DISQOVER Export

DISQOVER Export, developed by ONTOFORCE, is a data export solution designed for life sciences and pharmaceutical teams that need to move fully harmonized, provenance-rich knowledge out of the DISQOVER Knowledge Graph and into their broader data ecosystem. It delivers structured, semantically consistent data in industry-standard formats, ensuring that ontology mappings, entity relationships, and source metadata are preserved throughout the entire export and integration process.

Life sciences teams frequently encounter fragmented, inconsistently modeled datasets that are difficult to reuse outside their original systems. DISQOVER Export addresses this challenge by enabling direct integration into graph databases, triple stores, BI tools, and machine learning pipelines — without sacrificing semantics, context, or traceability.

Core Features and Capabilities

• Full Semantic Structure: Exported data retains the exact ontology mappings, entity relationships, and graph structure defined in the DISQOVER Knowledge Graph, ensuring consistency across teams and downstream ecosystems.
• Harmonized RDF and RDF*: Outputs are ideal for triple stores, semantic layers, FAIR workflows, and downstream knowledge graphs, including Neo4j via RDF import pipelines.
• Export What You See: Anything built within the Explore interface — including saved filters, enriched views, and curated result sets — can be exported as structured data for downstream use.
• Provenance-Rich Outputs: Every exported value includes its source metadata, supporting compliance, auditability, and trust across analytical and regulatory processes.
• Flexible Formats for Any Workflow: In addition to graph formats, DISQOVER Export supports XLSX, CSV, JSON, Parquet, and other lightweight output formats to suit a wide range of team needs.

Subgraph Export

• Users can export targeted subsets of their knowledge graph — such as specific concepts or relationships — using both Parquet and TTL export functionality.
• This capability allows teams to bring only the most relevant data into downstream analytics environments, data science workflows, BI tools, or AI pipelines.
• Subgraph export eliminates unnecessary noise and data volume while preserving full context from the original knowledge graph.

Supported Export Formats

• .ttl (Turtle/RDF): A rich, semantic graph format that preserves ontology structure, relationships, and provenance — ideal for triple stores and graph environments.
• .parquet: An optimized, columnar storage format suited for high-performance analytics and machine learning workloads at scale.
• .csv / .xlsx: Lightweight tabular exports for quick analysis, visualization tools, and ad hoc workflows across any team.
• .json: Flexible structured output for APIs, dashboards, scripting, and integration into modern data pipelines.

DISQOVER Export is built to integrate trusted, structured life sciences data directly into analytical pipelines, predictive models, and enterprise tools. As part of the broader DISQOVER platform — which is built on knowledge graph technology — it supports life sciences and pharmaceutical organizations in achieving interoperable, FAIR-aligned data management at scale.