Search Results

Documents authored by Hegemann, Tim

Artifact
Dataset
DOI: 10.4230/artifacts.25065
GD-collection-v1

Authors: Gavin J. Mooney, Tim Hegemann, Alexander Wolff, Michael Wybrow, and Helen C. Purchase

Abstract
Cite as

Gavin J. Mooney, Tim Hegemann, Alexander Wolff, Michael Wybrow, Helen C. Purchase. GD-collection-v1 (Dataset). Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

Copy BibTex To Clipboard

@misc{dagstuhl-artifact-25065,
   title = {{GD-collection-v1}}, 
   author = {Mooney, Gavin J. and Hegemann, Tim and Wolff, Alexander and Wybrow, Michael and Purchase, Helen C.},
   note = {Dataset, swhId: \href{https://archive.softwareheritage.org/swh:1:dir:478a27dd277dc5818bdf699d2a5bc222a010533b;origin=https://github.com/hegetim/gd-collection;visit=swh:1:snp:47572e3d1828ed35295469a20640d95523046494;anchor=swh:1:rev:d1135373ff9168ee932f61eee73dda6309e23c46}{\texttt{swh:1:dir:478a27dd277dc5818bdf699d2a5bc222a010533b}} (visited on 2025-11-26)},
   url = {https://github.com/hegetim/gd-collection},
   doi = {10.4230/artifacts.25065},
}
Artifact
Software
DOI: 10.4230/artifacts.25066
GEG Encodes Graphs

Authors: Gavin J. Mooney, Tim Hegemann, Alexander Wolff, Michael Wybrow, and Helen C. Purchase

Abstract
Cite as

Gavin J. Mooney, Tim Hegemann, Alexander Wolff, Michael Wybrow, Helen C. Purchase. GEG Encodes Graphs (Software, Source Code). Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

Copy BibTex To Clipboard

@misc{dagstuhl-artifact-25066,
   title = {{GEG Encodes Graphs}}, 
   author = {Mooney, Gavin J. and Hegemann, Tim and Wolff, Alexander and Wybrow, Michael and Purchase, Helen C.},
   note = {Software, swhId: \href{https://archive.softwareheritage.org/swh:1:dir:91f45ae7976a74b00a0bf86145b52dd78838fb29;origin=https://github.com/gavjmooney/geg;visit=swh:1:snp:466de3fc98d200d2aff60e99c9adaf669e207c17;anchor=swh:1:rev:2bb5506b887564f9e233ed6c60ad641ae740e5a8}{\texttt{swh:1:dir:91f45ae7976a74b00a0bf86145b52dd78838fb29}} (visited on 2025-11-26)},
   url = {https://github.com/gavjmooney/geg},
   doi = {10.4230/artifacts.25066},
}
Artifact
Software
DOI: 10.4230/artifacts.25067
NarratiViz

Authors: Tim Hegemann

Abstract
Cite as

Tim Hegemann. NarratiViz (Software, Source Code). Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

Copy BibTex To Clipboard

@misc{dagstuhl-artifact-25067,
   title = {{NarratiViz}}, 
   author = {Hegemann, Tim},
   note = {Software, BMFTR grant 01IS22012C, swhId: \href{https://archive.softwareheritage.org/swh:1:dir:a7efa9c0ca674b6cf25b1c4b2c1f4793cc814723;origin=https://github.com/hegetim/narrativiz;visit=swh:1:snp:b18239e66463dee63bc79cf243cc2afca36ef668;anchor=swh:1:rev:24dd910cfb575574c90d7aa0650ab69cfcd11b07}{\texttt{swh:1:dir:a7efa9c0ca674b6cf25b1c4b2c1f4793cc814723}} (visited on 2025-11-26)},
   url = {https://github.com/hegetim/narrativiz},
   doi = {10.4230/artifacts.25067},
}
Document
DOI: 10.4230/LIPIcs.GD.2025.30
Universal Quality Metrics for Graph Drawings: Which Graphs Excite Us Most?

