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Structured data tech spec emerging

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docs/tech-specs/STRUCTURED_DATA.md
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@ -11,11 +11,30 @@ This specification describes the integration of TrustGraph with structured data
## Goals
[List the primary goals and objectives]
- **Unified Data Access**: Provide a single interface for accessing both structured and unstructured data within TrustGraph
- **Seamless Integration**: Enable smooth interoperability between TrustGraph's graph-based knowledge representation and traditional structured data formats
- **Flexible Extraction**: Support automatic extraction of structured data from various unstructured sources (documents, text, etc.)
- **Query Versatility**: Allow users to query data using both natural language and structured query languages
- **Data Consistency**: Maintain data integrity and consistency across different data representations
- **Performance Optimization**: Ensure efficient storage and retrieval of structured data at scale
- **Schema Flexibility**: Support both schema-on-write and schema-on-read approaches to accommodate diverse data sources
- **Backwards Compatibility**: Preserve existing TrustGraph functionality while adding structured data capabilities
## Background
[Context and motivation for this specification]
TrustGraph currently excels at processing unstructured data and building knowledge graphs from diverse sources. However, many enterprise use cases involve data that is inherently structured - customer records, transaction logs, inventory databases, and other tabular datasets. These structured datasets often need to be analyzed alongside unstructured content to provide comprehensive insights.
Current limitations include:
- No native support for ingesting pre-structured data formats (CSV, JSON arrays, database exports)
- Inability to preserve the inherent structure when extracting tabular data from documents
- Lack of efficient querying mechanisms for structured data patterns
- Missing bridge between SQL-like queries and TrustGraph's graph queries
This specification addresses these gaps by introducing a structured data layer that complements TrustGraph's existing capabilities. By supporting structured data natively, TrustGraph can:
- Serve as a unified platform for both structured and unstructured data analysis
- Enable hybrid queries that span both graph relationships and tabular data
- Provide familiar interfaces for users accustomed to working with structured data
- Unlock new use cases in data integration and business intelligence
## Technical Design