Graphical Model Comprehensibility Scoring via Hierarchical Segmentation
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Solution Overview
Problem
Complex graphical models in graphical modeling environments become difficult to understand, maintain, and share as their complexity increases, leading to errors and inefficiencies in collaboration and representation.
Innovation Solution
A method to quantify the comprehensibility of graphical models by calculating their concrete and abstract complexities using metrics and cost functions, which allows for the comparison and recommendation of more comprehensible representations, and provides visual cues to communicate comprehensibility scores.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If graphical models become more complex to represent sophisticated systems, then the system's representational capability is improved, but the model's comprehensibility and ease of maintenance deteriorate
Solution Approach 1:
The patent applies segmentation by dividing complex graphical models into hierarchical levels (e.g., system level, subsystem level, component level). This allows sophisticated systems to be represented through multiple layers of abstraction, where each level maintains comprehensibility while collectively representing complex functionality. The segmentation enables users to navigate and understand models by focusing on relevant levels rather than being overwhelmed by complete system complexity.
Solution Approach 2:
The patent introduces an additional dimension of abstraction by implementing hierarchical levels beyond the traditional single-plane graphical representation. This dimensional change allows the model to organize elements vertically across multiple levels while maintaining horizontal relationships within each level, thereby preserving comprehensibility at each level while representing complex cross-level relationships.
2Measurement precision
If graphical models include more elements and relationships to capture system complexity, then the model's accuracy is improved, but the model's complexity and difficulty of understanding increase
Solution Approach 1:
The patent segments the model elements and relationships into hierarchical categories, organizing them by level and type. This segmentation allows accurate representation of complex relationships while managing complexity through structured organization. Each segment maintains necessary detail for accuracy while the hierarchical structure prevents overwhelming complexity by allowing selective viewing of relevant portions.
Solution Approach 2:
The patent applies local quality by allowing different levels of the hierarchical model to have different densities and types of relationships. Critical relationships receive detailed representation at appropriate levels, while less critical areas use simplified representations. This ensures model accuracy where needed while reducing unnecessary complexity in other areas.
3Manufacturing precision
If graphical models are highly detailed to ensure accurate representation, then the representation quality is improved, but the time required to create and maintain the model increases
Solution Approach 1:
The patent implements preliminary action by pre-defining hierarchical structures, relationship types, and representation templates at higher levels. This preliminary organization allows detailed representations to be generated systematically rather than created from scratch, reducing the time required to achieve high representation quality. The pre-established framework guides the creation process and ensures consistency across detailed representations.
Solution Approach 2:
The patent applies the nesting principle by creating hierarchical levels where higher-level models contain references to lower-level detailed models. This nested structure allows detailed representations to be maintained in separate, manageable units that can be independently created and maintained, then integrated into the overall model. This reduces total creation and maintenance time by allowing parallel development of different hierarchical levels.
4Adaptability or versatility
If graphical models represent complex systems with many components, then the system's functionality is captured more completely, but collaboration and sharing become more difficult
Solution Approach 1:
The patent segments the graphical model into hierarchical levels and modular components that can be independently viewed and edited by different collaborators. This segmentation allows team members to focus on specific levels or subsystems relevant to their expertise, making collaboration on complex systems more manageable. The hierarchical structure provides natural boundaries for dividing work while maintaining overall system coherence.
Solution Approach 2:
The patent implements universality by creating a hierarchical modeling framework that serves multiple functions: it enables detailed system representation, facilitates collaboration through manageable segments, supports various viewing levels, and maintains consistency across the model. This multi-functional framework addresses multiple collaboration needs simultaneously, improving ease of operation while maintaining complete functionality coverage.
Data Source
AI summary
In an embodiment, degree of comprehensibility of a graphical representation of a model is identified. The model is provided in a graphical modeling environment. The degree of comprehensibility of the graphical representation of model is identified based at least in part on one or more visual characteristics of one or more elements in the model. The one or more elements in the model include at least one of entities in the model, or relationships in the model. The degree of comprehensibility assigned to the model is communicated, for example, to a user.