Since IntelligentGraph combines Knowledge Graphs with embedded data analytics, Jupyter is an obvious choice as a data analysts’ IntelligentGraph workbench.
The following are screen-captures of a Jupyter-Notebook session showing how Jupyter can be used as an IDE for IntelligentGraph to perform all of the following:
Create a new IntelligentGraph repository
Add nodes to that repository
Add calculation nodes to the same repository
Navigate through the calculated results
Query the results using SPARQL
GettingStarted is available as a JupyterNotebook here: GettingStarted JupyterNotebook
Images of the GettingStarted JupyterNotebook follow:
Using the Jupyter ISparql, we can easily perform SPARQL queries over the same IntelligentGraph created above.… Read more...