Extensible Item Attribute Model for Business Data Ontology
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Solution Overview
Problem
Business applications such as e-commerce and CRM systems face challenges in managing and validating additional attributes for items beyond their primary attributes, requiring a solution that allows for extensible and searchable item attributes while maintaining data integrity and ontology alignment.
Innovation Solution
The implementation of an extensible item attribute system within a business application data model, where additional attributes can be added with meta attributes for validation and searching, using a data model manipulator to extend item attributes, validate data values, and move items within the model, ensuring data consistency and searchability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If additional attributes are added to items in business applications, then the versatility and functionality of the system is improved, but the complexity of data management and validation increases
Solution Approach 1:
The patent segments attribute management into distinct categories: primary attributes (inherent to item types) and secondary attributes (custom, item-specific). This segmentation allows the system to handle diverse attribute types through a unified framework, improving versatility while maintaining manageable complexity through structured organization.
Solution Approach 2:
The patent introduces an intermediary layer of attribute metadata that mediates between the item data and the validation/search mechanisms. This metadata layer includes properties like data type, validation rules, and searchability flags, which simplify the management of additional attributes by providing a standardized interface for handling them.
2Reliability
If extended item attributes are added with validation rules, then data integrity is improved, but the operational complexity and processing time increases
Solution Approach 1:
The patent applies preliminary action by defining validation rules and metadata properties in advance before data entry. Validation constraints such as data types, required fields, and value ranges are pre-established in the attribute metadata, enabling automatic validation during data entry without requiring complex runtime processing logic.
Solution Approach 2:
The system performs self-service validation where the attribute metadata automatically enforces validation rules without requiring manual intervention. The validation mechanism leverages the pre-defined metadata properties to automatically check data integrity, reducing operational complexity by eliminating the need for complex validation programming.
3Adaptability or versatility
If attributes are made searchable with metadata, then the functionality and query capability is improved, but the data model complexity increases
Solution Approach 1:
The patent implements universality by making the attribute metadata structure multi-functional: it simultaneously defines data types, validation rules, searchability flags, and display properties. This unified metadata approach enables search functionality across extended attributes without requiring separate search infrastructure, thereby improving search capability while minimizing data model complexity.
Data Source
AI summary
In a method for extension of an item attribute in a business application data model, a selection is received of an item of the business application data model to which an item attribute is being added. The item attribute is received, including receipt of relationship information which defines a location of the item attribute within a hierarchy of the business application data model. The item attribute is associated with the business application data model such that the item attribute is contextually included within a searchable ontology of the hierarchy in accordance with the relationship information.