Issue
Dagstuhl Reports, Volume 13, Issue 1
-
Part of:
Volume:
Dagstuhl Reports, Volume 13
Journal: Dagstuhl Reports (DagRep)
Event
Dagstuhl Seminars 23021, 23022, 23031, 23041, 23042, 23051Publication Details
- published at: 2023-09-18
- Publisher: Schloss Dagstuhl – Leibniz-Zentrum für Informatik
- DBLP: db/journals/dagstuhl-reports/dagstuhl-reports13
Access Numbers
- Detailed Access Statistics available here
-
Total Document Accesses (updated on a weekly basis):
0PDF Downloads
Documents
No documents found matching your filter selection.
Document
Complete Issue
Dagstuhl Reports, Volume 13, Issue 1, January 2023, Complete Issue
Abstract
Dagstuhl Reports, Volume 13, Issue 1, January 2023, Complete Issue
Cite as
Dagstuhl Reports, Volume 13, Issue 1, pp. 1-246, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)
Copy BibTex To Clipboard
@Article{DagRep.13.1,
title = {{Dagstuhl Reports, Volume 13, Issue 1, January 2023, Complete Issue}},
pages = {1--246},
journal = {Dagstuhl Reports},
ISSN = {2192-5283},
year = {2023},
volume = {13},
number = {1},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/DagRep.13.1},
URN = {urn:nbn:de:0030-drops-191150},
doi = {10.4230/DagRep.13.1},
annote = {Keywords: Dagstuhl Reports, Volume 13, Issue 1, January 2023, Complete Issue}
}
Document
Front Matter
Dagstuhl Reports, Table of Contents, Volume 13, Issue 1, 2023
Abstract
Dagstuhl Reports, Table of Contents, Volume 13, Issue 1, 2023
Cite as
Dagstuhl Reports, Volume 13, Issue 1, pp. i-ii, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)
Copy BibTex To Clipboard
@Article{DagRep.13.1.i,
title = {{Dagstuhl Reports, Table of Contents, Volume 13, Issue 1, 2023}},
pages = {i--ii},
journal = {Dagstuhl Reports},
ISSN = {2192-5283},
year = {2023},
volume = {13},
number = {1},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/DagRep.13.1.i},
URN = {urn:nbn:de:0030-drops-191168},
doi = {10.4230/DagRep.13.1.i},
annote = {Keywords: Table of Contents, Frontmatter}
}
Document
Media Forensics and the Challenge of Big Data (Dagstuhl Seminar 23021)
Abstract
With demanding and sophisticated crimes and terrorist threats becoming more pervasive, allied with the advent and widespread of fake news, it becomes paramount to design and develop objective and scientific-based criteria to identify the characteristics of investigated materials associated with potential criminal activities. We need effective approaches to help us answer the four most important questions in forensics regarding an event: "who," "in what circumstances," "why," and "how." In recent years, the rise of social media has resulted in a flood of media content. As well as providing a challenge due to the increase in data that needs fact-checking, it also allows leveraging big-data techniques for forensic analysis.
The seminar included sessions on traditional, deep learning-based methods, big data, benchmark and performance evaluation, applications, and future directions. It aimed to orchestrate the research community’s efforts in such a way that we harness different tools to fight misinformation and the spread of fake content.
Cite as
Irene Amerini, Anderson Rocha, Paul L. Rosin, and Xianfang Sun. Media Forensics and the Challenge of Big Data (Dagstuhl Seminar 23021). In Dagstuhl Reports, Volume 13, Issue 1, pp. 1-35, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)
Copy BibTex To Clipboard
@Article{amerini_et_al:DagRep.13.1.1,
author = {Amerini, Irene and Rocha, Anderson and Rosin, Paul L. and Sun, Xianfang},
title = {{Media Forensics and the Challenge of Big Data (Dagstuhl Seminar 23021)}},
pages = {1--35},
journal = {Dagstuhl Reports},
ISSN = {2192-5283},
year = {2023},
volume = {13},
number = {1},
editor = {Amerini, Irene and Rocha, Anderson and Rosin, Paul L. and Sun, Xianfang},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/DagRep.13.1.1},
URN = {urn:nbn:de:0030-drops-191177},
doi = {10.4230/DagRep.13.1.1},
annote = {Keywords: Digital forensics, Image and video authentication, Image and video forensics, Image and video forgery detection, Tampering detection}
}
Document
Inverse Biophysical Modeling and Machine Learning in Personalized Oncology (Dagstuhl Seminar 23022)
Abstract
This report documents the program and the outcomes of Dagstuhl Seminar 23022 "Inverse Biophysical Modeling and Machine Learning in Personalized Oncology".
This seminar brought together leading experts in mathematical, computational, and medical imaging sciences with research interests in data science, scientific machine learning, modeling and numerical simulation, optimization, and statistical and deterministic inversion, and image analysis with applications in medical imaging, and, in particular, oncology. A central theme of the seminar was the integration of data-driven methods with model-driven approaches for predictive modeling.
The seminar had several main thrusts including design and analysis of novel mathematical models, recent developments in medical imaging, machine learning in the context data analytics and data-driven model prediction, predictive computational modeling through (statistical) inversion, integration of machine learning with model-based priors and use of these methods to aid decision-making. We discussed these topics through the lens of foundational algorithmic complications and mathematical and computational challenges. The participants explored how advances in the applied sciences (e.g., data analytics, medical imaging, or radiomics) can aid us to tackle challenges in the application domain. We also discussed the significant challenges associated with the validation of the proposed methodology, and a lack of reproducibility due to the absence of standard protocols for validation of data- and model-driven methods by translational research groups.
Cite as
George Biros, Andreas Mang, Björn H. Menze, and Miriam Schulte. Inverse Biophysical Modeling and Machine Learning in Personalized Oncology (Dagstuhl Seminar 23022). In Dagstuhl Reports, Volume 13, Issue 1, pp. 36-67, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)
Copy BibTex To Clipboard
@Article{biros_et_al:DagRep.13.1.36,
author = {Biros, George and Mang, Andreas and Menze, Bj\"{o}rn H. and Schulte, Miriam},
title = {{Inverse Biophysical Modeling and Machine Learning in Personalized Oncology (Dagstuhl Seminar 23022)}},
pages = {36--67},
journal = {Dagstuhl Reports},
ISSN = {2192-5283},
year = {2023},
volume = {13},
number = {1},
editor = {Biros, George and Mang, Andreas and Menze, Bj\"{o}rn H. and Schulte, Miriam},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/DagRep.13.1.36},
URN = {urn:nbn:de:0030-drops-191189},
doi = {10.4230/DagRep.13.1.36},
annote = {Keywords: Bayesian inverse problems, image segmentation, inverse problems, machine learning, medical image analysis, parallel computing, tumor growth simulation and modeling}
}
Document
Frontiers of Information Access Experimentation for Research and Education (Dagstuhl Seminar 23031)
Abstract
This report documents the program and the outcomes of Dagstuhl Seminar 23031 "Frontiers of Information Access Experimentation for Research and Education", which brought together 37 participants from 12 countries.
The seminar addressed technology-enhanced information access (information retrieval, recommender systems, natural language processing) and specifically focused on developing more responsible experimental practices leading to more valid results, both for research as well as for scientific education.
The seminar brought together experts from various sub-fields of information access, namely Information Retrieval (IR), Recommender Systems (RS), Natural Language Processing (NLP), information science, and human-computer interaction to create a joint understanding of the problems and challenges presented by next generation information access systems, from both the research and the experimentation point of views, to discuss existing solutions and impediments, and to propose next steps to be pursued in the area in order to improve not also our research methods and findings but also the education of the new generation of researchers and developers.
The seminar featured a series of long and short talks delivered by participants, who helped in setting a common ground and in letting emerge topics of interest to be explored as the main output of the seminar. This led to the definition of five groups which investigated challenges, opportunities, and next steps in the following areas: reality check, i.e. conducting real-world studies, human–machine-collaborative relevance judgment frameworks, overcoming methodological challenges in information retrieval and recommender systems through awareness and education, results-blind reviewing, and guidance for authors.
Cite as
Christine Bauer, Ben Carterette, Nicola Ferro, Norbert Fuhr, and Guglielmo Faggioli. Frontiers of Information Access Experimentation for Research and Education (Dagstuhl Seminar 23031). In Dagstuhl Reports, Volume 13, Issue 1, pp. 68-154, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)
Copy BibTex To Clipboard
@Article{bauer_et_al:DagRep.13.1.68,
author = {Bauer, Christine and Carterette, Ben and Ferro, Nicola and Fuhr, Norbert and Faggioli, Guglielmo},
title = {{Frontiers of Information Access Experimentation for Research and Education (Dagstuhl Seminar 23031)}},
pages = {68--154},
journal = {Dagstuhl Reports},
ISSN = {2192-5283},
year = {2023},
volume = {13},
number = {1},
editor = {Bauer, Christine and Carterette, Ben and Ferro, Nicola and Fuhr, Norbert and Faggioli, Guglielmo},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/DagRep.13.1.68},
URN = {urn:nbn:de:0030-drops-191199},
doi = {10.4230/DagRep.13.1.68},
annote = {Keywords: evaluation, experimentation, information access systems, simulation, user interaction}
}
Document
Integrated Rigorous Analysis in Cyber-Physical Systems Engineering (Dagstuhl Seminar 23041)
Abstract
This report documents the program and the outcomes of the Dagstuhl Seminar 23041 "Integrated Rigorous Analysis in Cyber-Physical Systems (CPS) Engineering".
This seminar brought together academic and industry representations from a variety of domains with backgrounds in different techniques to develop a roadmap for addressing the current challenges in the area of CPS engineering. An overarching theme was the potential use of integrated models and associated methodologies that support cross-technique information/results sharing and smooth workflow hand-offs between individual tools and methods.
