This webinar has been recorded and available on YouTube.
Visual graph exploration helps you delve quickly into your data as it is. But what if you can create your own graph views on top of your data? How to address the challenges when changing the graph visualization according to a custom ontology schema, or hide provenance or another meta-data information?
In the imperfect world of open data, your graph often contains nodes and edges that should be combined to obtain a meaningful one. Or you may want to create more than one views over the same data, creating your virtual nodes and edges based on the existing ones. This is all doable with the power of the SPARQL language. Advanced visual graph configuration combines the power of visual representation and SPARQL to obtain easy to understand graph views with exploration designed by you to match your data and your needs.
In this webinar, we will show you how to create visual graphs by writing SPARQL queries. You will learn how to:
- Visualize a random Graph Query result;
- Extend auto-complete with a custom predicate to find your nodes;
- Create custom graph visualization by defining how to:
- Start graph exploration;
- Expand nodes in your graph;
- Present visually the nodes in your graph;
- Present visually the edges in your graph;
- Obtain additional data about the nodes in the graph.
Who is this webinar for:
- Technical people confident in SPARQL;
- Consultants and Solution Architects;
- Linked Data Scientists;
- People interested in graph data visualization.
Webinar Duration: 60 minutes
Live Webinar: Yes
Live Question Answering: Yes
Resource After Webinar: Recording
