Dagstuhl Reports, Volume 9, Issue 4



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Dagstuhl Reports, Volume 9, Issue 4, April 2019, Complete Issue

Abstract
Dagstuhl Reports, Volume 9, Issue 4, April 2019, Complete Issue

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Dagstuhl Reports, Volume 9, Issue 4, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)


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@Article{DagRep.9.4,
  title =	{{Dagstuhl Reports, Volume 9, Issue 4, April 2019, Complete Issue}},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2019},
  volume =	{9},
  number =	{4},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.9.4},
  URN =		{urn:nbn:de:0030-drops-114530},
  doi =		{10.4230/DagRep.9.4},
  annote =	{Keywords: Dagstuhl Reports, Volume 9, Issue 4, April 2019, Complete Issue}
}
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Front Matter
Dagstuhl Reports, Table of Contents, Volume 9, Issue 4, 2019

Abstract
Dagstuhl Reports, Table of Contents, Volume 9, Issue 4, 2019

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Dagstuhl Reports, Volume 9, Issue 4, pp. i-ii, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)


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@Article{DagRep.9.4.i,
  title =	{{Dagstuhl Reports, Table of Contents, Volume 9, Issue 4, 2019}},
  pages =	{i--ii},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2019},
  volume =	{9},
  number =	{4},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.9.4.i},
  URN =		{urn:nbn:de:0030-drops-114549},
  doi =		{10.4230/DagRep.9.4.i},
  annote =	{Keywords: Table of Contents, Frontmatter}
}
Document
Visual Computing in Materials Sciences (Dagstuhl Seminar 19151)

Authors: Christoph Heinzl, Robert Michael Kirby, Stepan V. Lomov, Guillermo Requena, and Rüdiger Westermann


Abstract
Visual computing has become highly attractive for boosting research endeavors in the materials science domain. Using visual computing, a multitude of different phenomena may now be studied, at various scales, dimensions, or using different modalities. This was simply impossible before. Visual computing techniques generate novel insights to understand, discover, design, and use complex material systems of interest. Its huge potential for retrieving and visualizing (new) information on materials, their characteristics and interrelations as well as on simulating the material's behavior in its target application environment is of core relevance to material scientists. This Dagstuhl seminar on Visual Computing in Materials Sciences thus focuses on the intersection of both domains to guide research endeavors in this field. It targets to provide answers regarding the following four challenges, which are of imminent need: -The Integrated Visual Analysis Challeng identifies standard visualization tools as insufficient for exploring materials science data in detail. What is required are integrated visual analysis tools, which are tailored to a specific application area and guide users in their investigations. Using linked views and other interaction concepts, these tools are required to combine all data domains using meaningful and easy to understand visualization techniques. Especially for the analysis of spatial and temporal data in dynamic processes (e.g., materials tested under load or in different environmental conditions) or multimodal, multiscale data, these tools and techniques are highly anticipated. Only integrated analysis concepts allow to make the most out of all the data available. - The Quantitative Data Visualization Challenge centers around the design and implementation of tailored visual analysis systems for extracting and analyzing derived data (e.g., computed from extracted features over spatial, temporal or even higher dimensional domains). Therefore, feature extraction and quantification techniques, segmentation techniques, or clustering techniques, are required as prerequisites for the targeted visual analysis. As the quantification may easily end up in 25 or more properties to be computed per feature, clustering techniques allow to distinguish features of interest into feature classes. These feature classes may then be statistically evaluated to visualize the properties of the individual features as well as the properties of the different classes. Information visualization techniques will be of special interest for solving this challenge. - The Visual Debugger Challenge is an idea which uses visual analysis to remove errors in the parametrization of a simulation or a data acquisition process. Similarly, to a debugger in computer programming, identifying errors in the code and providing hints to improve, a visual debugger in the domain of visual computing for materials science should show the following characteristics: It should indicate errors and identify wrongly used algorithms in the data analysis. Such a tool should also identify incorrect parameters, which either show no or very limited benefit or even provide erroneous results. Furthermore, it should give directions on how to improve a targeted analysis and suggest suitable algorithms or pipelines for specific tasks. - The Interactive Steering Challenge uses visual analysis tools to control a running simulation or an ongoing data acquisition process. Respective tools monitor costly processes and give directions to improve results regarding the respective targets. For example, in the material analysis domain, this could be a system which provides settings for improved data acquisition based on the current image quality achieved: If the image quality does no more fulfill the target requirements, the system influences all degrees of freedom in the data acquisition to enhance image quality. The same holds for the materials simulation domain. Visual analysis can help to steer target material properties in a specific application environment by predicting tendencies of costly simulation runs, e.g., using cheaper surrogate models.

