INDEXING.md

Legal Data Indexing

The DataHive Legal Data Indexing system is a core component of the LN1 node that processes, categorizes, and indexes legal documents for the decentralized legal intelligence network.

Key Components

Document Processing

• Raw document ingestion
• Text extraction and normalization
• Metadata generation
• Format standardization

Classification Engine

• Legal document type detection
• Jurisdiction identification
• Subject matter categorization
• Precedent relationship mapping

Index Structure

class LegalIndex:
    def __init__(self):
        self.document_store = DocumentStore()
        self.metadata_index = MetadataIndex()
        self.citation_graph = CitationGraph()

    async def process_document(self, document):
        metadata = self.extract_metadata(document)
        citations = self.extract_citations(document)
        return await self.store(document, metadata, citations)

Indexing Pipeline

Document Collection

• API-based document submission
• Batch processing capabilities
• Version control tracking
• Source verification

Processing Steps

• Document validation
• Content extraction
• Language detection
• Structure analysis

Metadata Generation

• Document attributes
• Legal classifications
• Temporal information
• Jurisdictional data

Integration Points

Network Interface

• Cross-node synchronization
• Distributed index updates
• Consensus validation
• Version management

Storage Layer

• Integration with 0G AIOS
• Distributed storage protocol
• Content-addressable system
• Redundancy management

Search Capabilities

Query Processing

• Legal term recognition
• Context-aware search
• Precedent matching
• Cross-reference resolution

Results Ranking

• Relevance scoring
• Authority weighting
• Temporal factors
• Jurisdictional priority

Note: This documentation is subject to updates as the indexing system evolves.