Traceable, reproducible research with complete provenance
AX Verified Research™ establishes a new standard for scientific reproducibility. Every result, calculation, and conclusion is tracked through knowledge graphs that capture complete data lineage, experimental conditions, and verification status.
This enables researchers to trace any finding back to its source data, verify computational methods, and reproduce results with confidence—addressing the reproducibility crisis in science.
We use Neo4j to track relationships between datasets, analyses, publications, and researchers. This helps visualize how findings connect.
MATCH (paper:Publication)-[:CITES]->(source:Publication) WHERE paper.title = "Quantum Photonics with GaAs" RETURN paper, source
Automatic tracking of data origins, transformations, and analyses. Every plot, table, and result includes metadata about how it was generated.
Automated checks verify that published results can be reproduced from source data. Flag discrepancies and track verification status across research artifacts.
Explore research connections through interactive graph visualizations. Discover related work, identify knowledge gaps, and trace the evolution of scientific ideas.
Attach verifiable provenance to publications, enabling readers to trace and reproduce findings
Share datasets and analyses with complete context for seamless collaboration
Navigate research connections to discover related work and identify knowledge gaps
Maintain audit trails for research in regulated industries (pharma, aerospace, etc.)
Graph database for knowledge representation and querying
Data version control for tracking datasets and models
Code versioning and collaboration
Query Neo4j to find all datasets that contributed to a specific publication:
MATCH (pub:Publication {doi: "10.1234/example"})-[:USES*]->(data:Dataset)
RETURN data.name, data.collection_date, data.source
ORDER BY data.collection_date DESC