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Christoph Heinzl, Robert Michael Kirby, Stepan V. Lomov, Guillermo Requena, and Rüdiger Westermann. Visual Computing in Materials Sciences (Dagstuhl Seminar 19151). In Dagstuhl Reports, Volume 9, Issue 4, pp. 1-42, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)


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@Article{heinzl_et_al:DagRep.9.4.1,
  author =	{Heinzl, Christoph and Kirby, Robert Michael and Lomov, Stepan V. and Requena, Guillermo and Westermann, R\"{u}diger},
  title =	{{Visual Computing in Materials Sciences (Dagstuhl Seminar 19151)}},
  pages =	{1--42},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2019},
  volume =	{9},
  number =	{4},
  editor =	{Heinzl, Christoph and Kirby, Robert Michael and Lomov, Stepan V. and Requena, Guillermo and Westermann, R\"{u}diger},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.9.4.1},
  URN =		{urn:nbn:de:0030-drops-113024},
  doi =		{10.4230/DagRep.9.4.1},
  annote =	{Keywords: Data Structures, Interaction, Materials Science, Visual Computing, Visualization / Visual Analysis}
}
Document
Emerging Hardware Techniques and EDA Methodologies for Neuromorphic Computing (Dagstuhl Seminar 19152)

Authors: Krishnendu Chakrabarty, Tsung-Yi Ho, Hai Li, and Ulf Schlichtmann


Abstract
This report documents the program and the outcomes of Dagstuhl Seminar 19152 "Emerging Hardware Techniques and EDA Methodologies for Neuromorphic Computing," which was held during April 7–10, 2019 in Schloss Dagstuhl - Leibniz Center for Informatics. Though interdisciplinary considerations of issues from computer science in the domain of machine learning and large scale computing have already successfully been covered in a series of Dagstuhl seminars, this was the first time that Neuromorphic Computing was brought out as the focus. During the seminar, many of the participants presented their current research on the traditional and emerging hardware techniques, design methodologies, electronic design automation techniques, and application of neuromorphic computing, including ongoing work and open problems. This report documents the abstracts or extended abstracts of the talks presented during the seminar, as well as summaries of the discussion sessions.

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Krishnendu Chakrabarty, Tsung-Yi Ho, Hai Li, and Ulf Schlichtmann. Emerging Hardware Techniques and EDA Methodologies for Neuromorphic Computing (Dagstuhl Seminar 19152). In Dagstuhl Reports, Volume 9, Issue 4, pp. 43-58, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)


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@Article{chakrabarty_et_al:DagRep.9.4.43,
  author =	{Chakrabarty, Krishnendu and Ho, Tsung-Yi and Li, Hai and Schlichtmann, Ulf},
  title =	{{Emerging Hardware Techniques and EDA Methodologies for Neuromorphic Computing (Dagstuhl Seminar 19152)}},
  pages =	{43--58},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2019},
  volume =	{9},
  number =	{4},
  editor =	{Chakrabarty, Krishnendu and Ho, Tsung-Yi and Li, Hai and Schlichtmann, Ulf},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.9.4.43},
  URN =		{urn:nbn:de:0030-drops-113034},
  doi =		{10.4230/DagRep.9.4.43},
  annote =	{Keywords: Neuromorphic computing; nanotechnology; hardware design; electronic design automation; reliability and robustness}
}
Document
Ethics and Trust: Principles, Verification and Validation (Dagstuhl Seminar 19171)

