Issue
Dagstuhl Reports, Volume 11, Issue 9
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Dagstuhl Reports, Volume 11
Journal: Dagstuhl Reports (DagRep)
Publication Details
- published at: 2022-04-11
- Publisher: Schloss Dagstuhl – Leibniz-Zentrum für Informatik
- DBLP: db/journals/dagstuhl-reports/dagstuhl-reports11
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Complete Issue
Dagstuhl Reports, Volume 11, Issue 9, October 2021, Complete Issue
Abstract
Dagstuhl Reports, Volume 11, Issue 9, October 2019, Complete Issue
Cite as
Dagstuhl Reports, Volume 11, Issue 9, pp. 1-121, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)
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@Article{DagRep.11.9,
title = {{Dagstuhl Reports, Volume 11, Issue 9, October 2021, Complete Issue}},
pages = {1--121},
journal = {Dagstuhl Reports},
ISSN = {2192-5283},
year = {2022},
volume = {11},
number = {9},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops-dev.dagstuhl.de/entities/document/10.4230/DagRep.11.9},
URN = {urn:nbn:de:0030-drops-159130},
doi = {10.4230/DagRep.11.9},
annote = {Keywords: Dagstuhl Reports, Volume 11, Issue 9, October 2019, Complete Issue}
}
Document
Front Matter
Dagstuhl Reports, Table of Contents, Volume 11, Issue 9, 2021
Abstract
Dagstuhl Reports, Table of Contents, Volume 11, Issue 9, 2021
Cite as
Dagstuhl Reports, Volume 11, Issue 9, pp. i-ii, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)
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@Article{DagRep.11.9.i,
title = {{Dagstuhl Reports, Table of Contents, Volume 11, Issue 9, 2021}},
pages = {i--ii},
journal = {Dagstuhl Reports},
ISSN = {2192-5283},
year = {2022},
volume = {11},
number = {9},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops-dev.dagstuhl.de/entities/document/10.4230/DagRep.11.9.i},
URN = {urn:nbn:de:0030-drops-159149},
doi = {10.4230/DagRep.11.9.i},
annote = {Keywords: Table of Contents, Frontmatter}
}
Document
Visualization of Biological Data - From Analysis to Communication (Dagstuhl Seminar 21401)
Abstract
Technological advancements in biology allow us to collect and generate a large quantity of data and pose a significant challenge to data interpretation and understanding. Addressing this challenge requires a blend of methodology from data visualization, bioinformatics, and biology. This methodology encompasses perception and design knowledge, algorithm design, techniques for analyzing and visualizing big data, statistical approaches, and specific domain knowledge for different application problems. In particular, it is essential to develop robust and integrative visualization methods combined with computational analytical techniques and approaches to communicate the outcomes visually. The purpose of Dagstuhl Seminar 21401, "Visualization of Biological Data - From Analysis to Communication," was to bring together researchers from various fields to discuss the state of the art, to debate means of advancing science in the field of visualization of biological data, and to foster the development of our international community.
Cite as
Karsten Klein, Georgeta Elisabeta Marai, Kay Katja Nieselt, and Blaz Zupan. Visualization of Biological Data - From Analysis to Communication (Dagstuhl Seminar 21401). In Dagstuhl Reports, Volume 11, Issue 9, pp. 1-27, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)
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@Article{klein_et_al:DagRep.11.9.1,
author = {Klein, Karsten and Marai, Georgeta Elisabeta and Nieselt, Kay Katja and Zupan, Blaz},
title = {{Visualization of Biological Data - From Analysis to Communication (Dagstuhl Seminar 21401)}},
pages = {1--27},
journal = {Dagstuhl Reports},
ISSN = {2192-5283},
year = {2022},
volume = {11},
number = {9},
editor = {Klein, Karsten and Marai, Georgeta Elisabeta and Nieselt, Kay Katja and Zupan, Blaz},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops-dev.dagstuhl.de/entities/document/10.4230/DagRep.11.9.1},
URN = {urn:nbn:de:0030-drops-159158},
doi = {10.4230/DagRep.11.9.1},
annote = {Keywords: Bioinformatics, biology, Imaging, interdisciplinarity, Omics, Visual analytics, visualization}
}
Document
Digital Disinformation: Taxonomy, Impact, Mitigation, and Regulation (Dagstuhl Seminar 21402)
Abstract
We report on the discussions and conclusions of a Dagstuhl seminar focused on digital mis- and disinformation, held in October of 2021. An international and interdisciplinary group of seminar participants considered key technical and societal topics including trustworthiness algorithms (i.e., how to build systems that assess trustworthiness automatically), friction as a technique in platform design (e.g., to slow down people’s consumption of information on social media), the ethics of mis/disinformation interventions, and how to educate users. We detail these discussions and highlight questions for the future.
