Knowledge graphs are more and more core and key components of a modern data management and data science pipeline. In a knowledge graph, a domain of application is broken down into entities (people, organisations, software, workflows, events, etc) connected together by mean of relationships whose semantic are explicit. But most importantly, it allows to:

• unify fragmented and unstructured data in a data integration hub
• capture data context
• capture data lineage (provenance)
• enforce (meta)data quality

During this workshop, we will learn how to build, shape up and manage a knowledge graph while ensuring the quality of the data and using Blue Brain Nexus (Github and website), an open source project developed by Blue Brain Project and released under the Apache 2 License.

Using Blue Brain Nexus, participants will be able to:

• Semantically model a domain of interest using best practices
• Manage entities representing data
• Enforce (meta)data quality using high-level and expressive domain models
• Connect data from different sources
• Capture and manage data provenance in a knowledge graph
• Search and navigate a knowledge graph using ElasticSearch and SPARQL as graph based and semantic enabled query language

• bring a laptop
• beginner level knowledge about one programming language (recommended: Python, Java or Scala)