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Dagstuhl Reports, Volume 6, Issue 4

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  • Dagstuhl Seminars 16141, 16142, 16151 (Perspectives Workshop), 16152 (Perspectives Workshop), 16161, 16162, 16171, 16172

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Document
Complete Issue
DOI: 10.4230/DagRep.6.4
Dagstuhl Reports, Volume 6, Issue 4, April 2016, Complete Issue
Abstract
Dagstuhl Reports, Volume 6, Issue 4, April 2016, Complete Issue
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Dagstuhl Reports, Volume 6, Issue 4, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)

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@Article{DagRep.6.4,
  title =	{{Dagstuhl Reports, Volume 6, Issue 4, April 2016, Complete Issue}},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2016},
  volume =	{6},
  number =	{4},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.6.4},
  URN =		{urn:nbn:de:0030-drops-67290},
  doi =		{10.4230/DagRep.6.4},
  annote =	{Keywords: Dagstuhl Reports, Volume 6, Issue 4, April 2016, Complete Issue}
}
Document
Front Matter
DOI: 10.4230/DagRep.6.4.i
Dagstuhl Reports, Table of Contents, Volume 6, Issue 4, 2016
Abstract
Table of Contents, Frontmatter
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Dagstuhl Reports, Volume 6, Issue 4, pp. i-ii, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)

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@Article{DagRep.6.4.i,
  title =	{{Dagstuhl Reports, Table of Contents, Volume 6, Issue 4, 2016}},
  pages =	{i--ii},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2016},
  volume =	{6},
  number =	{4},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.6.4.i},
  URN =		{urn:nbn:de:0030-drops-67288},
  doi =		{10.4230/DagRep.6.4.i},
  annote =	{Keywords: Dagstuhl Reports, Table of Contents, Volume 6, Issue 4, 2016}
}
Document
DOI: 10.4230/DagRep.6.4.1
Analysis, Interpretation and Benefit of User-Generated Data: Computer Science Meets Communication Studies (Dagstuhl Seminar 16141)

Authors: Thorsten Quandt, German Shegalov, Helle Sjøvaag, and Gottfried Vossen

Abstract
This report documents the program and the outcomes of Dagstuhl Seminar 16141 "Analysis, Interpretation and Benefit of User-Generated Data: Computer Science Meets Communication Studies".
Cite as

Thorsten Quandt, German Shegalov, Helle Sjøvaag, and Gottfried Vossen. Analysis, Interpretation and Benefit of User-Generated Data: Computer Science Meets Communication Studies (Dagstuhl Seminar 16141). In Dagstuhl Reports, Volume 6, Issue 4, pp. 1-15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)

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@Article{quandt_et_al:DagRep.6.4.1,
  author =	{Quandt, Thorsten and Shegalov, German and Sj{\o}vaag, Helle and Vossen, Gottfried},
  title =	{{Analysis, Interpretation and Benefit of User-Generated Data: Computer Science Meets Communication Studies (Dagstuhl Seminar 16141)}},
  pages =	{1--15},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2016},
  volume =	{6},
  number =	{4},
  editor =	{Quandt, Thorsten and Shegalov, German and Sj{\o}vaag, Helle and Vossen, Gottfried},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.6.4.1},
  URN =		{urn:nbn:de:0030-drops-61500},
  doi =		{10.4230/DagRep.6.4.1},
  annote =	{Keywords: Communication Studies, Text Analysis, NLP, Text Mining, Topic Detection, Senitment Analysis, Machine Learning}
}
Document
DOI: 10.4230/DagRep.6.4.16
Multidisciplinary Approaches to Multivalued Data: Modeling, Visualization, Analysis (Dagstuhl Seminar 16142)

Authors: Ingrid Hotz, Evren Özarslan, and Thomas Schultz

Abstract
This report documents the program and the outcomes of Dagstuhl Seminar 16142, "Multidisciplinary Approaches to Multivalued Data: Modelling, Visualization, Analysis", which was attended by 27 international researchers, both junior and senior. Modelling multivalued data using tensors and higher-order descriptors has become common practice in neuroscience, engineering, and medicine. Novel tools for image analysis, visualization, as well as statistical hypothesis testing and machine learning are required to extract value from such data, and can only be developed within multidisciplinary collaborations. This report gathers abstracts of the talks held by participants on recent advances and open questions related to these challenges, as well as an account of topics raised within two of the breakout sessions.
Cite as

