Context Tree Abstraction for Data Model Access
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Solution Overview
Problem
In existing systems, consumers of data models need to be aware of all aspects and contexts of how data models are used, and both builders and runtime consumers must understand how to construct or interpret data interchange schemas, making it complex to access and validate data values.
Innovation Solution
A system comprising an interface, processor, and memory that uses a context tree locator to receive data model entry points and context filters, determining context tree data from context tree providers, allowing for a tailored context tree abstraction that enables clients to access appropriate data without needing to know how values are retrieved, while maintaining validation framework integrity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If consumers directly access data model aspects and manifestations, then data access completeness is improved, but system complexity increases
Solution Approach 1:
The patent introduces a context tree as an intermediary layer between consumers and the data model. The context tree provider receives requests from consumers and translates them into appropriate data model queries, while the context tree locator manages the mapping between context trees and data models. This mediator approach allows consumers to access complete data model information without directly dealing with the complexity of data model construction and interpretation.
2Manufacturing precision
If builders and runtime consumers understand data interchange schemas, then data model accuracy is improved, but operational complexity increases
Solution Approach 1:
The context tree provider is configured with the capability to automatically construct and interpret data interchange schemas without requiring manual intervention from builders or runtime consumers. The system performs self-service by automatically mapping context tree nodes to data model elements, generating appropriate queries, and retrieving data values, thereby maintaining data model accuracy while eliminating the need for users to understand complex schema construction.
3Measurement precision
If runtime consumers know how to find data values, then data retrieval accuracy is improved, but accessibility decreases
Solution Approach 1:
The patent segments the data retrieval process into distinct functional components: the context tree locator handles mapping and routing, the context tree provider handles query construction and data retrieval, and the data model serves as the structured storage. This segmentation allows each component to specialize in its function, ensuring data retrieval accuracy while making the overall system more accessible to consumers who only need to interact with the simplified context tree interface.
Data Source
AI summary
A system for providing context tree based on data model is disclosed. The system comprises an interface, a processor, and a memory. The interface is configured to receive a data model entry point, and to receive one or more context filters. The processor is configured to determine context tree data based on the one or more context filters and the data model entry point from any context tree provider that has appropriate context tree information. The memory is coupled to the processor and is configured to provide the processor with instructions.