Authors: Gavin J. Mooney, Tim Hegemann, Alexander Wolff, Michael Wybrow, and Helen C. Purchase

Published in: LIPIcs, Volume 357, 33rd International Symposium on Graph Drawing and Network Visualization (GD 2025)

Abstract
Graphs are drawn for various purposes, and drawings are meant to display various features of a graph (such as planarity, Hamiltonicity). Still, there is a long history in measuring the quality of a graph drawing. Most of the metrics that have been implemented and used in large studies assume that graphs are drawn straight-line. Most of the studies use randomly generated graphs or one of very few existing benchmark sets that consist of graphs with a specific technical background (e.g., telecommunication networks). In this paper, we extend ten commonly used metrics to node-link diagrams where edges can be curves or polygonal chains. We implement these measures and use them to evaluate a new collection of graph drawings that we have extracted from 27 proceedings of the Graph Drawing conference using an automated pipeline. We compare the "metrics landscape" of our new benchmark set, the GD-collection-v1, which seems to mostly contain manually drawn graphs, to the metric landscape of a benchmark set with randomly generated graphs and computer-generated straight-line drawings that has been used in a recent study [Mooney et al.; PacificVis 2024]. Comparing the GD-collection-v1 with the Mooney at al. dataset reveals a distinct metrics landscape: GD drawings come from much smaller graphs (median vertex number 11 vs. 48) and therefore attain higher medians on most readability metrics. For example, Neighbourhood Preservation (0.5 vs. 0.239) is markedly higher in the GD-collection-v1. We also find that a large proportion of extracted drawings contain curved and/or polygonal edges (57%), motivating the extended metric definitions.
Cite as

Gavin J. Mooney, Tim Hegemann, Alexander Wolff, Michael Wybrow, and Helen C. Purchase. Universal Quality Metrics for Graph Drawings: Which Graphs Excite Us Most?. In 33rd International Symposium on Graph Drawing and Network Visualization (GD 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 357, pp. 30:1-30:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

Copy BibTex To Clipboard

@InProceedings{mooney_et_al:LIPIcs.GD.2025.30,
  author =	{Mooney, Gavin J. and Hegemann, Tim and Wolff, Alexander and Wybrow, Michael and Purchase, Helen C.},
  title =	{{Universal Quality Metrics for Graph Drawings: Which Graphs Excite Us Most?}},
  booktitle =	{33rd International Symposium on Graph Drawing and Network Visualization (GD 2025)},
  pages =	{30:1--30:20},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-403-1},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{357},
  editor =	{Dujmovi\'{c}, Vida and Montecchiani, Fabrizio},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.GD.2025.30},
  URN =		{urn:nbn:de:0030-drops-250162},
  doi =		{10.4230/LIPIcs.GD.2025.30},
  annote =	{Keywords: Graph drawing metrics, metric landscape, straight-line drawings, polyline drawings, curved drawings, automated extraction of graph drawings}
}
Document
DOI: 10.4230/LIPIcs.GD.2025.39
Optimizing Wiggle in Storylines

Authors: Alexander Dobler, Tim Hegemann, Martin Nöllenburg, and Alexander Wolff

Published in: LIPIcs, Volume 357, 33rd International Symposium on Graph Drawing and Network Visualization (GD 2025)

Abstract
A storyline visualization shows interactions between characters over time. Each character is represented by an x-monotone curve. Time is mapped to the x-axis, and groups of characters that interact at a particular point t in time must be ordered consecutively in the y-dimension at x = t. The predominant objective in storyline optimization so far has been the minimization of crossings between (blocks of) characters. Building on this work, we investigate another important, but less studied quality criterion, namely the minimization of wiggle, i.e., the amount of vertical movement of the characters over time. Given a storyline instance together with an ordering of the characters at any point in time, we show that wiggle count minimization is NP-complete. In contrast, we provide algorithms based on mathematical programming to solve linear wiggle height minimization and quadratic wiggle height minimization efficiently. Finally, we introduce a new method for routing character curves that focuses on keeping distances between neighboring curves constant as long as they run in parallel. We have implemented our algorithms, and we conduct a case study that explores the differences between the three optimization objectives. We use existing benchmark data, but we also present a new use case for storylines, namely the visualization of rolling stock schedules in railway operation.
Cite as

