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Documents authored by Archambault, Daniel

Document
DOI: 10.4230/LIPIcs.GD.2024.15
Bundling-Aware Graph Drawing

Authors: Daniel Archambault, Giuseppe Liotta, Martin Nöllenburg, Tommaso Piselli, Alessandra Tappini, and Markus Wallinger

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

Abstract
Edge bundling algorithms significantly improve the visualization of dense graphs by reducing the clutter of many edges visible on screen by bundling them together. As such, bundling is often viewed as a post-processing step applied to a drawing, and the vast majority of edge bundling algorithms consider a graph and its drawing as input. Another way of thinking about edge bundling is to simultaneously optimize both the drawing and the bundling. In this paper, we investigate methods to simultaneously optimize a graph drawing and its bundling. We describe an algorithmic framework which consists of three main steps, namely Filter, Draw, and Bundle. We then propose two alternative implementations and experimentally compare them against the state-of-the-art approach and the simple idea of drawing and subsequently bundling the graph. The experiments confirm that bundled drawings created by our framework outperform previous approaches according to standard quality metrics for edge bundling.
Cite as

Daniel Archambault, Giuseppe Liotta, Martin Nöllenburg, Tommaso Piselli, Alessandra Tappini, and Markus Wallinger. Bundling-Aware Graph Drawing. In 32nd International Symposium on Graph Drawing and Network Visualization (GD 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 320, pp. 15:1-15:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{archambault_et_al:LIPIcs.GD.2024.15,
  author =	{Archambault, Daniel and Liotta, Giuseppe and N\"{o}llenburg, Martin and Piselli, Tommaso and Tappini, Alessandra and Wallinger, Markus},
  title =	{{Bundling-Aware Graph Drawing}},
  booktitle =	{32nd International Symposium on Graph Drawing and Network Visualization (GD 2024)},
  pages =	{15:1--15:19},
  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.2024.15},
  URN =		{urn:nbn:de:0030-drops-212995},
  doi =		{10.4230/LIPIcs.GD.2024.15},
  annote =	{Keywords: Edge Bundling, Experimental Comparison, Graph Sparsification}
}
Document
DOI: 10.4230/DagRep.14.2.191
Reflections on Pandemic Visualization (Dagstuhl Seminar 24091)

Authors: Daniel Archambault, Fintan McGee, Nicolás Reinoso-Schiller, Tatiana von Landesberger, and Simone Scheithauer

Published in: Dagstuhl Reports, Volume 14, Issue 2 (2024)

Abstract
This report documents the program and the outcomes of Dagstuhl Seminar "Reflections on Pandemic Visualization" (24091). The fight against COVID-19 has highlighted the crucial role of data visualization and analytics, prompting significant innovations and collaborations. This Dagstuhl Seminar brought together experts from various fields to reflect on the lessons learned. The aim is to document and disseminate these insights, enhancing preparedness for future global health crises.
Cite as

Daniel Archambault, Fintan McGee, Nicolás Reinoso-Schiller, Tatiana von Landesberger, and Simone Scheithauer. Reflections on Pandemic Visualization (Dagstuhl Seminar 24091). In Dagstuhl Reports, Volume 14, Issue 2, pp. 191-205, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@Article{archambault_et_al:DagRep.14.2.191,
  author =	{Archambault, Daniel and McGee, Fintan and Reinoso-Schiller, Nicol\'{a}s and von Landesberger, Tatiana and Scheithauer, Simone},
  title =	{{Reflections on Pandemic Visualization (Dagstuhl Seminar 24091)}},
  pages =	{191--205},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2024},
  volume =	{14},
  number =	{2},
  editor =	{Archambault, Daniel and McGee, Fintan and Reinoso-Schiller, Nicol\'{a}s and von Landesberger, Tatiana and Scheithauer, Simone},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.14.2.191},
  URN =		{urn:nbn:de:0030-drops-205043},
  doi =		{10.4230/DagRep.14.2.191},
  annote =	{Keywords: Epidemiology, Pandemic, Preparedness, Visualisation}
}
Document
DOI: 10.4230/DagRep.5.11.103
Crowdsourcing and Human-Centred Experiments (Dagstuhl Seminar 15481)

Authors: Daniel Archambault, Tobias Hoßfeld, and Helen C. Purchase

Published in: Dagstuhl Reports, Volume 5, Issue 11 (2016)

Abstract
This report documents the program and the outcomes of Dagstuhl Seminar 15481 "Evaluation in the Crowd: Crowdsourcing and Human-Centred Experiments". Human-centred empirical evaluations play important roles in the fields of human-computer interaction, visualization, graphics, multimedia, and psychology. The advent of crowdsourcing platforms, such as Amazon Mechanical Turk or Microworkers, has provided a revolutionary methodology to conduct human-centred experiments. Through such platforms, experiments can now collect data from hundreds, even thousands, of participants from a diverse user community over a matter of weeks, greatly increasing the ease with which we can collect data as well as the power and generalizability of experimental results. However, such an experimental platform does not come without its problems: ensuring participant investment in the task, defining experimental controls, and understanding the ethics behind deploying such experiments en-masse. The major interests of the seminar participants were focused in different working groups on (W1) Crowdsourcing Technology, (W2) Crowdsourcing Community, (W3) Crowdsourcing vs. Lab, (W4) Crowdsourcing & Visualization, (W5) Crowdsourcing & Psychology, (W6) Crowdsourcing & QoE Assessment.
Cite as

Daniel Archambault, Tobias Hoßfeld, and Helen C. Purchase. Crowdsourcing and Human-Centred Experiments (Dagstuhl Seminar 15481). In Dagstuhl Reports, Volume 5, Issue 11, pp. 103-126, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)

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@Article{archambault_et_al:DagRep.5.11.103,
  author =	{Archambault, Daniel and Ho{\ss}feld, Tobias and Purchase, Helen C.},
  title =	{{Crowdsourcing and Human-Centred Experiments (Dagstuhl Seminar 15481)}},
  pages =	{103--126},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2016},
  volume =	{5},
  number =	{11},
  editor =	{Archambault, Daniel and Ho{\ss}feld, Tobias and Purchase, Helen C.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.5.11.103},
  URN =		{urn:nbn:de:0030-drops-57676},
  doi =		{10.4230/DagRep.5.11.103},
  annote =	{Keywords: Crowdsourcing; Human Computation; Crowdsourcing Design, Mechanisms, Engineering; Practical Experience; Computer Graphics; Applied Perception; HCI; Visualization}
}
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