nexusforge 0.4.0

Building and Using Knowledge Graphs made easy.

Blue Brain Nexus Forge is a domain-agnostic, generic and extensible Python framework enabling non-expert users to create and manage knowledge graphs by making it easy to:

• Discover and reuse available knowledge resources such as ontologies and schemas to shape, constraint, link and add semantics to datasets.

• Build knowledge graphs from datasets generated from heterogenous sources and formats. Defining, executing and sharing data mappers to transform data from a source format to a target one conformant to schemas and ontologies.

• Interface with various stores offering knowledge graph storage, management and scaling capabilities, for example Nexus Core store or in-memory store.

• Validate and register data and metadata.

• Search and download data and metadata from a knowledge graph.

Getting Started

The examples directory contains many Jupyter Notebooks to get started with Blue Nexus Forge user features and usage scenarios.

You can run the Getting Started notebooks on Binder by clicking on .

For local execution, make sure that the jupyter notebook|lab is launched in the same virtual environment where Blue Brain Nexus Forge is installed. Alternatively, set up a specialized kernel.

In both cases, please start with the notebook named 00 - Initialization. It contains instructions for configuring the Forge with:

• an example in-memory store and an example schema language,

• Blue Brain Nexus as store and W3C SHACL as schema language.

After, it is recommended to run the notebooks following their number (01, 02, …).

Installation

It is recommended to use a virtual environment such as venv or conda environment.

Stable version

pip install nexusforge

Upgrade to the latest version

pip install --upgrade nexusforge

Development version

pip install git+https://github.com/BlueBrain/nexus-forge

Acknowledgements

This project has received funding from the EPFL Blue Brain Project (funded by the Swiss government’s ETH Board of the Swiss Federal Institutes of Technology) and from the European Union’s Horizon 2020 Framework Programme for Research and Innovation under the Specific Grant Agreement No. 785907 (Human Brain Project SGA2).