The free­form 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 (Fig 1.) where code may be difficult to follow (Fig 2.).

In this tutorial we will instruct attendees on how to visually explore and query RDF data sets 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 tutorial introduction we will cover these use cases and offer demonstrations.
During the tutorial we 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 tutorial will work through the following concepts and attendees will be encouraged to follow along with sample datasets provided or using their own data.

This tutorial is designed for beginner/intermediate technical attendees that would like to become more proficient in SPARQL and data discovery usinga semantic graph database. Advanced SPARQL users will also benefit from the data discovery capabilities that will be demonstrated during the tutorial.
Basic understanding of Graphs, RDF, and SPARQL is helpful but not necessary.

Lunch

Dr. Jans Aasman started his career as an experimental and cognitive psychologist, earning his PhD in cognitive science with a detailed model of car driver behavior. He has spent most of his professional life in telecommunications research, specializing in intelligent user interfaces and applied artificial intelligence projects. From 1995 to 2004, he was also a part­time professor in the Industrial Design department of the Technical University of Delft. Jans is currently the CEO of Franz Inc., the leading supplier of commercial, persistent, and scalable Graph Database products that provide the storage layer for powerful reasoning and ontology modeling capabilities for Cognitive Computing applications.