Alexander Dobler, Tim Hegemann, Martin Nöllenburg, and Alexander Wolff. Optimizing Wiggle in Storylines. In 33rd International Symposium on Graph Drawing and Network Visualization (GD 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 357, pp. 39:1-39:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

Copy BibTex To Clipboard

@InProceedings{dobler_et_al:LIPIcs.GD.2025.39,
  author =	{Dobler, Alexander and Hegemann, Tim and N\"{o}llenburg, Martin and Wolff, Alexander},
  title =	{{Optimizing Wiggle in Storylines}},
  booktitle =	{33rd International Symposium on Graph Drawing and Network Visualization (GD 2025)},
  pages =	{39:1--39:17},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-403-1},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{357},
  editor =	{Dujmovi\'{c}, Vida and Montecchiani, Fabrizio},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.GD.2025.39},
  URN =		{urn:nbn:de:0030-drops-250252},
  doi =		{10.4230/LIPIcs.GD.2025.39},
  annote =	{Keywords: Storyline visualization, wiggle minimization, NP-complete, linear programming, quadratic programming, experimental analysis}
}
Artifact
Software
DOI: 10.4230/artifacts.22518
Graph Harvester

Authors: Julius Deynet, Tim Hegemann, Sebastian Kempf, and Alexander Wolff

Abstract
Cite as

Julius Deynet, Tim Hegemann, Sebastian Kempf, Alexander Wolff. Graph Harvester (Software, Source Code). Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

Copy BibTex To Clipboard

@misc{dagstuhl-artifact-22518,
   title = {{Graph Harvester}}, 
   author = {Deynet, Julius and Hegemann, Tim and Kempf, Sebastian and Wolff, Alexander},
   note = {Software, swhId: \href{https://archive.softwareheritage.org/swh:1:dir:f390ce9e8201cb8d2c97848e8fb5170173dcb82b;origin=https://github.com/JuliusDeynet/graph_harvester;visit=swh:1:snp:bdfe5f02f631232b0713ec89a61137901514f2fc;anchor=swh:1:rev:42f62e576eecab2ab51e79d22bba90bc7aff0496}{\texttt{swh:1:dir:f390ce9e8201cb8d2c97848e8fb5170173dcb82b}} (visited on 2024-11-28)},
   url = {https://github.com/JuliusDeynet/graph_harvester},
   doi = {10.4230/artifacts.22518},
}
Artifact
Software
DOI: 10.4230/artifacts.22519
Publines

Authors: Tim Hegemann and Alexander Wolff

Abstract
Cite as

Tim Hegemann, Alexander Wolff. Publines (Software, Source Code). Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

Copy BibTex To Clipboard

@misc{dagstuhl-artifact-22519,
   title = {{Publines}}, 
   author = {Hegemann, Tim and Wolff, Alexander},
   note = {Software, swhId: \href{https://archive.softwareheritage.org/swh:1:dir:8b6a0dd881ed0b7a4b0e5d8dbfa38f82827aa641;origin=https://github.com/hegetim/publines;visit=swh:1:snp:3c1e7e4af669de65e04453c4429a636ff7e3e7db;anchor=swh:1:rev:9271104cbd24e6d51af7e073e6bad0593f8f0e96}{\texttt{swh:1:dir:8b6a0dd881ed0b7a4b0e5d8dbfa38f82827aa641}} (visited on 2024-11-28)},
   url = {https://github.com/hegetim/publines},
   doi = {10.4230/artifacts.22519},
}
Document
DOI: 10.4230/LIPIcs.GD.2024.26
Storylines with a Protagonist

Authors: Tim Hegemann and Alexander Wolff

Published in: LIPIcs, Volume 320, 32nd International Symposium on Graph Drawing and Network Visualization (GD 2024)