Authors: Michael Fisher, Christian List, Marija Slavkovik, and Astrid Weiss


Abstract
This report documents the programme of, and outcomes from, the Dagstuhl Seminar 19171 on "Ethics and Trust: Principles, Verification and Validation". We consider the issues of ethics and trust as crucial to the future acceptance and use of autonomous systems. The development of new classes of autonomous systems, such as medical robots, "driver-less" cars, and assistive care robots has opened up questions on how we can integrate truly autonomous systems into our society. Once a system is truly autonomous, i.e. learning from interactions, moving and manipulating the world we are living in, and making decisions by itself, we must be certain that it will act in a safe and ethical way, i.e. that it will be able to distinguish 'right' from `wrong' and make the decisions we would expect of it. In order for society to accept these new machines, we must also trust them, i.e. we must believe that they are reliable and that they are trying to assist us, especially when engaged in close human-robot interaction. The seminar focused on questions of how does trust with autonomous machines evolve, how to build a `practical' ethical and trustworthy system, and what are the societal implications. Key issues included: Change of trust and trust repair, AI systems as decision makers, complex system of norms and algorithmic bias, and potential discrepancies between expectations and capabilities of autonomous machines. This workshop was a follow-up to the 2016 Dagstuhl Seminar 16222 on Engineering Moral Agents: From Human Morality to Artificial Morality. When organizing this workshop we aimed to bring together communities of researchers from moral philosophy and from artificial intelligence and extend it with researchers from (social) robotics and human-robot interaction research.

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Michael Fisher, Christian List, Marija Slavkovik, and Astrid Weiss. Ethics and Trust: Principles, Verification and Validation (Dagstuhl Seminar 19171). In Dagstuhl Reports, Volume 9, Issue 4, pp. 59-86, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)


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@Article{fisher_et_al:DagRep.9.4.59,
  author =	{Fisher, Michael and List, Christian and Slavkovik, Marija and Weiss, Astrid},
  title =	{{Ethics and Trust: Principles, Verification and Validation (Dagstuhl Seminar 19171)}},
  pages =	{59--86},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2019},
  volume =	{9},
  number =	{4},
  editor =	{Fisher, Michael and List, Christian and Slavkovik, Marija and Weiss, Astrid},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.9.4.59},
  URN =		{urn:nbn:de:0030-drops-113046},
  doi =		{10.4230/DagRep.9.4.59},
  annote =	{Keywords: Verification, Artificial Morality, Social Robotics, Machine Ethics, Autonomous Systems, Explain-able AI, Safety, Trust, Mathematical Philosophy, Robot Ethics, Human-Robot Interaction}
}
Document
Computational Creativity Meets Digital Literary Studies (Dagstuhl Seminar 19172)

Authors: Tarek Richard Besold, Pablo Gervás, Evelyn Gius, and Sarah Schulz


Abstract
This report documents the outcomes of Dagstuhl Seminar 19172 "Computational Creativity Meets Digital Literary Studies", held from April 22 to April 25, 2019. Computational Creativity and Digital Humanities are emerging, interdisciplinary fields still experiencing significant growth and development in terms of community, research questions, methods, and approaches. Computational Storytelling as a prominent subfield within Computational Creativity that has mostly focused on planning stories - thus simulating a logically coherent plot - could fruitfully extend its horizon to narrative concepts like narrative style, chronology of narratives, focalization and perspective. These narratological concepts have been investigated by literary scholars for a long time. Yet, operationalization of these concepts is required when used as the basis for computational modelling. This in turn sharpens the definitions of theoretical considerations and can feed back into theoretical discussions in the literary studies. Moreover, there are obvious connection points between Computational Creativity and Natural Language Processing on the one hand, and between Natural Language Processing and Digital Literary Studies on the other hand. However, these connections currently are not transitive. The goal of the seminar was to establish international links between all three disciplines and among involved researchers through presentations by participants and extensive group-work sessions.

