Data-Bound Graphic Objects for Dynamic Visualization Patterns
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Solution Overview
Problem
Traditional methods for creating data visualizations, such as using templates, manual drawing, or coding, are limited in flexibility, accuracy, and ease of use, particularly for designers without programming expertise, as they often require rigid templates, slow manual adjustments, or complex coding.
Innovation Solution
The development of a system that allows graphic objects to be bound to data variables, enabling visual properties like position, size, or color to be automatically updated based on data changes, facilitating the creation of data-driven designs with greater flexibility and accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If template tools are used to create data visualizations, then the process is simplified and faster, but the flexibility for creative expression is reduced
Solution Approach 1:
The system dynamically adapts between template-based and custom-based creation modes. Users can start with a template and progressively customize it by binding data variables to visual properties, allowing the visualization to evolve from a rigid template to a flexible, data-driven design without starting over.
Solution Approach 2:
The system serves multiple functions: it provides pre-built templates for quick visualization creation, enables data binding to customize visual properties, and allows manual adjustment of individual objects. This multi-functionality resolves the contradiction by accommodating both template users and custom designers in a single platform.
2Adaptability or versatility
If manual drawing is used to create data visualizations, then design flexibility is maximized, but the process becomes slow and potentially inaccurate
Solution Approach 1:
The system performs preliminary actions by providing pre-configured templates with established visual structures, data bindings, and styling. Users can leverage these pre-prepared elements to avoid building visualizations from scratch, thus maintaining flexibility while significantly reducing creation time and potential errors.
Solution Approach 2:
Users can copy and reuse visual objects, data bindings, and design patterns from templates or existing visualizations. This copying mechanism allows rapid prototyping and iteration while maintaining design consistency, bridging the gap between manual customization and template efficiency.
3Adaptability or versatility
If coding is used to build data visualizations, then customization flexibility is achieved, but the difficulty increases for designers without programming expertise
Solution Approach 1:
The system introduces a visual programming intermediary layer that sits between traditional coding and manual design. Users interact with drag-and-drop interfaces, property binders, and visual editors that translate design intentions into code behind the scenes, eliminating the need for direct programming while maintaining customization capabilities.
Solution Approach 2:
The system replaces the mechanical system of manual coding with automated code generation based on visual interactions. When users bind data variables to visual properties or adjust object properties through the interface, the system automatically generates and updates the underlying code, substituting complex coding mechanics with intuitive visual operations.
4Stability of the object's composition
If traditional visualization methods are used, then design integrity can be maintained, but the iterative workflow between data manipulation and visual design becomes complex
Solution Approach 1:
The system merges data manipulation and visual design into a unified workflow. Data bindings create direct links between data variables and visual properties, so that changes in either domain automatically propagate to the other. This integration eliminates the need for separate, iterative passes between data processing and visual design, reducing workflow complexity while maintaining design integrity.
Solution Approach 2:
The system implements continuous feedback loops where data changes automatically update visualizations and visual adjustments automatically update data bindings. This real-time feedback mechanism ensures design integrity is maintained throughout the iterative process without requiring manual synchronization or complex coordination between data and visual layers.
Data Source
AI summary
Computer-readable media, methods, and systems are provided for creating a display pattern for a plurality of graphic objects that are bound to at least one data variable. Data comprising a plurality of observations with variable values is received. A first graphic object is presented for display within a display area of a graphic user interface and is bound to the data such that the property value for one of the object's visual property is determined by a variable value a corresponding data observation. A direction of expansion for the display area is received, and as the display area is expanded, a plurality of additional graphic objects also bound to the data are created and presented with the first graphic object to form a display pattern. The display pattern is determined, in part, by the order of the corresponding observations in the data set and the selected direction of expansion.