standardized formats, allowing automatic generation and updating of visualizations across different types, with the ability to customize graphical objects and propagate changes back to the source data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual updating of visualizations is used when source data changes, then the visualization can be updated to reflect the latest data, but the process becomes time-consuming and tedious when the visualization includes many nodes
Solution Approach 1:
The system enables self-service automation where the visualization automatically updates itself when source data changes. The event subscription mechanism detects data changes and triggers automatic regeneration of the visualization without requiring manual intervention, thus maintaining data accuracy while eliminating time-consuming manual updates.
Solution Approach 2:
The system performs preliminary actions by establishing event subscriptions and data binding relationships in advance. When source data changes, the pre-configured event handlers automatically detect the changes and trigger the appropriate update actions, eliminating the need for manual intervention and reducing update time significantly.
2Reliability
If manual generation of visualization from scratch is performed when source data is updated, then the visualization reflects the latest data structure, but the process is bothersome and time-consuming
Solution Approach 1:
The system enables self-service automation where the visualization automatically updates itself when source data changes. The event subscription mechanism detects data changes and triggers automatic regeneration of the visualization without requiring manual intervention, thus maintaining data accuracy while eliminating time-consuming manual updates.
Solution Approach 2:
The system implements feedback mechanisms where the visualization continuously monitors source data for changes. When changes are detected, the system automatically triggers update processes and notifies users of the changes, creating a closed-loop system that maintains data consistency without manual intervention.
3Ease of manufacture
If fixed visualization templates are used, then the visualization structure is standardized, but the system lacks flexibility in handling different data formats and user customization needs
Solution Approach 1:
The system implements universal data binding mechanisms that can handle multiple data formats and sources through a common event subscription interface. The event-driven architecture allows the same visualization framework to adapt to different data types (JSON, CSV, database queries) and sources (APIs, files, databases) without requiring format-specific templates, thus maintaining standardization while achieving versatility.
Solution Approach 2:
The system transitions from static templates to dynamic data binding where visualization structures adapt automatically based on the source data format and user requirements. The event-driven architecture allows real-time adjustments to visualization parameters, enabling the system to maintain standardized processes while accommodating diverse data formats and customization needs.
Data Source
AI summary
A method may include receiving input effective to select a visualization type of multiple different visualization types to apply to a visualization of data. The selected visualization type may be associated with a contract. Each of the different visualization types may be associated with a specific contract. Each contract may include a corresponding schema that specifies a set of data fields and one or more relationships between data fields in the set to generate and display a corresponding visualization having a visualization type. The method may include mapping at least some data of a data source to the contract such that the contract is satisfied. The contract may specify that the data of the data source be in a graph format. The method may include displaying the visualization of the at least some data of the data source based on the contract, the displayed visualization having the selected visualization type.