morph-kgc 2.3.0

Powerful [R2]RML engine to create RDF knowledge graphs from heterogeneous data sources.

Morph-KGC is an engine that constructs RDF and RDF-star knowledge graphs from heterogeneous data sources with the R2RML, RML and RML-star mapping languages. Morph-KGC is built on top of pandas and it leverages mapping partitions to significantly reduce execution times and memory consumption for large data sources.

Citing Morph-KGC: If you used Morph-KGC in your work, please cite the SWJ paper:

@article{arenas2022morph,
  title   = {{Morph-KGC: Scalable knowledge graph materialization with mapping partitions}},
  author  = {Arenas-Guerrero, Julián and Chaves-Fraga, David and Toledo, Jhon and Pérez, María S. and Corcho, Oscar},
  journal = {Semantic Web},
  year    = {2022},
  doi     = {10.3233/SW-223135}
}

Main Features

• Supports R2RML, RML and RML-star mapping languages.
• Input data formats:
  • Relational databases: MySQL, PostgreSQL, Oracle, Microsoft SQL Server, MariaDB, SQLite.
  • Tabular files: CSV, TSV, Excel, Parquet, Feather, ORC, Stata, SAS, SPSS, ODS.
  • Hierarchical files: JSON, XML.
• Output RDF and RDF-star serializations: N-Triples, N-Triples-star, N-Quads, N-Quads-star.
• Integration with RDFLib and Oxigraph.
• Remote data files and mapping files.
• Runs on Linux, Windows and macOS systems.
• Compatible with Python 3.7 or higher.
• Optimized to materialize large knowledge graphs.

Documentation

Read the documentation.

Tutorial

Learn quickly with the tutorial in Google Colaboratory!

Getting Started

PyPi is the fastest way to install Morph-KGC:

pip install morph-kgc

We recommend to use virtual environments to install Morph-KGC.

To run the engine via command line you just need to execute the following:

python3 -m morph_kgc config.ini

Check the documentation to see how to generate the configuration INI file. Here you can also see an example INI file.

It is also possible to run Morph-KGC as a library with RDFLib and Oxigraph:

import morph_kgc

# generate the triples and load them to an RDFLib graph
g_rdflib = morph_kgc.materialize('/path/to/config.ini')
# work with the RDFLib graph
q_res = g_rdflib.query(' SELECT DISTINCT ?classes WHERE { ?s a ?classes } ')

# generate the triples and load them to Oxigraph
g_oxigraph = morph_kgc.materialize_oxigraph('/path/to/config.ini')
# work with Oxigraph
q_res = graph.query(' SELECT DISTINCT ?classes WHERE { ?s a ?classes } ')

# the methods above also accept the config as a string
config = """
            [DataSource1]
            mappings: /path/to/mapping/mapping_file.rml.ttl
            db_url: mysql+pymysql://user:password@localhost:3306/db_name
         """
g_rdflib = morph_kgc.materialize(config)

License

Morph-KGC is available under the Apache License 2.0.

Author

• Julián Arenas-Guerrero - [e-mail]

Ontology Engineering Group, Universidad Politécnica de Madrid.

Contributors

See the full list of contributors here.