07. – 12. April 2019, Dagstuhl-Seminar 19151

Visual Computing in Materials Sciences


Christoph Heinzl (FH Oberösterreich – Wels, AT)
Robert Michael Kirby (University of Utah – Salt Lake City, US)
Stepan V. Lomov (KU Leuven, BE)
Guillermo Requena (DLR – Köln, DE)
Rüdiger Westermann (TU München, DE)

Auskunft zu diesem Dagstuhl-Seminar erteilt

Dagstuhl Service Team


Dagstuhl Report, Volume 9, Issue 4 Dagstuhl Report
Programm des Dagstuhl-Seminars [pdf]


In this Dagstuhl workshop, we brought together computer and computational scientists interested in building tools for use in visual computing with material scientists with expressed interest in using such tools. As would be anticipated when one brings together two distinct fields, the initial challenge we encountered was that of language. Although both groups came together having experiences with visual computing tools - some as developers and some as users - although they often used the same terms, they semantically meant different things. We found that the Dagstuhl philosophy of "immersion" was most helpful to this issue as having several days together helped break down these barriers. Over the course of the week, we interspersed talks by computational scientists and material scientists. The talks by computational scientists often presented their current understanding of what kinds of tools are needed, demonstrations of current tools they have developed in collaboration with domain-specific experts, and success stories of applications they have currently impacted. The talks by the material scientists often presented a description of the tools they currently use, the positive points and deficiencies of current tools, the types of features that they would like to see in future tools, and examples of current challenge problems and how they might be impacted by the next generation of tools.

Fundamental Results:

  1. The systems that are desired by many material scientists will be used both for exploration and for interactive steering. When used for exploration, material scientists want tools that not only present the data with its corresponding reliability (uncertainty) bounds, but which also give predictive capabilities such as where next to sample.
  2. There is a general acknowledgement that both automation and interactivity are needed. Automation of tasks and procedures through AI and Machine Learning can be used to help deal with the volumes of data being produced - helping scientists sift through the field of possibilities to isolate those places for which they should expend human effort. At the same time, there are many current practices that continue to require "the human in the loop" to make decisions. In such cases, tools are needed that have smart defaults but yet allow the user to explore, navigate and possibly refine data.
  3. With regards to visualization scientists, there is a need for both data and tasks. Many researchers requested data on which they can try their methods. In addition to the data itself, descriptors of the data are necessary so that it can be interpreted properly. Once read into their system, the visualization scientists then requested a collection of tasks (driven by the material science domain experts) which would help drive their tool development and evaluation.

Final Comments

Due to the ever-increasing interest in this topic, we foresee that future review articles and/or special issues of journals driven by multilateral research cooperations between seminars' participants will be an outcome of this workshop. To ensure and stimulate further cooperation in this field, a list of specific follow up activities has been elaborated and discussed with the participants. All in all, a fruitful discussion was stimulated across the two domains throughout the complete week of this Dagstuhl workshop which will become more obvious in joint research efforts of all kinds.

Summary text license
  Creative Commons BY 3.0 Unported license
  Christoph Heinzl, Robert Michael Kirby, Stepan V. Lomov, Guillermo Requena, and Rüdiger Westermann


  • Computer Graphics / Computer Vision
  • Data Structures / Algorithms / Complexity
  • Modelling / Simulation


  • Visual Computing
  • Materials Science
  • Visualization / Visual Analysis
  • Data Structures
  • Interaction


In der Reihe Dagstuhl Reports werden alle Dagstuhl-Seminare und Dagstuhl-Perspektiven-Workshops dokumentiert. Die Organisatoren stellen zusammen mit dem Collector des Seminars einen Bericht zusammen, der die Beiträge der Autoren zusammenfasst und um eine Zusammenfassung ergänzt.


Download Übersichtsflyer (PDF).


Es besteht weiterhin die Möglichkeit, eine umfassende Kollektion begutachteter Arbeiten in der Reihe Dagstuhl Follow-Ups zu publizieren.

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