Import from JSON

JSON File Structure

Basic JSON Format

Understand the JSON structures compatible with ResearchArcade:

{
  "papers": [
    {
      "paper_id": 1,
      "title": "Deep Learning Fundamentals",
      "authors": [
        {"name": "Smith, J.", "affiliation": "MIT"},
        {"name": "Jones, A.", "affiliation": "Stanford"}
      ],
      "year": 2023,
      "abstract": "This paper explores...",
      "citations": [2, 3, 5]
    },
    {
      "paper_id": 2,
      "title": "Graph Neural Networks",
      "authors": [
        {"name": "Brown, K.", "affiliation": "CMU"}
      ],
      "year": 2024,
      "abstract": "We present a novel...",
      "citations": [1]
    }
  ]
}

Nested vs Flat JSON

Work with both flat and deeply nested JSON structures:

# Code example placeholder
# Add your Python/API code here for handling nested structures

JSON Lines Format

Import newline-delimited JSON (JSONL/NDJSON) for streaming large datasets:

# Code example placeholder
# Add your Python/API code here for JSONL format

Importing Nodes from JSON

Basic Node Import

Load simple JSON objects as graph nodes:

# Code example placeholder
# Add your Python/API code here for basic node import

Mapping JSON Keys to Properties

Define how JSON fields correspond to node attributes:

# Code example placeholder
# Add your Python/API code here for property mapping

Handling Arrays of Objects

Import multiple entities from JSON arrays:

# Code example placeholder
# Add your Python/API code here for array processing

Handling Nested Structures

Creating Relationships from Nested Objects

Transform nested JSON into nodes and edges:

# Code example placeholder
# Add your Python/API code here for nested relationships

Flattening Hierarchies

Convert hierarchical JSON into graph structure:

# Code example placeholder
# Add your Python/API code here for flattening hierarchies

Preserving JSON Structure as Properties

Store complex nested data as node properties:

# Code example placeholder
# Add your Python/API code here for preserving structure

Importing Edges from JSON

Explicit Relationship Format

Import edges defined explicitly in JSON:

# Code example placeholder
# Add your Python/API code here for explicit edges

Implicit Relationships from References

Create edges from ID references in nested objects:

# Code example placeholder
# Add your Python/API code here for implicit relationships

Many-to-Many Relationships

Handle arrays of references for complex connections:

# Code example placeholder
# Add your Python/API code here for many-to-many relationships

Schema Validation

JSON Schema Validation

Validate JSON structure against a schema before import:

# Code example placeholder
# Add your Python/API code here for JSON schema validation

Custom Validation Rules

Implement domain-specific validation logic:

# Code example placeholder
# Add your Python/API code here for custom validation

Handling Invalid Data

Manage validation errors and malformed JSON:

# Code example placeholder
# Add your Python/API code here for handling invalid data

Data Transformation

Custom Field Transformations

Apply transformations during import:

# Code example placeholder
# Add your Python/API code here for field transformations

Type Coercion

Convert JSON types to appropriate database types:

# Code example placeholder
# Add your Python/API code here for type coercion

Computed Properties

Generate additional properties from JSON data:

# Code example placeholder
# Add your Python/API code here for computed properties

Advanced Import Features

Incremental Updates

Update existing nodes with new JSON data:

# Code example placeholder
# Add your Python/API code here for incremental updates

Conditional Import Logic

Apply conditional rules during import:

# Code example placeholder
# Add your Python/API code here for conditional import

Merging Multiple JSON Sources

Combine data from multiple JSON files:

# Code example placeholder
# Add your Python/API code here for merging sources

Performance Optimization

Streaming Large JSON Files

Process large files without loading entirely into memory:

# Code example placeholder
# Add your Python/API code here for streaming

Batch Processing

Import JSON records in optimized batches:

# Code example placeholder
# Add your Python/API code here for batch processing

Parallel Import

Use parallel processing for faster imports:

# Code example placeholder
# Add your Python/API code here for parallel import

Error Handling

Parse Errors

Handle malformed JSON gracefully:

# Code example placeholder
# Add your Python/API code here for parse error handling

Missing Required Fields

Manage records with missing mandatory data:

# Code example placeholder
# Add your Python/API code here for missing fields

Transaction Rollback

Implement rollback for failed imports:

# Code example placeholder
# Add your Python/API code here for rollback

Best Practices

• Validate JSON schema before attempting large imports
• Use consistent identifier fields across all JSON objects
• Stream large JSON files instead of loading into memory
• Define clear mapping rules for nested structures
• Implement comprehensive error logging
• Use transactions to maintain data consistency
• Test import logic on sample data first
• Document your JSON-to-graph mapping schema
• Handle null and undefined values appropriately
• Consider using JSON Lines format for very large datasets

Common Import Scenarios

Importing Academic Papers with Nested Metadata

# Code example placeholder
# Import complex paper records with authors, sections, and citations

Building Knowledge Graphs from Structured Data

# Code example placeholder
# Create entity-relationship graphs from JSON

Importing Hierarchical Taxonomies

# Code example placeholder
# Load nested category structures

JSON vs Other Formats

Next Steps

Continue learning about data import from external sources: