PhD School on Visual exploration of graph databases

The pre-conference PhD school is planned on-site at the conference venue (Saracen Sands Hotel & Congress Centre) for September 19, 2023. Each participant must register by filling in the corresponding entry of the registration form.

Topic

In recent years, a multitude of new technologies have been developed for managing, processing and analyzing graphs. Among these technologies, graph databases are becoming the main solution adopted by industries and institutions to exploit the expressiveness and flexibility of the graph model in multiple use cases. In this context, a key challenge is to allow end users, possibly without technical knowledge, to fully exploit the power of these solutions. To this aim, advanced graph visualization solutions can play a crucial role. To foster research in this field within the GD community, our speakers will introduce the main concepts and ideas behind graph databases from both an academic and industry perspective, and they will showcase some of the most advanced visual exploration tools for such technologies.

Speakers

Nikolay Yakovets - TU Eindhoven
Nick is an Assistant Professor at the Department of Mathematics and Computer Science, Information Systems WSK&I at Eindhoven University of Technology (TU/e). His main area of study is databases and data intensive systems. He is particularly interested in foundations of databases, efficient data analytics and engineering of high-performance data processing systems. He’s current focus is on design and implementation of core database technologies, management of massive graph data, and efficient processing of queries on graphs. His educational activities focus on data modeling and databases, data management for data analytics, database technology, and data engineering.
Andreas Kollegger - Neo4J
Andreas Kollegger is a technological humanist. Starting at NASA, Andreas designed systems from scratch to support science missions. Then in Zambia, he built medical informatics systems to apply technology for social good. Now with Neo4j, he is democratizing graph databases to validate and extend our intuitions about how the world works.
At Neo4j he has specialized in graph visualization products, creating Neo4j Browser to visualize query results and Neo4j Bloom to power graph exploration. Today he manages Neo4j Arrows, a graph illustration application.
Fouli Argyriou - yWorks
Fouli received her Ph.D. in Computer Science in 2013 from the National Technical University of Athens, Greece. Her research interests concern theoretical aspects of Computer Science, focusing on algorithms and their complexity mostly from the areas of graph drawing with emphasis on security applications, fraud detection, and information visualization. Since 2014 she works as a Software Engineer at yWorks, first as part of the layout team and now as part of the yFiles for HTML team.

Program

First lecture: Nikolay Yakovets - Querying graphs

Graph data modeling and querying arises in many practical application domains such as social, biological, and transportation networks where the primary focus is on concepts and their relationships and the rich patterns in these complex webs of interconnectivity. In this lecture, a concise unified view is given on the fundamental challenges which arise over the complete life cycle of formulating and processing queries on graph databases.
Second lecture: Andreas Kollegger - From graph data to human-friendly representations

In this talk, Andreas Kollegger of Neo4j will map from the precise details of graph data to the human-friendly representations of graph visualization used by Neo4j Bloom. Just like relational databases, graph databases have a conceptual, logical and physical model. Neo4j Bloom is growing from the physical model to the conceptual, abstracting the implementation details to restore the original domain knowledge that is critical for an intuitive exploration experience. We'll review three key aspects: modeling, searching, and exploration:
  • "Perspectives" as an abstraction over the physical graph data model
  • Patterns, phrases, and natural language searches
  • Graph visualization as an interactive interface
Third lecture: Fouli Argyriou - Visualizing and exploring graph databases with yFiles

Graph databases have gained significant popularity in big data analysis, especially when dealing with data with complex relationships and connections. Making advantage of the graph structure and representing the data as a set of nodes (entities) and edges (relationships), they offer highly flexible and efficient storage and handling of connected data in comparison to traditional databases. These features make graph databases particularly useful for use cases like social networks, criminal network analysis, or fraud detection.
The graph structure of graph databases can be directly utilized for creating a graphical representation in the form of a diagram which facilitates uncovering insights and patterns that might be difficult to discern through other analytical methods. While the nature of the connected data of graph databases lends itself well to visualization, creating a visualization that effectively conveys the information can be a challenging task due to the sheer volume of data typically included.
This presentation aims to provide an easy and convenient way to visually explore the contents of a Neo4j graph database using yWorks visualization tools with low-code and no-code techniques. It will encompass key topics such as establishing a connection to the database, understanding the database schema, and exploring interactively the data using both built-in features of the tools and Cypher queries. Furthermore, it will demonstrate how advanced graph analysis algorithms can be utilized to identify previously unidentified insights within the data and how adaptable visualization styles can be applied to graph elements.