Hierarchical Data Model Versioning via Action Queues
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Solution Overview
Problem
Large hierarchical data models, such as organizational charts for companies with hundreds of thousands or millions of employees, require significant computational resources to create and modify, making experimental reorganization impractical due to memory and processing constraints.
Innovation Solution
A system that stores changes as an action queue, allowing for efficient creation, display, and storage of experimental versions without duplicating the entire data model, and validates actions to ensure accuracy and prevent cascading errors when applying changes to the original chart.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a full copy of the organizational chart is made for experimentation, then the ability to visualize and experiment with reorganization changes is improved, but the computational resources (memory and processing) required become prohibitively large
Solution Approach 1:
The patent segments the organizational chart into a base version and separate versioning layers (action queues, diff sets). Instead of copying the entire hierarchy, only the changes are stored as segmented units that can be applied to the base version to create experimental versions on demand.
Solution Approach 2:
The patent uses a selective copying approach where only the differences (diff sets) between versions are stored rather than copying entire organizational charts. This allows multiple experimental versions to be created from a single base version with minimal memory overhead.
2Adaptability or versatility
If multiple copies of the organizational chart are created to try different changes, then the ability to test multiple reorganization scenarios is improved, but the memory consumption becomes computationally intractable
Solution Approach 1:
The patent merges multiple versioning operations into a single base version with layered diff sets. Multiple experimental scenarios share the same base version and store only their unique changes, combining storage efficiency with the ability to test multiple scenarios independently.
Solution Approach 2:
The patent applies partial action by storing only the necessary changes (diff sets) rather than complete copies. This allows multiple versions to be maintained with minimal memory overhead by storing only the excess information needed to differentiate them from the base version.
3Reliability
If the organizational chart is stored in a normalized database format, then data consistency and validation are improved, but the ease of rendering and displaying the chart deteriorates
Solution Approach 1:
The patent performs preliminary action by pre-computing and caching the rendered representation of the organizational chart in the normalized database. This allows the normalized data to be stored once and then efficiently rendered multiple times without repeated complex processing, bridging the gap between data consistency and rendering ease.
Data Source
AI summary
A system includes an interface and a processor. The interface is configured to receive an indication to render a proposed organization chart. The processor is configured to determine a net action queue for the proposed organization chart. Determining the net action queue includes scanning an action queue to consolidate actions for the net action queue, apply the net action queue to an original organization chart to obtain the proposed organization. The processor is further configured to chart and render the proposed organization chart.