Earlier this year, we introduced kgextension, the Python extension for processing knowledge graphs. With this extension, data analysts can easily link their data at hand to both public and private knowledge graphs, and add the wealth of public knowledge graphs such as Wikidata to their data analytics tasks with just a few simple lines of code. The extension can be combined with popular frameworks such as scikit-learn, and offers a variety of features ranging from data linkage and fusion to knowledge graph specific feature extraction and filtering.
The extension was developed in a student team project by Tabea-Clara Bucher, Xuehui Jiang, Ole Meyer, and Stephan Waitz, and supervised by Sven Hertling and Heiko Paulheim.
This week, we presented the extension at the Extended Semantic Web Conference 2021, where it was recognized with the best demonstration award! Congratulations again to Tabea-Clara, Xuehui, Ole, and Stephan for the phantastic work they did in their team project!
Links to the demo:
Links to kgextension: