Search Results

Documents authored by Voigt, Hannes

Document
Position
DOI: 10.4230/TGDK.4.2.2
How Human-Centric Are Our Graph Data Abstractions?

Authors: Angela Bonifati, Anastasia Dimou, Stefania Dumbrava, George Fletcher, Katja Hose, George Konstantinidis, Jose Emilio Labra Gayo, Wim Martens, Nina Pardal, Liat Peterfreund, Katherine Thornton, Maria-Esther Vidal, and Hannes Voigt

Published in: TGDK, Volume 4, Issue 2 (2026): Special Issue on Data Management for (Knowledge) Graphs. Transactions on Graph Data and Knowledge, Volume 4, Issue 2

Abstract
Graph data abstractions are often assumed to be intuitive, but experience shows that they are not equally understandable or usable in practice. In this vision and challenges paper, we examine the human-centricity of contemporary graph data abstractions through four lenses: researchability, usability, teachability, and societal impact. Drawing on diverse real-world use cases, ranging from clinical data and collaborative knowledge bases to biological and pangenomic graphs, we distill insights from database research, human-computer interaction, and education. Based on this analysis, we identify open research challenges that must be addressed to make graph abstractions easier to study, use, learn, and reason about.
Cite as

Angela Bonifati, Anastasia Dimou, Stefania Dumbrava, George Fletcher, Katja Hose, George Konstantinidis, Jose Emilio Labra Gayo, Wim Martens, Nina Pardal, Liat Peterfreund, Katherine Thornton, Maria-Esther Vidal, and Hannes Voigt. How Human-Centric Are Our Graph Data Abstractions?. In Special Issue on Data Management for (Knowledge) Graphs. Transactions on Graph Data and Knowledge (TGDK), Volume 4, Issue 2, pp. 2:1-2:31, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

Copy BibTex To Clipboard

@Article{bonifati_et_al:TGDK.4.2.2,
  author =	{Bonifati, Angela and Dimou, Anastasia and Dumbrava, Stefania and Fletcher, George and Hose, Katja and Konstantinidis, George and Gayo, Jose Emilio Labra and Martens, Wim and Pardal, Nina and Peterfreund, Liat and Thornton, Katherine and Vidal, Maria-Esther and Voigt, Hannes},
  title =	{{How Human-Centric Are Our Graph Data Abstractions?}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{2:1--2:31},
  ISSN =	{2942-7517},
  year =	{2026},
  volume =	{4},
  number =	{2},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/TGDK.4.2.2},
  URN =		{urn:nbn:de:0030-drops-275837},
  doi =		{10.4230/TGDK.4.2.2},
  annote =	{Keywords: graph data abstractions, property graphs, RDF, human-centric data management, usability, computing education}
}
Document
DOI: 10.4230/DagRep.15.4.79
Holistic Graph-Processing Systems: Enabling Real-World Scale and Societal Impact (Dagstuhl Seminar 25171)

Authors: Alexandru Iosup, Ana Lucia Varbanescu, Hannes Voigt, and Jože Rožanec

Published in: Dagstuhl Reports, Volume 15, Issue 4 (2025)

Abstract
This report documents the program and the outcomes of Dagstuhl Seminar 25171, "Holistic Graph-Processing Systems: Enabling Real-World Scale and Societal Impact". Motivated by the need to tackle the challenges that massive and complex data production and consumption bring to our interconnected, digital world, this seminar focused on large-scale graph processing as a systematic approach to transform these challenges into opportunities. Graphs provide a universal mathematical abstraction for such data, and they already influence various sectors - such as logistics, drug discovery, or fraud detection. However, we have only begun to realize their potential. Nevertheless, the benefits of graph processing could be canceled out by the rapid increase in data scale and diversity, as well as the increasing complexity in developing, executing, and sharing graph-based algorithms and workflows. The emerging field of graph processing systems promises to tackle these challenges. To make such systems effective and efficient, and facilitate their adoption, we need holistic approaches to cope with data transformation and ingestion, workload and system dynamics, high-tier graph programming and co-design with the platform, the emerging computing continuum, and domain-specific needs, among others. Our seminar explored the symbiosis of graph systems, machine learning, and network science by bringing together researchers, developers, and practitioners actively working on these topics with a focus on graphs. The seminar featured a mix of invited talks, expert panels, and focused discussion groups. The report documents these different elements, summarizes the main findings, and identifies the open problems and challenges that we will tackle next as a joint community.
Cite as

