From 694f74e85da3f29026cae0bd6d43d92477deb361 Mon Sep 17 00:00:00 2001 From: Cyber MacGeddon Date: Mon, 4 Aug 2025 16:56:43 +0100 Subject: [PATCH] Structured data tech spec emerging --- docs/tech-specs/STRUCTURED_DATA.md | 23 +++++++++++++++++++++-- 1 file changed, 21 insertions(+), 2 deletions(-) diff --git a/docs/tech-specs/STRUCTURED_DATA.md b/docs/tech-specs/STRUCTURED_DATA.md index c36221ee..cca449fa 100644 --- a/docs/tech-specs/STRUCTURED_DATA.md +++ b/docs/tech-specs/STRUCTURED_DATA.md @@ -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