Cite as
Erika Abraham, Stefan Hallerstede, John Hatcliff, Danielle Stewart, and Noah Abou El Wafa. Integrated Rigorous Analysis in Cyber-Physical Systems Engineering (Dagstuhl Seminar 23041). In Dagstuhl Reports, Volume 13, Issue 1, pp. 155-183, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)
Copy BibTex To Clipboard
@Article{abraham_et_al:DagRep.13.1.155,
author = {Abraham, Erika and Hallerstede, Stefan and Hatcliff, John and Stewart, Danielle and Wafa, Noah Abou El},
title = {{Integrated Rigorous Analysis in Cyber-Physical Systems Engineering (Dagstuhl Seminar 23041)}},
pages = {155--183},
journal = {Dagstuhl Reports},
ISSN = {2192-5283},
year = {2023},
volume = {13},
number = {1},
editor = {Abraham, Erika and Hallerstede, Stefan and Hatcliff, John and Stewart, Danielle and Wafa, Noah Abou El},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/DagRep.13.1.155},
URN = {urn:nbn:de:0030-drops-191209},
doi = {10.4230/DagRep.13.1.155},
annote = {Keywords: cyber-physical systems, formal methods, rigorous modelling and analysis, systems engineering}
}
Document
Quality of Sustainable Experience (QoSE) (Dagstuhl Seminar 23042)
Abstract
This report documents the program and the outcomes of Dagstuhl Seminar 23042 "Quality of Sustainable Experience (QoSE)". The seminar aimed to bring together people from different fields, perspectives and backgrounds. The participants discussed how experiences - as the main selling point of products and services – in various ICT-related domains can be made more sustainable, how they can contribute to relevant sustainable development goals, and how the quality and degree of sustainability of such experiences may be evaluated and be better understood. The main objectives of the seminar were to foster new alliances, to inspire, to trigger scientific renewal, as well as to identify future opportunities and research challenges through a hands-on approach.
Cite as
Katrien De Moor, Markus Fiedler, Ashok Jhunjhunwala, and Alexander Raake. Quality of Sustainable Experience (QoSE) (Dagstuhl Seminar 23042). In Dagstuhl Reports, Volume 13, Issue 1, pp. 184-215, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)
Copy BibTex To Clipboard
@Article{demoor_et_al:DagRep.13.1.184,
author = {De Moor, Katrien and Fiedler, Markus and Jhunjhunwala, Ashok and Raake, Alexander},
title = {{Quality of Sustainable Experience (QoSE) (Dagstuhl Seminar 23042)}},
pages = {184--215},
journal = {Dagstuhl Reports},
ISSN = {2192-5283},
year = {2023},
volume = {13},
number = {1},
editor = {De Moor, Katrien and Fiedler, Markus and Jhunjhunwala, Ashok and Raake, Alexander},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/DagRep.13.1.184},
URN = {urn:nbn:de:0030-drops-191212},
doi = {10.4230/DagRep.13.1.184},
annote = {Keywords: Design for Sustainability, Digitalisation, Human-Computer Interaction, Information and Communication Technology, Wellbeing}
}
Document
Perception in Network Visualization (Dagstuhl Seminar 23051)
Abstract
Networks are used to model and represent data in many application areas from life sciences to social sciences. Visual network analysis is a crucial tool to improve the understanding of data sets and processes over many levels of complexity, such as different semantic, spatial and temporal granularities. While there is a great deal of work on the algorithmic aspects of network visualization and the computational complexity of the underlying problems, the role and limits of human perception are rarely explicitly investigated and taken into account when designing network visualizations. To address this issue, this Dagstuhl Seminar raised awareness in the network visualization community of the need for more extensive theoretical and empirical understanding of how people perceive and make sense of network visualizations and the significant potential for improving current solutions when perception-based strategies are employed. Likewise, the seminar increased awareness in the perception community that challenges in network research can drive new questions for perception research, for example, in identifying features and patterns in large, often time-varying networks. We brought together researchers from several different communities to initiate a dialogue, foster exchange, discuss the state of the art at this intersection and within the respective fields, identify promising research questions and directions, and start working on selected problems.
Cite as
Karsten Klein, Stephen Kobourov, Bernice E. Rogowitz, Danielle Szafir, and Jacob Miller. Perception in Network Visualization (Dagstuhl Seminar 23051). In Dagstuhl Reports, Volume 13, Issue 1, pp. 216-244, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)
Copy BibTex To Clipboard
@Article{klein_et_al:DagRep.13.1.216,
author = {Klein, Karsten and Kobourov, Stephen and Rogowitz, Bernice E. and Szafir, Danielle and Miller, Jacob},
title = {{Perception in Network Visualization (Dagstuhl Seminar 23051)}},
pages = {216--244},
journal = {Dagstuhl Reports},
ISSN = {2192-5283},
year = {2023},
volume = {13},
number = {1},
editor = {Klein, Karsten and Kobourov, Stephen and Rogowitz, Bernice E. and Szafir, Danielle and Miller, Jacob},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/DagRep.13.1.216},
URN = {urn:nbn:de:0030-drops-191220},
doi = {10.4230/DagRep.13.1.216},
annote = {Keywords: Network Visualization, Graph Drawing, Perception, Cognition}
}