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Tarek Richard Besold, Pablo Gervás, Evelyn Gius, and Sarah Schulz. Computational Creativity Meets Digital Literary Studies (Dagstuhl Seminar 19172). In Dagstuhl Reports, Volume 9, Issue 4, pp. 87-106, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)


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@Article{besold_et_al:DagRep.9.4.87,
  author =	{Besold, Tarek Richard and Gerv\'{a}s, Pablo and Gius, Evelyn and Schulz, Sarah},
  title =	{{Computational Creativity Meets Digital Literary Studies (Dagstuhl Seminar 19172)}},
  pages =	{87--106},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2019},
  volume =	{9},
  number =	{4},
  editor =	{Besold, Tarek Richard and Gerv\'{a}s, Pablo and Gius, Evelyn and Schulz, Sarah},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.9.4.87},
  URN =		{urn:nbn:de:0030-drops-113054},
  doi =		{10.4230/DagRep.9.4.87},
  annote =	{Keywords: computational creativity, computational narrativity, digital humanities, digital literary studies, storytellin}
}
Document
Computational Geometry (Dagstuhl Seminar 19181)

Authors: Siu-Wing Cheng, Anne Driemel, and Jeff Erickson


Abstract
This report documents the program and the outcomes of Dagstuhl Seminar 19181 "Computational Geometry". The seminar was held from April 28 to May 3, 2019 and 40 participants from various countries attended it. New advances and directions in computational geometry were presented and discussed. The report collects the abstracts of talks and open problems presented in the seminar.

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Siu-Wing Cheng, Anne Driemel, and Jeff Erickson. Computational Geometry (Dagstuhl Seminar 19181). In Dagstuhl Reports, Volume 9, Issue 4, pp. 107-123, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)


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@Article{cheng_et_al:DagRep.9.4.107,
  author =	{Cheng, Siu-Wing and Driemel, Anne and Erickson, Jeff},
  title =	{{Computational Geometry (Dagstuhl Seminar 19181)}},
  pages =	{107--123},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2019},
  volume =	{9},
  number =	{4},
  editor =	{Cheng, Siu-Wing and Driemel, Anne and Erickson, Jeff},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.9.4.107},
  URN =		{urn:nbn:de:0030-drops-113064},
  doi =		{10.4230/DagRep.9.4.107},
  annote =	{Keywords: Computational geometry, polynomial partition, geometric data structures, approximation}
}
Document
Multi-Document Information Consolidation (Dagstuhl Seminar 19182)

Authors: Ido Daga, Iryna Gurevych, Dan Roth, and Amanda Stent


Abstract
This report documents the program and the outcomes of Dagstuhl Seminar 19182 "Multi-Document Information Consolidation". At this 5-day Dagstuhl seminar, an interdisciplinary collection of leading researchers discussed and develop research ideas to address multi-documents in machine learning and NLP systems. In particular, the seminar addressed four major topics: 1) how to represent information in multi-document repositories; 2) how to support inference over multi-document repositories; 3) how to summarize and visualize multi-document repositories for decision support; and 4) how to do information validation on multi-document repositories. General talks as well as topic-specific talks were given to stimulate the discussion between the participants, which lead to various new research ideas.

Cite as

Ido Daga, Iryna Gurevych, Dan Roth, and Amanda Stent. Multi-Document Information Consolidation (Dagstuhl Seminar 19182). In Dagstuhl Reports, Volume 9, Issue 4, pp. 124-139, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)


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@Article{daga_et_al:DagRep.9.4.124,
  author =	{Daga, Ido and Gurevych, Iryna and Roth, Dan and Stent, Amanda},
  title =	{{Multi-Document Information Consolidation (Dagstuhl Seminar 19182)}},
  pages =	{124--139},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2019},
  volume =	{9},
  number =	{4},
  editor =	{Daga, Ido and Gurevych, Iryna and Roth, Dan and Stent, Amanda},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.9.4.124},
  URN =		{urn:nbn:de:0030-drops-113572},
  doi =		{10.4230/DagRep.9.4.124},
  annote =	{Keywords: Information Consolidation, Multi-Document, NLP}
}

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