Abstract
Storyline visualizations show interactions between a given set of characters over time. Each character is represented by an x-monotone curve. A meeting is represented by a vertical bar that is crossed by the curves of exactly those characters that participate in the meeting. Therefore, character curves may have to cross each other. In the context of publication networks, we consider storylines where the characters are authors and the meetings are joint publications. We are especially interested in visualizing a group of colleagues centered around an author, the protagonist, who participates in all selected publications. For such instances, we propose a drawing style where the protagonist’s curve is drawn at a prominent position and never crossed by any other author’s curve. We consider two variants of storylines with a protagonist. In the one-sided variant, the protagonist is required to be drawn at the top position. In this restricted setting, we can efficiently compute a drawing with the minimum number of pairwise crossings, whereas we show that it is NP-hard to minimize the number of block crossings (i.e., pairs of blocks of parallel curves that intersect each other). In the two-sided variant, the task is to split the set of co-authors of the protagonist into two groups, and to place the curves of one group above and the curves of the other group below the protagonist’s curve such that the total number of (block) crossings is minimized. As our main result, we present an algorithm for bundling a sequence of pairwise crossings into a sequence of few block crossings (in the absence of meetings). It exploits a connection to a rectangle dissection problem. In the presence of meetings, it yields results that are very close to a lower bound. Based on this bundling algorithm and our exact algorithm for the one-sided variant, we present a new heuristic for computing two-sided storylines with few block crossings. We perform an extensive experimental study using publication data of 81 protagonists from GD 2023 and their most frequent collaborators over the last ten years. Our study shows that, for two-sided storylines with a protagonist, our new heuristic uses fewer block crossings (and fewer pairwise crossings) than two heuristics for block crossing minimization in general storylines.
Cite as

Tim Hegemann and Alexander Wolff. Storylines with a Protagonist. In 32nd International Symposium on Graph Drawing and Network Visualization (GD 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 320, pp. 26:1-26:22, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

Copy BibTex To Clipboard

@InProceedings{hegemann_et_al:LIPIcs.GD.2024.26,
  author =	{Hegemann, Tim and Wolff, Alexander},
  title =	{{Storylines with a Protagonist}},
  booktitle =	{32nd International Symposium on Graph Drawing and Network Visualization (GD 2024)},
  pages =	{26:1--26:22},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-343-0},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{320},
  editor =	{Felsner, Stefan and Klein, Karsten},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.GD.2024.26},
  URN =		{urn:nbn:de:0030-drops-213109},
  doi =		{10.4230/LIPIcs.GD.2024.26},
  annote =	{Keywords: Storyline visualization, storyline with a protagonist, crossing minimization, block crossings}
}
Document
Software Abstract
DOI: 10.4230/LIPIcs.GD.2024.58
Graph Harvester (Software Abstract)

Authors: Julius Deynet, Tim Hegemann, Sebastian Kempf, and Alexander Wolff

Published in: LIPIcs, Volume 320, 32nd International Symposium on Graph Drawing and Network Visualization (GD 2024)

Abstract
We present Graph Harvester, a website for extracting graphs from illustrations in scientific papers. For every graph that has been extracted, Graph Harvester queries the graph database House of Graphs. If the graph is not already present there, the user can upload the graph into the database, possibly after modifying it, and with a reference to the paper that contains the drawing of the graph.
Cite as

Julius Deynet, Tim Hegemann, Sebastian Kempf, and Alexander Wolff. Graph Harvester (Software Abstract). In 32nd International Symposium on Graph Drawing and Network Visualization (GD 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 320, pp. 58:1-58:3, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

Copy BibTex To Clipboard

@InProceedings{deynet_et_al:LIPIcs.GD.2024.58,
  author =	{Deynet, Julius and Hegemann, Tim and Kempf, Sebastian and Wolff, Alexander},
  title =	{{Graph Harvester}},
  booktitle =	{32nd International Symposium on Graph Drawing and Network Visualization (GD 2024)},
  pages =	{58:1--58:3},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-343-0},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{320},
  editor =	{Felsner, Stefan and Klein, Karsten},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.GD.2024.58},
  URN =		{urn:nbn:de:0030-drops-213427},
  doi =		{10.4230/LIPIcs.GD.2024.58},
  annote =	{Keywords: House of Graphs, Graph recognition, Information extraction}
}
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
© 2023-2025 Schloss Dagstuhl – LZI GmbH About DROPS Imprint Privacy Contact