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Claude Kirchner and Franziska Roesner. Digital Disinformation: Taxonomy, Impact, Mitigation, and Regulation (Dagstuhl Seminar 21402). In Dagstuhl Reports, Volume 11, Issue 9, pp. 28-44, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)
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@Article{kirchner_et_al:DagRep.11.9.28,
author = {Kirchner, Claude and Roesner, Franziska},
title = {{Digital Disinformation: Taxonomy, Impact, Mitigation, and Regulation (Dagstuhl Seminar 21402)}},
pages = {28--44},
journal = {Dagstuhl Reports},
ISSN = {2192-5283},
year = {2022},
volume = {11},
number = {9},
editor = {Kirchner, Claude and Roesner, Franziska},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops-dev.dagstuhl.de/entities/document/10.4230/DagRep.11.9.28},
URN = {urn:nbn:de:0030-drops-159162},
doi = {10.4230/DagRep.11.9.28},
annote = {Keywords: Information, disinformation, misinformation, fake news, deep fake, ethics, trustworthiness, friction, verification}
}
Document
Machine Learning in Sports (Dagstuhl Seminar 21411)
Abstract
Data about sports have long been the subject of research and analysis by sports scientists. The increasing size and availability of these data have also attracted the attention of researchers in machine learning, computer vision and artificial intelligence. However, these communities rarely interact. This seminar aimed to bring together researchers from these areas to spur an interdisciplinary approach to these problems. The seminar was organized around five different themes that were introduced with tutorial and overview style talks about the key concepts to facilitate knowledge exchange among researchers with different backgrounds and approaches to data-based sports research. These were augmented by more in-depth presentations on specific problems or techniques. There was a panel discussion by practitioners on the difficulties and lessons learned about putting analytics into practice. Finally, we came up with a number of conclusions and next steps.
Cite as
Ulf Brefeld, Jesse Davis, Martin Lames, and James J. Little. Machine Learning in Sports (Dagstuhl Seminar 21411). In Dagstuhl Reports, Volume 11, Issue 9, pp. 45-63, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)
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@Article{brefeld_et_al:DagRep.11.9.45,
author = {Brefeld, Ulf and Davis, Jesse and Lames, Martin and Little, James J.},
title = {{Machine Learning in Sports (Dagstuhl Seminar 21411)}},
pages = {45--63},
journal = {Dagstuhl Reports},
ISSN = {2192-5283},
year = {2022},
volume = {11},
number = {9},
editor = {Brefeld, Ulf and Davis, Jesse and Lames, Martin and Little, James J.},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops-dev.dagstuhl.de/entities/document/10.4230/DagRep.11.9.45},
URN = {urn:nbn:de:0030-drops-159178},
doi = {10.4230/DagRep.11.9.45},
annote = {Keywords: machine learning, artificial intelligence, sports science, computer vision, explanations, visualization, tactics, health, biomechanics}
}
Document
Quantum Cryptanalysis (Dagstuhl Seminar 21421)
Abstract
This seminar report documents the program and the outcomes of Dagstuhl Seminar 21421 Quantum Cryptanalysis. The seminar took place in a hybrid format in Fall 2021. The report starts out with the motivation and comments on the organization of this instance of the Dagstuhl Seminar series on {Quantum Cryptanalysis}, followed by abstracts of presentations. The presentation abstracts were provided by seminar participants.
