Visualization UI Autowiring via Expression Language Metadata
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Solution Overview
Problem
Current web portal systems require extensive knowledge of data source attributes to wire UI components, making it difficult for non-technical users to create data visualizations, and increasing the time and effort needed to manage and update complex web content.
Innovation Solution
A system that generates a visualization user interface by parsing a visualization template with an expression language (EL) to create bindings between UI components and data sources, allowing users to select data sources and templates without needing to know the underlying data attributes, using an autowiring mechanism to automatically bind UI components to data sources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual wiring of UI components to data sources is used, then precise binding control is achieved, but extensive technical knowledge is required and operation becomes difficult
Solution Approach 1:
The system performs automatic wiring where the framework itself identifies and binds UI components to data sources without requiring manual intervention. The expression language metadata within templates enables the system to self-configure bindings by parsing template definitions and automatically establishing connections between components and data sources.
Solution Approach 2:
The binding configurations are pre-defined within the visualization templates through expression language metadata. This preliminary setup allows the system to automatically wire components during runtime without requiring users to perform complex binding operations at that stage.
2Ease of operation
If automatic template parsing is used, then ease of use for non-technical users is improved, but processing time increases
Solution Approach 1:
The expression language metadata and binding configurations are prepared in advance within the template definitions. This preliminary structuring allows the parsing operation to be more efficient during runtime, as the system only needs to interpret pre-structured metadata rather than perform complex analysis from scratch.
Data Source
AI summary
A system that generates a visualization user interface. The system receives a selection of a data source, and receives a selection of a visualization template that includes metadata. The system further receives a selection of data attributes corresponding to the data source. The system parses the visualization template for the metadata, and replaces the metadata with binding between a visualization component and the data source. The system then generates the visualization user interface using the visualization component.