Graph Data Science: an abstraction layer in Python for building knowledge graphs, integrated with popular graph libraries – atop Pandas, NetworkX, RAPIDS, RDFlib, pySHACL, PyVis, morph-kgc, pslpython, pyarrow, etc.
inference based on OWL-RL, RDFS, SKOSby creating a mixin
@ceteri let me know if this is ok. The only problem I see is that the credits for writing the code are moved to the developer that created the mixin. So if you want to keep the credits to the developer that wrote the code in the first place he/she will have to create the mixins by himself. Let me know if this is a problem.
Change logs
Add querying module that incapsulates querying for KnowledgeGraph
Move querying out of KnowledgeGraph into QueryingMixin
tomaarsen
commented
2 years ago
Current behaviour
All the methods are stacked in the
kglabmodule and it makes it difficult to handle.New expected behaviour
Implement mixins for different functionalities in different modules:
@ceteri let me know if this is ok. The only problem I see is that the credits for writing the code are moved to the developer that created the mixin. So if you want to keep the credits to the developer that wrote the code in the first place he/she will have to create the mixins by himself. Let me know if this is a problem.
Change logs
queryingmodule that incapsulates querying forKnowledgeGraphqueryingout ofKnowledgeGraphintoQueryingMixin