Ontological Data Mapping for Cross-Platform Operations
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Solution Overview
Problem
Conventional data importation into platforms restricts operations to platform-specific operations, limiting flexibility and efficiency, particularly when transitioning between table-oriented and object-oriented platforms.
Innovation Solution
A system and method for mapping data based on an ontology of a platform, where data is organized and shaped to align with a target ontology, enabling operations on a table-oriented platform to represent and perform operations on object-oriented data structures, facilitating synchronization and efficient staging of changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If data is imported into a platform by applying the platform's ontology onto the data, then the data can be used by the platform, but the operations on the data are restricted to platform-oriented operations
Solution Approach 1:
The patent introduces an intermediary layer that maps between different ontologies. A source ontology represents the data structure of the source platform, while a target ontology represents the data structure of the destination platform. The mapping between these ontologies serves as an intermediary that enables data to be organized for use by a table-oriented platform while still being representable as object-oriented data structures, thus providing operational flexibility without requiring direct importation into the target platform.
Solution Approach 2:
The patent segments the data representation into multiple layers: source data, source ontology, target ontology, and mapped data structure. This segmentation allows the system to maintain the original data structure while creating platform-specific representations, enabling independent optimization for different platforms without compromising the other.
2Ease of operation
If data is imported into an object-oriented platform, then the data can be processed using object-oriented operations, but the computational intensity and complexity increase
Solution Approach 1:
The patent creates a representative copy of the object-oriented data structure using tabular data. Instead of actually importing and transforming complex object-oriented data into another platform, the system creates a simplified tabular representation that captures the essential structure and relationships. This copy can be processed using efficient tabular operations while still representing the original object-oriented data, thereby reducing computational intensity.
Solution Approach 2:
The patent uses simple, lightweight tabular data structures as temporary representations that can be easily created and processed. These tabular representations serve as disposable intermediaries that avoid the computational overhead of working with complex object-oriented structures, providing a cost-effective way to perform data operations without the full complexity of object-oriented processing.
3Productivity
If data is organized for use by a table-oriented platform, then tabular operations can be performed efficiently, but the data cannot directly represent object-oriented structures
Solution Approach 1:
The patent creates a universal data representation system where tabular data can serve multiple functions: it can be processed by table-oriented platforms for efficient tabular operations, while simultaneously representing object-oriented data structures through the mapping to target ontology. This multi-functionality allows the same tabular representation to support both efficient processing and cross-platform compatibility.
Solution Approach 2:
The patent adds an ontological dimension to the data representation by introducing source ontology and target ontology layers. This additional dimension allows tabular data to be interpreted in multiple ways: as simple tabular structures for efficient processing, and as representations of complex object-oriented relationships through the ontology mapping, thus enabling both efficiency and versatility.
Data Source
AI summary
Systems, methods, and non-transitory computer readable media are provided for mapping data based on an ontology of a platform. A data set may be obtained. Data within the data set may be for use by an operation platform based on an operation ontology. The operation ontology may define an operation data structure for the operation platform. The data may be shaped based on a target ontology. The target ontology may define a target data structure for a target platform. The data may be shaped such that the data is mapped to the target data structure.