Data Versioning Through Transformations
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Solution Overview
Problem
Long-term data storage in databases faces challenges as data formats and schemas evolve over time, leading to incompatibility issues between different applications and versions, making it difficult to maintain accessibility of data across varying technologies and applications.
Innovation Solution
Implementing data transformation mechanisms that match data versions to the format specified in a registration between the database provider and the requesting application, using XML schemas to define data structures and enable transformations between different schema versions, ensuring compatibility and accessibility regardless of the original or new schema versions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data is stored using a particular format or schema corresponding to a particular application, then the data can be accessed and read by that application, but over time the data may not be accessible by currently available applications or backward compatible with existing applications due to format changes
Solution Approach 1:
The patent introduces an intermediary data transformation layer that converts data between different schema versions. When an application requests data, the system automatically transforms the stored data into the format expected by that application using registration information that maps between schemas. This mediator approach resolves the contradiction by maintaining data accessibility (reliability) while supporting multiple schema versions (adaptability).
Solution Approach 2:
The patent employs parameter changes by storing data in multiple schema versions simultaneously and dynamically selecting which version to return based on the requesting application's registered schema. The system changes the format parameters of the data on-the-fly during retrieval, allowing the same underlying data to be presented in different formats to maintain both accessibility and compatibility across evolving applications.
2Productivity
If data formats and schemas evolve over time to incorporate new technologies and data elements, then new applications can access and utilize new data elements, but existing applications may fail or become incompatible with the updated data formats
Solution Approach 1:
The patent applies preliminary action by pre-defining registration information that maps between different schema versions before data transformation is needed. The system registers multiple schema versions and their relationships in advance, so when data needs to be transformed, the conversion path is already established. This allows new data elements and formats to be incorporated (improving productivity) while maintaining compatibility with existing applications through pre-planned transformation rules.
Solution Approach 2:
The patent creates a universal data access interface that can handle multiple schema versions through a single registration-based transformation mechanism. The system stores data in multiple formats and uses registration information to universally serve any application regardless of which schema version it expects. This multi-functional approach allows the system to support both new applications utilizing new data elements and existing applications requiring older formats, resolving the contradiction between data utility and application compatibility.
3Duration of action of stationary object
If data is maintained in a complete and accessible form despite changes in computer programs and equipment, then long-term data accessibility is ensured, but data transformation and version management complexity increases
Solution Approach 1:
The patent extracts the complexity of schema management into a separate registration system that is independent from the core data storage and retrieval operations. By taking out the schema versioning and transformation logic into a dedicated registration layer, the system can maintain data in multiple formats over long periods (increasing duration) without embedding transformation complexity throughout the entire data management system. The registration module serves as a centralized complexity management point.
Solution Approach 2:
The patent segments the data storage system into distinct layers: the core data storage layer that maintains data in various schema versions, and a transformation layer that handles format conversion based on registration information. This segmentation allows the system to retain data indefinitely in complete forms (long-term retention) while isolating the transformation complexity to a specific module, reducing the overall system complexity burden.
Data Source
AI summary
In response to receiving a request for data stored according to a first version of a data type, a second version of the data type supported by the requester is determined, and the requested data is transformed from the first version to the second version to provide access to the data.