# What Formats Can Semantica Export Data To? Complete Export Format Reference

> Discover Semantica's extensive data export capabilities. Explore over 20 formats including RDF, GraphML, Parquet, vector embeddings, and database imports for seamless integration.

- Repository: [Semantica /semantica](https://github.com/semantica-agi/semantica)
- Tags: api-reference
- Published: 2026-08-22

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**Semantica supports over 20 distinct export formats spanning RDF serializations (Turtle, JSON-LD), graph exchange formats (GraphML, GEXF, Cypher), columnar storage (Parquet, Apache Arrow), vector embeddings (FAISS, NumPy), and database-specific imports (Neo4j CSV, ArangoDB AQL), all accessible through the unified `export_knowledge_graph` dispatcher.**

The `semantica-agi/semantica` repository implements a registry-based export architecture centered in [`semantica/export/methods.py`](https://github.com/semantica-agi/semantica/blob/main/semantica/export/methods.py). This design allows the high-level `export_knowledge_graph` helper (lines 92–111) to automatically route knowledge graphs, ontologies, and vector data to the correct serializer based on file extension or explicit `format` arguments.

## Semantic Web and Linked Data Formats

Semantica provides comprehensive support for W3C semantic web standards through dedicated exporters in [`semantica/export/rdf_exporter.py`](https://github.com/semantica-agi/semantica/blob/main/semantica/export/rdf_exporter.py) and [`semantica/export/owl_exporter.py`](https://github.com/semantica-agi/semantica/blob/main/semantica/export/owl_exporter.py).

- **RDF Serializations** — Export to `turtle`, `rdfxml`, `ntriples`, and `n3` (Notation3) via the **RDF Exporter** (registered around lines 9–17 in [`methods.py`](https://github.com/semantica-agi/semantica/blob/main/methods.py)).
- **JSON-LD** — Available as `jsonld` through the RDF exporter or `json-ld` through the **JSON Exporter** ([`semantica/export/json_exporter.py`](https://github.com/semantica-agi/semantica/blob/main/semantica/export/json_exporter.py), lines 18–22), providing Linked Data compatible output.
- **OWL Ontologies** — Serialize schemas to `owl-xml` or `turtle` formats using the **OWL Exporter** (lines 36–39), optimized for ontology exchange with Protégé and other OWL tools.

## Tabular and Columnar Storage Formats

For analytics pipelines and data science workflows, Semantica supports efficient binary and text-based tabular formats:

- **CSV** — Standard comma-separated output for entities and relationships via [`semantica/export/csv_exporter.py`](https://github.com/semantica-agi/semantica/blob/main/semantica/export/csv_exporter.py) (lines 22–28), compatible with pandas and Excel.
- **Apache Arrow** — Zero-copy IPC format (`arrow`) for high-performance data exchange between Python, R, and Julia (around lines 40–46).
- **Apache Parquet** — Compressed columnar storage (`parquet`) ideal for data lakes and warehouse ingestion (lines 84–92), with configurable compression codecs.

## Graph Visualization and Exchange Formats

Visualization tools and graph databases receive native support through [`semantica/export/graph_exporter.py`](https://github.com/semantica-agi/semantica/blob/main/semantica/export/graph_exporter.py) and specialized database exporters:

- **GraphML and GEXF** — Standard XML formats for **Gephi** and network analysis tools (`graphml`, `gexf`).
- **Graphviz DOT** — Generation of `dot` files for rendering directed graphs with Graphviz.
- **JSON Graph** — Lightweight JSON representation of nodes and edges for web-based visualizations.
- **Labeled Property Graph (LPG)** — Raw `lpg` format and `cypher` query scripts for Neo4j bulk operations via [`semantica/export/lpg_exporter.py`](https://github.com/semantica-agi/semantica/blob/main/semantica/export/lpg_exporter.py).

## Database Import Formats

Semantica generates deterministic import files for popular graph databases without requiring live connections:

- **Neo4j CSV** — `neo4j_csv` format produces separate header and data files conforming to Neo4j Admin import specifications ([`semantica/export/neo4j_csv_exporter.py`](https://github.com/semantica-agi/semantica/blob/main/semantica/export/neo4j_csv_exporter.py), lines 50–52).
- **ArangoDB AQL** — `aql` format emits executable `INSERT` statements for ArangoDB collections via [`semantica/export/arango_aql_exporter.py`](https://github.com/semantica-agi/semantica/blob/main/semantica/export/arango_aql_exporter.py) (lines 73–78).

