Use Monarch Dipper
Dipper is a Python package to generate RDF triples from common scientific resources. It has been used to build and expose RDF from multiple sources for the Monarch Initiative.
Dipper includes subpackages and modules to create graphical models of this data, including:
- Models package for generating common sets of triples, including common OWL axioms, complex genotypes, associations, evidence and provenance models.
- Graph package for building graphs with RDFLib or streaming n-triples
- Source package containing fetchers and parsers that interface with remote databases and web services
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Dipper Notebooks2 Jupyter Notebooks proposed by the Dipper documentation can be easily deploy in Jupyterlab:
- Work with the Dipper Model API: see the documentation
- Query associations from IMPC, including evidence and provenance modeled with SEPIO
Clone in workspace/notebooks
, install requirements and start the Notebooks:
Access at http://localhost:8888
See the documentation to work with graphs
Or run Jupyterlab it directly using Docker:
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Download Monarch Dipper dataMonarch Initiative data generated from Dipper can be accessed through multiple interfaces. The dipper output is quality checked and released on a regular basis.
The data model: OBO
- E.g. RO_0001000, CL_0000236, rdfs:label, foaf:Person, dc:description, owl:sameAs,
OBO:RO_0002162 OBO:NCBITaxon_9606
- The BioLink model is planned to be adopted in the future.
- E.g. RO_0001000, CL_0000236, rdfs:label, foaf:Person, dc:description, owl:sameAs,
Neo4j dump: https://archive.monarchinitiative.org/latest/scigraph.tgz.
Python scripts to transform the sources: https://github.com/monarch-initiative/dipper/tree/master/dipper/sources
New sources ingestion can be wrote following this documentation.