Alexandru Iosup, Ana Lucia Varbanescu, Hannes Voigt, and Jože Rožanec. Holistic Graph-Processing Systems: Enabling Real-World Scale and Societal Impact (Dagstuhl Seminar 25171). In Dagstuhl Reports, Volume 15, Issue 4, pp. 79-91, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

Copy BibTex To Clipboard

@Article{iosup_et_al:DagRep.15.4.79,
  author =	{Iosup, Alexandru and Varbanescu, Ana Lucia and Voigt, Hannes and Ro\v{z}anec, Jo\v{z}e},
  title =	{{Holistic Graph-Processing Systems: Enabling Real-World Scale and Societal Impact (Dagstuhl Seminar 25171)}},
  pages =	{79--91},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2025},
  volume =	{15},
  number =	{4},
  editor =	{Iosup, Alexandru and Varbanescu, Ana Lucia and Voigt, Hannes and Ro\v{z}anec, Jo\v{z}e},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.15.4.79},
  URN =		{urn:nbn:de:0030-drops-252708},
  doi =		{10.4230/DagRep.15.4.79},
  annote =	{Keywords: digital continuum choreography, graph processing optimization, machine learning on graphs, massive graphs, sustainable distributed graph processing}
}
Document
DOI: 10.4230/DagRep.9.12.1
Big Graph Processing Systems (Dagstuhl Seminar 19491)

Authors: Angela Bonifati, Alexandru Iosup, Sherif Sakr, and Hannes Voigt

Published in: Dagstuhl Reports, Volume 9, Issue 12 (2020)

Abstract
This report documents the program and the outcomes of Dagstuhl Seminar 19491 "Big Graph Processing Systems". We are just beginning to understand the role graph processing could play in our society. Data is not just getting bigger, but, crucially, also more connected. Exploring, describing, predicting, and explaining real- and digital-world phenomena is increasingly relying on abstractions that can express interconnectedness. Graphs are such an abstraction. They can model naturally the complex relationships, interactions, and interdependencies between objects. However, after initial success, graph processing systems are struggling to cope with the new scale, diversity, and other real-world needs. The Dagstuhl Seminar 19491 aims to addresses the question: How could the next decade look like for graph processing systems? To identify the opportunities and challenges of graph processing systems over the next decade, we met in December 2019 with circa 40 high-quality and diverse researchers for the Dagstuhl Seminar on Big Graph Processing Systems. A main strength of this seminar is the combination of the data management and large-scale systems communities. The seminar was successful, and addressed in particular topics around graph processing systems: ecosystems, abstractions and other fundamental theory, and performance.
Cite as

Angela Bonifati, Alexandru Iosup, Sherif Sakr, and Hannes Voigt. Big Graph Processing Systems (Dagstuhl Seminar 19491). In Dagstuhl Reports, Volume 9, Issue 12, pp. 1-27, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)

Copy BibTex To Clipboard

@Article{bonifati_et_al:DagRep.9.12.1,
  author =	{Bonifati, Angela and Iosup, Alexandru and Sakr, Sherif and Voigt, Hannes},
  title =	{{Big Graph Processing Systems (Dagstuhl Seminar 19491)}},
  pages =	{1--27},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2020},
  volume =	{9},
  number =	{12},
  editor =	{Bonifati, Angela and Iosup, Alexandru and Sakr, Sherif and Voigt, Hannes},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.9.12.1},
  URN =		{urn:nbn:de:0030-drops-120098},
  doi =		{10.4230/DagRep.9.12.1},
  annote =	{Keywords: Abstractions, Big Data, Big Graph, data management, Ecosystems, graph processing, Performance, systems, Theory}
}

Any Issues?
X

Feedback on the Current Page

CAPTCHA

Thanks for your feedback!

Feedback submitted to Dagstuhl Publishing

Could not send message

Please try again later or send an E-mail
© 2023-2026 Schloss Dagstuhl – LZI GmbH Schloss Dagstuhl – LZI GmbH About DROPS Imprint Privacy Contact