Ingrid Hotz, Evren Özarslan, and Thomas Schultz. Multidisciplinary Approaches to Multivalued Data: Modeling, Visualization, Analysis (Dagstuhl Seminar 16142). In Dagstuhl Reports, Volume 6, Issue 4, pp. 16-38, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)

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@Article{hotz_et_al:DagRep.6.4.16,
  author =	{Hotz, Ingrid and \"{O}zarslan, Evren and Schultz, Thomas},
  title =	{{Multidisciplinary Approaches to Multivalued Data: Modeling, Visualization, Analysis (Dagstuhl Seminar 16142)}},
  pages =	{16--38},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2016},
  volume =	{6},
  number =	{4},
  editor =	{Hotz, Ingrid and \"{O}zarslan, Evren and Schultz, Thomas},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.6.4.16},
  URN =		{urn:nbn:de:0030-drops-61517},
  doi =		{10.4230/DagRep.6.4.16},
  annote =	{Keywords: visualization, image processing, statistical analysis, machine learning, tensor fields, higher-order descriptors, diffusion-weighted imaging (DWI), structural mechanics, fluid dynamics, microstructure imaging, connectomics, uncertainty visualization, feature extraction}
}
Document
DOI: 10.4230/DagRep.6.4.39
Foundations of Data Management (Dagstuhl Perspectives Workshop 16151)

Authors: Marcelo Arenas, Richard Hull, Wim Marten, Tova Milo, and Thomas Schwentick

Abstract
In this Workshop we have explored the degree to which principled foundations are crucial to the long-term success and effectiveness of the new generation of data management paradigms and applications, and investigated what forms of research need to be pursued to develop and advance these foundations. The workshop brought together specialists from the existing database theory community, and from adjoining areas, particularly from various subdisciplines within the Big Data community, to understand the challenge areas that might be resolved through principled foundations and mathematical theory.
Cite as

Marcelo Arenas, Richard Hull, Wim Marten, Tova Milo, and Thomas Schwentick. Foundations of Data Management (Dagstuhl Perspectives Workshop 16151). In Dagstuhl Reports, Volume 6, Issue 4, pp. 39-56, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)

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@Article{arenas_et_al:DagRep.6.4.39,
  author =	{Arenas, Marcelo and Hull, Richard and Marten, Wim and Milo, Tova and Schwentick, Thomas},
  title =	{{Foundations of Data Management (Dagstuhl Perspectives Workshop 16151)}},
  pages =	{39--56},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2016},
  volume =	{6},
  number =	{4},
  editor =	{Arenas, Marcelo and Hull, Richard and Marten, Wim and Milo, Tova and Schwentick, Thomas},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.6.4.39},
  URN =		{urn:nbn:de:0030-drops-61526},
  doi =		{10.4230/DagRep.6.4.39},
  annote =	{Keywords: Foundations of data management, Principles of databases}
}
Document
DOI: 10.4230/DagRep.6.4.57
Tensor Computing for Internet of Things (Dagstuhl Perspectives Workshop 16152)

Authors: Avrim Acar, Animashree Anandkumar, Lenore Mullin, Sebnem Rusitschka, and Volker Tresp

Abstract
This report documents the program and the outcomes of Dagstuhl Perspectives Workshop 16152 "Tensor Computing for Internet of Things". In an interactive three-day workshop industrial and academic researchers exchanged their multidisciplinary perspectives through impulse talks, panel discussions, and break-out sessions. Internet of Things (IoT) or Cyber-physical systems (CPS) bring out interesting new challenges to tensor computing, such as the need for real-time analytics and control in interconnected dynamic networks, e.g. electricity, transportation, manufacturing. On the other hand, IoT/CPS have characteristics that make tensor methods applicable to extract information very efficiently. During our discussions we identified an action plan to have a structured approach that will enable the multidisciplinary community of domain and control experts, data scientists, and distributed, embedded software developers to share knowledge and best practices, compare and exchange tensor models depending on data types and applications in distinct IoT/CPS scenarios.
Cite as

Avrim Acar, Animashree Anandkumar, Lenore Mullin, Sebnem Rusitschka, and Volker Tresp. Tensor Computing for Internet of Things (Dagstuhl Perspectives Workshop 16152). In Dagstuhl Reports, Volume 6, Issue 4, pp. 57-79, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)

