The free-form nature of Graph style data offers a lot of flexibility for connecting data, but that freedom can also make it more challenging to find interesting patterns or simply navigate through your data. It has become typical for RDF data sets to contain thousands of classes and relationship types, creating challenges to even formulate the analytics and queries you want to perform. Visual discovery and exploration tools provide a means to make data analyst more effective and the process more efficient. Generating complex SPARQL queries graphically, rather than writing code, offers an onramp to developers learning SPARQL and a means for advanced users visualize complex queries where code may be difficult to follow.

We will demonstrate how to visually explore and query RDF data sets and ontologies (such as FIBO) with Gruff, a free downloadable tool. Gruff, a visual analytics and discovery tool, was developed to specifically address the Graph data exploration challenges in large data sets. The tool is used by analysts in the financial world to find connections between their clients and also to discover fraud. Analysts in the pharmaceutical industry use it to visualize and discover connections between drugs, diseases, and cellular pathways. As part of the presentation we will cover these use cases and offer demonstrations.

The presentation will touch on other visualization tools, such as Linkurious and Gephi, and how they can be used to view the overall structure in your data. We will touch on ideas to use these tools collaboratively with Gruff and best practices for exploring large RDF datasets.

The presentation will focus on:

• Exploring Data in the Graph View
• Generating SPARQL Queries Directly from the Graph View
• Modifying and Building Visual SPARQL Queries from the Ground Up