Third-Party Data Embedding in Native Application Files
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Solution Overview
Problem
Existing methods for embedding and retrieving data in application file formats face challenges, particularly when dealing with large datasets and complex queries like OLAP, leading to distribution and synchronization issues, especially in collaboration projects, and require specialized skills to manage multi-dimensional objects.
Innovation Solution
The solution involves embedding third-party data in a native application file format using a data provider like OLEDB, allowing on-demand access and asynchronous loading, enabling users to interact with large datasets without needing to understand the data format or having specialized skills, and allowing seamless distribution and use of files without a network connection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If data is stored in an online database, then data accessibility is improved, but data availability offline deteriorates
Solution Approach 1:
The patent segments data into two parts: structured data stored in online databases and unstructured data embedded directly in application files. This allows the system to provide both online accessibility and offline availability by storing different types of data in different locations, resolving the contradiction between centralized data management and distributed access.
Solution Approach 2:
The patent embeds third-party data structures within native application file formats, creating a nested structure where external data is contained within the application's own file format. This nesting enables offline access to third-party data while maintaining the application's native file structure and compatibility.
2Quantity of substance
If large amounts of data are stored separately, then data storage capacity is improved, but distribution and synchronization issues worsen
Solution Approach 1:
The patent merges third-party data structures with native application file formats into a single integrated file. By combining what was previously separate (application data and third-party data) into one unified file structure, the system eliminates distribution and synchronization issues while maintaining large data storage capacity.
3Adaptability or versatility
If users create multi-dimensional objects, then data manipulation capability is improved, but user skill requirements worsen
Solution Approach 1:
The patent introduces an intermediary layer (the embedded data structure with connection information) that automatically handles the complexity of multi-dimensional data access. Users interact with simple embedded structures, while the system automatically manages the complex queries and data retrieval, reducing skill requirements while maintaining manipulation capability.
4Adaptability or versatility
If third-party data is embedded in application files, then data portability is improved, but application compatibility requirements worsen
Solution Approach 1:
The patent creates a universal embedded data structure that can be contained within native application file formats. This multi-functional approach allows the same embedding mechanism to work across different applications and data types, improving portability while managing compatibility through a standardized embedded structure.
Data Source
AI summary
Third party data embedding may be provided. Data associated with a third party provider may be saved in a native application save file. If a save file opened by the application is determined to comprise third party data, the application may determine whether an appropriate data provider is available. The application may connect to the data provider and provide on-demand, asynchronous access to the third party data upon request from a user.