## Vector and Machine Learning Formats

Vector embeddings export to specialized formats for similarity search and ML pipelines through [`semantica/export/vector_exporter.py`](https://github.com/semantica-agi/semantica/blob/main/semantica/export/vector_exporter.py):

- **FAISS** — Native `faiss` index format for Facebook AI Similarity Search, supporting efficient billion-scale similarity queries.
- **NumPy Arrays** — Binary `.npy` files (`numpy`) for direct loading into scikit-learn and PyTorch.
- **Raw Binary** — Compact `binary` format for custom vector store implementations.
- **JSON Vectors** — Human-readable `json` representation for debugging small embedding sets.

## Configuration and Documentation Formats

Human-readable and configuration formats support schema documentation and reporting:

- **YAML Schemas** — `semantic_network` and `schema` formats via [`semantica/export/yaml_exporter.py`](https://github.com/semantica-agi/semantica/blob/main/semantica/export/yaml_exporter.py) (lines 31–34, 55–62) for knowledge graph structure definitions.
- **Automated Reports** — `html`, `markdown`, `json`, and `text` reports generated by [`semantica/export/report_generator.py`](https://github.com/semantica-agi/semantica/blob/main/semantica/export/report_generator.py) (lines 53–57) for audit trails and documentation.

## Export System Architecture

The export layer employs a method registry pattern where each format maps to a specific exporter class. When `export_knowledge_graph(data, filename, format=None)` is invoked (lines 92–111 of [`semantica/export/methods.py`](https://github.com/semantica-agi/semantica/blob/main/semantica/export/methods.py)), the function inspects the file extension or `format` parameter to select the appropriate exporter from the registry. This extensible design allows new formats to be added by implementing a new exporter class and registering it in the central registry without modifying the high-level API.

## Practical Code Examples

```python
from semantica.export.methods import export_knowledge_graph

# Export knowledge graph to Turtle RDF for semantic web integration

export_knowledge_graph(kg, "ontology.ttl", format="turtle")

# Generate GraphML for visualization in Gephi

export_knowledge_graph(kg, "network.graphml", format="graphml")

# Create Neo4j bulk import CSV files

export_knowledge_graph(kg, "nodes.csv", format="neo4j_csv")

# Export vector embeddings to FAISS index

export_knowledge_graph(embeddings, "index.faiss", format="faiss")

# Generate Markdown documentation report

export_knowledge_graph(kg, "report.md", format="markdown")

```

## Summary

- **Semantica exports to 20+ formats** across six categories: RDF, tabular, graph visualization, database imports, vectors, and documentation.
- **Central dispatch** occurs through `export_knowledge_graph` in [`semantica/export/methods.py`](https://github.com/semantica-agi/semantica/blob/main/semantica/export/methods.py), which auto-detects formats by file extension.
- **Database formats** include Neo4j CSV, Cypher scripts, and ArangoDB AQL for offline bulk imports.
- **Vector formats** support FAISS, NumPy, and binary serialization for ML workflows.
- **Extensible registry** allows custom exporters to integrate seamlessly with the existing `format` parameter.

## Frequently Asked Questions

### What is the difference between JSON and JSON-LD export in Semantica?

The standard `json` format produces plain JSON via [`semantica/export/json_exporter.py`](https://github.com/semantica-agi/semantica/blob/main/semantica/export/json_exporter.py), while `jsonld` (or `json-ld`) produces JSON-LD via either the JSON exporter or [`semantica/export/rdf_exporter.py`](https://github.com/semantica-agi/semantica/blob/main/semantica/export/rdf_exporter.py). JSON-LD includes semantic context and vocabulary mappings required for linked data applications, whereas plain JSON provides a simpler structural representation without RDF semantics.

### Does Semantica export directly to Neo4j or generate import files?

Semantica generates import files rather than maintaining live database connections. The `cypher` format produces Cypher query scripts, while `neo4j_csv` generates deterministic CSV files compatible with the Neo4j Admin `import` command. These files are created through [`semantica/export/lpg_exporter.py`](https://github.com/semantica-agi/semantica/blob/main/semantica/export/lpg_exporter.py) and [`semantica/export/neo4j_csv_exporter.py`](https://github.com/semantica-agi/semantica/blob/main/semantica/export/neo4j_csv_exporter.py) respectively.

### How can I add a custom export format to Semantica?

Implement a new exporter class following the existing pattern in [`semantica/export/methods.py`](https://github.com/semantica-agi/semantica/blob/main/semantica/export/methods.py), then register it in the method registry (around lines 9–92). Once registered, the `export_knowledge_graph` dispatcher automatically recognizes the new format via the `format` parameter or file extension without requiring changes to the public API.

### Which format is best for large-scale knowledge graphs?

For analytics and data science workflows, use **`parquet`** for compressed columnar storage or **`arrow`** for inter-process communication. For semantic web archiving, **`turtle`** provides a balance of readability and compression. For graph database migration, **`neo4j_csv`** offers the fastest bulk import performance into Neo4j.