Graph Database Metamodel for Cross-Domain Data Organization
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Solution Overview
Problem
Current enterprise technologies lack a formally documented meta-model that streamlines workflows, improves communication, and provides standardized access to data, resulting in disorganized enterprise information.
Innovation Solution
A system and method for categorizing data domains based on logical groupings and data velocities, using a graph database with nodes and edges to represent data objects and relationships, and applying a metamodel to analyze and organize architectural information across multiple domains.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Stability of the object's composition
If data is stored in traditional enterprise technology systems without a standardized meta-model, then data can be stored in existing systems, but data organization becomes disorganized and relationships between different types of information cannot be established
Solution Approach 1:
The patent segments data into distinct domains (technology, business, strategy) with standardized meta-models for each domain. This segmentation allows data to be organized systematically while maintaining the ability to establish relationships across domains through the graph database structure, resolving the contradiction between stable organization and adaptability.
Solution Approach 2:
The patent introduces a graph database as an intermediary layer between traditional enterprise systems and analytical applications. This intermediary standardizes data organization through meta-models while enabling flexible relationships between different information types, thus resolving the contradiction between structured storage and adaptive querying.
2Ease of operation
If data domains are distributed between multiple applications without standardization, then data can be accessed by relevant applications, but data organization becomes inconsistent and relationships between data elements are lost
Solution Approach 1:
The patent creates a universal graph database structure that serves multiple applications simultaneously. The standardized meta-models and domain definitions provide a common framework that maintains data organization consistency while allowing different applications to access and query data according to their specific needs, resolving the contradiction between ease of access and organizational consistency.
3Ease of manufacture
If no formal meta-model is implemented, then system implementation is simpler, but workflows cannot be streamlined and communication between different information systems is impaired
Solution Approach 1:
The patent applies preliminary action by establishing standardized meta-models and domain definitions before data integration and analysis. This upfront standardization enables streamlined workflows and improved communication in subsequent operations, resolving the contradiction between initial implementation complexity and long-term productivity.
Data Source
AI summary
A system for categorizing data in or more domains for storage in a database. The system may include at least one processor; and at least one memory configured to execute the instructions to perform operations. The operations may include receiving the one or more data domains from a source system, wherein each of the one or more data domains is configured to be distributed between one or more applications and each of the data domains is categorized according to a logical grouping of the data domains based on instruments within the source system for storage within the database; store the categorized data for each of the or more data domains within the database; and further categorize each of the one or more data domains as having a data velocity selected from a range of data velocities, each representative of a frequency with which data of the data domain changes.