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@Article{acar_et_al:DagRep.6.4.57,
  author =	{Acar, Avrim and Anandkumar, Animashree and Mullin, Lenore and Rusitschka, Sebnem and Tresp, Volker},
  title =	{{Tensor Computing for Internet of Things (Dagstuhl Perspectives Workshop 16152)}},
  pages =	{57--79},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2016},
  volume =	{6},
  number =	{4},
  editor =	{Acar, Avrim and Anandkumar, Animashree and Mullin, Lenore and Rusitschka, Sebnem and Tresp, Volker},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.6.4.57},
  URN =		{urn:nbn:de:0030-drops-66912},
  doi =		{10.4230/DagRep.6.4.57},
  annote =	{Keywords: Tensor Methods, Multi-way Data Analysis, Multi-linear Algebra, Tensor Software, Distributed \backslash\& Parallel Computing, Big Data Computing \& Analytics, Cyber-physical Systems, Intelligent Autonomous Systems, Applications in Smart Grid, Mobility, Smart City}
}
Document
DOI: 10.4230/DagRep.6.4.80
Natural Language Argumentation: Mining, Processing, and Reasoning over Textual Arguments (Dagstuhl Seminar 16161)

Authors: Elena Cabrio, Graeme Hirst, Serena Villata, and Adam Wyner

Abstract
This report documents the program and the outcomes of Dagstuhl Seminar 16161 "Natural Language Argumentation: Mining, Processing, and Reasoning over Textual Arguments", 17--22 April 2016. The seminar brought together leading researchers from computational linguistics, argumentation theory and cognitive psychology communities to discuss the obtained results and the future challenges of the recently born Argument Mining research area. 40 participants from 14 different countries took part in 7 sessions that included 30 talks, two tutorials, and a hands-on “unshared” task.
Cite as

Elena Cabrio, Graeme Hirst, Serena Villata, and Adam Wyner. Natural Language Argumentation: Mining, Processing, and Reasoning over Textual Arguments (Dagstuhl Seminar 16161). In Dagstuhl Reports, Volume 6, Issue 4, pp. 80-109, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)

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@Article{cabrio_et_al:DagRep.6.4.80,
  author =	{Cabrio, Elena and Hirst, Graeme and Villata, Serena and Wyner, Adam},
  title =	{{Natural Language Argumentation: Mining, Processing, and Reasoning over Textual Arguments (Dagstuhl Seminar 16161)}},
  pages =	{80--109},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2016},
  volume =	{6},
  number =	{4},
  editor =	{Cabrio, Elena and Hirst, Graeme and Villata, Serena and Wyner, Adam},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.6.4.80},
  URN =		{urn:nbn:de:0030-drops-66923},
  doi =		{10.4230/DagRep.6.4.80},
  annote =	{Keywords: Argument Mining, Argumentation Theory, Cognitive Science, Computational Linguistics}
}
Document
DOI: 10.4230/DagRep.6.4.110
Managing Technical Debt in Software Engineering (Dagstuhl Seminar 16162)

Authors: Paris Avgeriou, Philippe Kruchten, Ipek Ozkaya, and Carolyn Seaman

Abstract
This report documents the program and outcomes of Dagstuhl Seminar 16162, “Managing Technical Debt in Software Engineering.” We summarize the goals and format of the seminar, results from the breakout groups, a definition for technical debt, a draft conceptual model, and a research road map that culminated from the discussions during the seminar. The report also includes the abstracts of the talks presented at the seminar and summaries of open discussions.
Cite as

Paris Avgeriou, Philippe Kruchten, Ipek Ozkaya, and Carolyn Seaman. Managing Technical Debt in Software Engineering (Dagstuhl Seminar 16162). In Dagstuhl Reports, Volume 6, Issue 4, pp. 110-138, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)

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@Article{avgeriou_et_al:DagRep.6.4.110,
  author =	{Avgeriou, Paris and Kruchten, Philippe and Ozkaya, Ipek and Seaman, Carolyn},
  title =	{{Managing Technical Debt in Software Engineering (Dagstuhl Seminar 16162)}},
  pages =	{110--138},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2016},
  volume =	{6},
  number =	{4},
  editor =	{Avgeriou, Paris and Kruchten, Philippe and Ozkaya, Ipek and Seaman, Carolyn},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.6.4.110},
  URN =		{urn:nbn:de:0030-drops-66938},
  doi =		{10.4230/DagRep.6.4.110},
  annote =	{Keywords: coding tools and techniques, design tools and techniques, management, metrics, software engineering}
}
Document
DOI: 10.4230/DagRep.6.4.139
Algorithmic Methods for Optimization in Public Transport (Dagstuhl Seminar 16171)

