Dynamic Entity Relationship Model for Organizational Data
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Solution Overview
Problem
Current information organization methods and data models in computer systems do not provide a holistic view of interdependencies among organization units, leading to a lack of understanding of how individual work efforts contribute to organizational goals and requiring excessive time and resources for implementation.
Innovation Solution
A method and apparatus that model multiple relationship dimensions among entities by identifying metadata about supported relationship aspects, comparing entity aspects to a configuration, and dynamically attaching entities to form a structure, enabling a more efficient display of relationships within a computer system.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If current information organization methods and data models are used to store information about organization units, then information can be stored in databases, but a holistic view of interdependencies among organization units is not provided and individual employees lack understanding of how their work impacts others
Solution Approach 1:
The patent segments the organization into discrete entities (employees, teams, departments, projects) and models their relationships through a hierarchical structure. Each entity is represented as a separate object with defined attributes and relationships to other entities, allowing interdependencies to be captured without requiring a monolithic complex data model. The relationship model breaks down the organization into manageable components that can be individually configured and linked.
Solution Approach 2:
The patent introduces a new dimensional layer for representing organizational relationships by creating a multi-level hierarchical structure that goes beyond traditional flat database schemas. It adds dimensions such as reporting relationships, project assignments, team memberships, and operational dependencies, allowing interdependencies to be visualized and analyzed from multiple perspectives simultaneously.
2Loss of information
If current information organization methods are implemented to show interdependencies among organization units, then relationship information can be displayed, but excessive time and computational resources are required
Solution Approach 1:
The patent performs preliminary configuration by pre-defining relationship templates, entity types, and association rules before actual organizational data is populated. The system pre-establishes the hierarchical structure framework, relationship categories, and metadata schemas, so that when organizational entities are added, their relationships can be automatically inferred or quickly configured based on the pre-set templates, significantly reducing implementation time.
Solution Approach 2:
The patent uses template copying mechanisms where standard organizational structures (such as typical reporting hierarchies, common team configurations, or standard project relationships) can be copied and adapted. Instead of manually configuring each relationship from scratch, administrators can replicate proven relationship patterns across similar organizational units, dramatically reducing the time and resources needed to model interdependencies.
3Loss of information
If detailed relationship structures are modeled to show how individual work efforts contribute to organizational goals, then employee understanding of interdependencies improves, but the data model becomes bloated and requires significant computational resources
Solution Approach 1:
The patent applies local quality by allowing different levels of relationship detail and complexity at different hierarchical levels of the organization. Individual employee records can have detailed relationship information (projects, teams, reporting lines), while higher-level organizational units can have aggregated or summarized relationship views. The system dynamically adjusts the granularity of relationship data based on the specific context and user needs, avoiding uniform complexity throughout the entire data model.
Solution Approach 2:
The patent implements partial relationship modeling by capturing only the most significant and relevant interdependencies rather than attempting to model every possible relationship between all entities. The system identifies and models key relationship types (such as direct reporting, project assignments, and team memberships) that have the greatest impact on understanding organizational contributions, while less critical relationships can be inferred or omitted, reducing data model bloat while maintaining sufficient detail for understanding work contributions.
Data Source
AI summary
A method and apparatus model multiple relationship dimensions among a set of entities is presented. A computer system identifies a configuration for the structure. The configuration comprises metadata about supported relationship aspects for the set of entities within a structure context. The computer system identifies aspects for an entity according to the structure context. The entity aspects comprise metadata about relationships for the entity within the structure context. The computer system compares the entity aspects to the configuration for the structure to determine a relationship of the entity to the set of entities. The computer system dynamically attaches the entity to the set of entities according to the determined relationship to form the structure.