Entity-Relationship Schema Navigation for Direct Chart Generation
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Solution Overview
Problem
Existing systems for generating visualizations from entity-relationship databases are cumbersome as they require converting structured data into tabular form before creating charts, making it difficult for users to discern business knowledge, especially in large databases.
Innovation Solution
The ReadiNow Engine Intelligence (REI) system provides a user interface and method for directly selecting and navigating entity-relationship schemas to generate charts without intermediate tabular conversion, allowing users to select entity types, relationship paths, and bindable data targets for chart creation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If data is converted from entity-relationship database format to tabular form before generating charts, then chart generation can be performed using existing systems, but the process becomes cumbersome and difficult to use
Solution Approach 1:
The patent extracts the tabular conversion step from the chart generation process, allowing users to generate charts directly from entity-relationship database schemas without converting to tabular form first. The system takes out the intermediate conversion layer and enables direct access to ER data for visualization.
Solution Approach 2:
The patent introduces a new intermediary component - a chart generation system that can directly interpret entity-relationship schemas. This mediator translates ER model elements (entities, attributes, relationships) directly into chart components, eliminating the need for tabular conversion while maintaining compatibility with existing charting capabilities.
2Loss of information
If existing systems are used to generate charts from entity-relationship databases, then chart generation is possible, but users cannot easily discern business knowledge from large databases
Solution Approach 1:
The patent segments the entity-relationship schema into navigable components (entities, attributes, relationships) that can be explored hierarchically. Users can traverse relationship paths from selected entities to discover business knowledge embedded in the data structure, making large databases more understandable through structured navigation.
Solution Approach 2:
The system performs preliminary actions by automatically generating relevant charts and visualizations based on the entity-relationship schema without requiring manual data extraction or conversion. The system pre-processes the ER model to identify meaningful relationships and patterns, presenting business knowledge in an accessible format before the user even requests specific analyses.
3Ease of operation
If a simple entity-relationship database structure is used, then data presentation is simple, but it is difficult to discern business knowledge, especially in very large databases
Solution Approach 1:
The patent adds a new dimension to data presentation by introducing visual navigation through relationship paths and hierarchical exploration of entity schemas. Instead of flat tabular views, users can traverse multi-dimensional relationships in the ER model, exploring business knowledge through navigational paths that reveal connections across large datasets while maintaining the simplicity of the underlying ER structure.
Data Source
AI summary
A user interface for allowing a user to create a chart, the user interface comprising: an entity type selection area for allowing a user to select a type of entity; an explorer for displaying an entity-relationship schema associated with the selected entity type and allowing a user to navigate the schema via one or more relationship paths; a list area for displaying one or more available fields of an entity associated with a relationship path selected from the explorer; and a target area for displaying a list of bindable data targets and allowing a user to assign one or more of the available fields to the bindable data targets to create a chart.