Authors: Leo G. Kroon, Anita Schöbel, and Dorothea Wagner

Abstract
This report documents the talks and discussions at the Dagstuhl seminar 16171 “Algorithmic Methods for Optimization in Public Transport”. The seminar brought together researchers from algorithm, algorithm engineering, operations research, mathematical optimization and engineering, all interested in algorithms in public transportation. Also several practitioners were able to join the group and brought valuable insights on current practice and challenging problems.
Cite as

Leo G. Kroon, Anita Schöbel, and Dorothea Wagner. Algorithmic Methods for Optimization in Public Transport (Dagstuhl Seminar 16171). In Dagstuhl Reports, Volume 6, Issue 4, pp. 139-160, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)

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@Article{kroon_et_al:DagRep.6.4.139,
  author =	{Kroon, Leo G. and Sch\"{o}bel, Anita and Wagner, Dorothea},
  title =	{{Algorithmic Methods for Optimization in Public Transport (Dagstuhl Seminar 16171)}},
  pages =	{139--160},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2016},
  volume =	{6},
  number =	{4},
  editor =	{Kroon, Leo G. and Sch\"{o}bel, Anita and Wagner, Dorothea},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.6.4.139},
  URN =		{urn:nbn:de:0030-drops-66949},
  doi =		{10.4230/DagRep.6.4.139},
  annote =	{Keywords: delay and disruption management, dynamic passenger information, public transportation, resource scheduling, timetabling}
}
Document
DOI: 10.4230/DagRep.6.4.161
Machine Learning for Dynamic Software Analysis: Potentials and Limits (Dagstuhl Seminar 16172)

Authors: Amel Bennaceur, Dimitra Giannakopoulou, Reiner Hähnle, and Karl Meinke

Abstract
This report documents the program and the outcomes of Dagstuhl Seminar 16172 "Machine Learning for Dynamic Software Analysis: Potentials and Limits". Machine learning is a powerful paradigm for software analysis that provides novel approaches to automating the generation of models and other essential artefacts. This Dagstuhl Seminar brought together top researchers active in the fields of machine learning and software analysis to have a better understanding of the synergies between these fields and suggest new directions and collaborations for future research.
Cite as

Amel Bennaceur, Dimitra Giannakopoulou, Reiner Hähnle, and Karl Meinke. Machine Learning for Dynamic Software Analysis: Potentials and Limits (Dagstuhl Seminar 16172). In Dagstuhl Reports, Volume 6, Issue 4, pp. 161-173, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)

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@Article{bennaceur_et_al:DagRep.6.4.161,
  author =	{Bennaceur, Amel and Giannakopoulou, Dimitra and H\"{a}hnle, Reiner and Meinke, Karl},
  title =	{{Machine Learning for Dynamic Software Analysis: Potentials and Limits (Dagstuhl Seminar 16172)}},
  pages =	{161--173},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2016},
  volume =	{6},
  number =	{4},
  editor =	{Bennaceur, Amel and Giannakopoulou, Dimitra and H\"{a}hnle, Reiner and Meinke, Karl},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.6.4.161},
  URN =		{urn:nbn:de:0030-drops-66954},
  doi =		{10.4230/DagRep.6.4.161},
  annote =	{Keywords: Machine learning, Automata learning, Software analysis, Dynamic analysis, Testing, Model extraction, Systems integration}
}

Filters

  • Authors
  • A
  • Acar, Avrim
  • Anandkumar, Animashree
  • Arenas, Marcelo
  • Avgeriou, Paris
  • B
  • Bennaceur, Amel
  • C
  • Cabrio, Elena
  • G
  • Giannakopoulou, Dimitra
  • H
  • Hähnle, Reiner
  • Hirst, Graeme
  • Hotz, Ingrid
  • Hull, Richard
  • K
  • Kroon, Leo G.
  • Kruchten, Philippe
  • M
  • Marten, Wim
  • Meinke, Karl
  • Milo, Tova
  • Mullin, Lenore
  • O
  • Özarslan, Evren
  • Ozkaya, Ipek
  • Q
  • Quandt, Thorsten
  • R
  • Rusitschka, Sebnem
  • S
  • Schöbel, Anita
  • Schultz, Thomas
  • Schwentick, Thomas
  • Seaman, Carolyn
  • Shegalov, German
  • Sjøvaag, Helle
  • T
  • Tresp, Volker
  • V
  • Villata, Serena
  • Vossen, Gottfried
  • W
  • Wagner, Dorothea
  • Wyner, Adam

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