16. – 21. Januar 2022, Dagstuhl-Seminar 22031

Bringing Graph Databases and Network Visualization Together


Karsten Klein (Universität Konstanz, DE)
Juan F. Sequeda ( – Austin, US)
Hsiang-Yun Wu (FH – St. Pölten , AT)
Da Yan (The University of Alabama – Birmingham, US)

Auskunft zu diesem Dagstuhl-Seminar erteilt

Dagstuhl Service Team


Dagstuhl Report, Volume 12, Issue 1 Dagstuhl Report
Gemeinsame Dokumente


Network analytics through interactive network visualization has been essential in many research and application areas, such as bioinformatics, biomedicine, cyber security, e-commerce, social science, and software engineering. A network is often supported by graph databases with advanced query engines and indexing techniques. Graph databases have substantial contributions by academia and gained strong momentum in the industry, where the focus is on scalable systems using graph query languages that require to be learned by users. Even though the Graph Database and Network Visualization communities study the same object, a graph/network, albeit from different perspectives, they do not communicate with each other. By bringing both communities together, we aimed to initiate and foster mutual communication and joint work. The goal of this seminar was to initiate collaborative efforts, to increase the mutual awareness of each others' existing concepts and technologies, and to identify new and complementary research challenges that lead to novel scientific outcomes. We have developed the schedule for the seminar based on our experience from previous successful Dagstuhl Seminars with a balance between prepared talks, plenary discussions, and breakout groups for less structured discussions focused on a selection of highly relevant topics.

The organizers envisioned several core topics for discussion at the Dagstuhl Seminar, as outlined in the proposal:

  • Integration of fundamental concepts used in the two communities
  • Visual scalability and computational performance
  • Visual graph query paradigm
  • Responsive visualization of graph query results
  • (Qualitative) Evaluation
  • Domain-oriented applications

During the plenary discussions on the first day, the participants identified several more specific topics for the work in separate working groups, which lead to the following working group titles:

  • Evaluation and Usefulness
  • Understanding gaps and opportunities between Graph Databases and Network Visualization
  • Visual querying and result visualization

Our aim was to have focused discussions on these topics in which we would be able to make significant progress during the seminar, in order to shape a position paper and to lay the foundations for subsequent collaborations. The discussions showed that there indeed is the need for a closer exchange between the communities in order to improve the mutual understanding and practical solutions, but also to identify research questions that can be tackled jointly. They however also showed the great potential in this exchange and the large interest in both communities for joint work.

We have organized the seminar during the COVID-19 pandemic. Due to various regulations and travel restrictions, only roughly half of the usual number of participants attended in person. The meeting was held purely on-site, with the exception of one participant connecting in via video conferencing. We thank Dagstuhl for equipping the seminar rooms with suitable infrastructure and for putting suitable health and safety regulations in place to create a smooth experience and safe environment for all participants.


We would like to thank all participants of the seminar for their contributions and lively discussions, and the scientific directorate of Dagstuhl for providing us with the opportunity to organize this seminar. Finally, the seminar would not have been possible without the amazing support by the staff of Dagstuhl.

Summary text license
  Creative Commons BY 4.0
  Karsten Klein, Juan F. Sequeda, Hsiang-Yun Wu, and Da Yan


  • Data Structures And Algorithms
  • Databases
  • Human-Computer Interaction


  • Graph databases
  • Network visualization
  • Visual analytics


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