Visualization State Management Across Data Transitions
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing data analysis techniques are limited by their inability to efficiently analyze and collaborate on multiple disparate data sources, requiring a scalable approach that supports collaboration among end users.
Innovation Solution
A server-based system with a data processing module that maintains annotations for visualizations, utilizing visualization configuration parameters to link and harmonize data from various sources, enabling context-aware data analysis and collaboration through a data ingest module, story control module, and collaboration module.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If discrete data sources are analyzed separately, then analysis simplicity is maintained, but collaboration efficiency and scalability deteriorate
Solution Approach 1:
The system segments the complex task of multi-source data analysis into independent modular components: data ingest modules for individual sources, story control modules for analysis workflows, and collaboration modules for user interaction. Each module operates independently but contributes to the overall collaborative analysis, enabling scalability without proportionally increasing system complexity.
Solution Approach 2:
The patent implements universal story control modules and collaboration modules that can handle multiple different data sources and analysis types through standardized interfaces. These modules perform multiple functions including data ingestion, processing, visualization control, and user collaboration across various data sources, reducing the need for separate specialized components for each data source.
2Adaptability or versatility
If multiple data sources are integrated, then analysis comprehensiveness improves, but data harmonization complexity increases
Solution Approach 1:
The system standardizes data from different sources by transforming and normalizing various data parameters into a common format. The data ingest modules and story control modules apply parameter transformations to harmonize disparate data structures, schemas, and formats, enabling seamless integration of multiple data sources without requiring complex custom integration logic for each source.
Solution Approach 2:
The story control modules act as intermediaries between diverse data sources and the collaboration functionality. These modules mediate the integration process by receiving data from multiple sources, applying harmonization rules, and presenting unified results to users, thereby simplifying the complexity of direct multi-source integration.
3Loss of information
If visualization state is maintained across transitions, then user context awareness improves, but state management complexity increases
Solution Approach 1:
The system uses story templates as reusable copies of analysis configurations and state definitions. When users create or load stories, the state of visualizations, data selections, and analysis parameters are captured as template instances. This copying mechanism allows state to be preserved and restored across visualization transitions without requiring complex real-time state synchronization, as each story instance carries its own state definition.
Solution Approach 2:
The story control modules pre-define and pre-configure the state of visualizations and analysis parameters through templates before actual data analysis occurs. By establishing state definitions in advance through story templates, the system eliminates the need for complex runtime state management, as the state configuration is already determined and stored in the template structure.
Data Source
AI summary
A server has a data processing module with instructions executed by a processor to maintain an annotation of a first visualization of data, where the first visualization of data has visualization configuration parameters. The annotation is linked to a second visualization of the data that utilizes the visualization configuration parameters.