XML Schema Content Indexing for WinFS Data Retrieval
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Solution Overview
Problem
Current storage systems, such as WinFS, face challenges in efficiently indexing and searching rich structured data due to limitations in content indexing, which hampers data aggregation and sharing across multiple applications.
Innovation Solution
A method and system for defining content-indexable data using a schema with XML-based type definitions, generating query language statements for content index data extraction, and storing these statements in a file system, enabling effective indexing and search capabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Difficulty of detecting and measuring
If content indexing is implemented for rich structured data in WinFS, then data search and aggregation capabilities are improved, but the complexity of defining and processing content-indexable data increases
Solution Approach 1:
The patent introduces an intermediary system consisting of schema definitions and query language statements that mediate between the rich structured data and the content indexing mechanism. This intermediary layer translates complex structured data into indexable formats without requiring changes to the underlying data storage or retrieval mechanisms, thereby improving search capability while managing system complexity through abstraction.
Solution Approach 2:
The patent segments the content indexing process into distinct components: schema definitions that identify indexable properties, query language statements that extract index data, and separate indexing mechanisms that process the extracted data. This segmentation allows each component to be developed and optimized independently, improving overall search capability while distributing system complexity across multiple manageable modules.
2Productivity
If schema-based content index definitions are used, then data extraction and indexing efficiency is improved, but the difficulty of schema design and annotation increases
Solution Approach 1:
The patent creates a universal schema definition framework using XML-based type definitions that can be applied to various rich structured data formats. This universal approach enables consistent data extraction across different data types through standardized annotation mechanisms, improving extraction efficiency while reducing schema design difficulty through reuse of common patterns and structures.
Solution Approach 2:
The patent implements preliminary action by requiring schema definitions and content index annotations to be established before actual data indexing occurs. This upfront preparation, while adding initial design effort, enables automated and efficient data extraction during runtime, significantly improving productivity for large-scale data indexing operations.
3Measurement precision
If query language statements are generated and stored for content index extraction, then data retrieval accuracy is improved, but the storage and processing overhead increases
Solution Approach 1:
The patent uses copying by storing query language statements as separate, reusable templates rather than embedding extraction logic directly in the data or indexing process. These statement copies can be efficiently stored, cached, and executed multiple times without duplicating the actual data, thereby maintaining high retrieval accuracy while minimizing storage overhead through template reuse.
Data Source
AI summary
An XML based type-definition language for declaring content-index for WinFS Types is provided. Content-index declarations can be specified for the Item type as well as it's sub-entities like Fragments, etc across Item type hierarchies. The properties of WinFS types in the schema are marked for content-indexing by the schema designer. Installing the content-index definitions includes parsing content-index definitions in the schema, generation of appropriate SQL statements for data extraction and storing the SQL statements.