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Stacey Jeffery, Michele Mosca, Maria Naya-Plasencia, and Rainer Steinwandt. Quantum Cryptanalysis (Dagstuhl Seminar 21421). In Dagstuhl Reports, Volume 11, Issue 9, pp. 64-79, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)
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@Article{jeffery_et_al:DagRep.11.9.64,
author = {Jeffery, Stacey and Mosca, Michele and Naya-Plasencia, Maria and Steinwandt, Rainer},
title = {{Quantum Cryptanalysis (Dagstuhl Seminar 21421)}},
pages = {64--79},
journal = {Dagstuhl Reports},
ISSN = {2192-5283},
year = {2022},
volume = {11},
number = {9},
editor = {Jeffery, Stacey and Mosca, Michele and Naya-Plasencia, Maria and Steinwandt, Rainer},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops-dev.dagstuhl.de/entities/document/10.4230/DagRep.11.9.64},
URN = {urn:nbn:de:0030-drops-159187},
doi = {10.4230/DagRep.11.9.64},
annote = {Keywords: computational algebra, post-quantum cryptography, quantum computing, quantum resource estimation}
}
Document
Rigorous Methods for Smart Contracts (Dagstuhl Seminar 21431)
Abstract
This report documents the program and the outcomes of Dagstuhl Seminar 21431 "Rigorous Methods for Smart Contracts". Blockchain technologies have emerged as an exciting field for both researchers and practitioners focusing on formal guarantees for software. It is arguably a "once in a lifetime" opportunity for rigorous methods to be integrated in audit processes for parties deploying smart contracts, whether for fund raising, securities trading, or supply-chain management. Smart contracts are programs managing cryptocurrency accounts on a blockchain. Research in the area of smart contracts includes a fascinating combination of formal methods, programming-language semantics, and cryptography. First, there is vibrant development of verification and program-analysis techniques that check the correctness of smart-contract code. Second, there are emerging designs of programming languages and methodologies for writing smart contracts such that they are more robust by construction or more amenable to analysis and verification. Programming-language abstraction layers expose low-level cryptographic primitives enabling developers to design high-level cryptographic protocols. Automated-reasoning mechanisms present a common underlying enabler; and the specific needs of the smart-contract world offer new challenges. This workshop brought together stakeholders in the aforementioned areas related to advancing reliable smart-contract technologies.
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Nikolaj S. Bjørner, Maria Christakis, Matteo Maffei, and Grigore Rosu. Rigorous Methods for Smart Contracts (Dagstuhl Seminar 21431). In Dagstuhl Reports, Volume 11, Issue 9, pp. 80-101, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)
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@Article{bjrner_et_al:DagRep.11.9.80,
author = {Bj{\o}rner, Nikolaj S. and Christakis, Maria and Maffei, Matteo and Rosu, Grigore},
title = {{Rigorous Methods for Smart Contracts (Dagstuhl Seminar 21431)}},
pages = {80--101},
journal = {Dagstuhl Reports},
ISSN = {2192-5283},
year = {2022},
volume = {11},
number = {9},
editor = {Bj{\o}rner, Nikolaj S. and Christakis, Maria and Maffei, Matteo and Rosu, Grigore},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops-dev.dagstuhl.de/entities/document/10.4230/DagRep.11.9.80},
URN = {urn:nbn:de:0030-drops-159198},
doi = {10.4230/DagRep.11.9.80},
annote = {Keywords: automated reasoning, cryptographic protocols, program verification, programming languages, smart contracts}
}
Document
Probabilistic Numerical Methods - From Theory to Implementation (Dagstuhl Seminar 21432)
Abstract
Numerical methods provide the computational foundation of science, and power automated data analysis and inference in its contemporary form of machine learning. Probabilistic numerical methods aim to explicitly represent uncertainty resulting from limited computational resources and imprecise inputs in these models. With theoretical analysis well underway, software development is now a key next step to wide-spread success. This seminar brought together experts from the forefront of machine learning, statistics and numerical analysis to identify important open problems in the field and to lay the theoretical and practical foundation for a software stack for probabilistic numerical methods.
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Philipp Hennig, Ilse C.F. Ipsen, Maren Mahsereci, and Tim Sullivan. Probabilistic Numerical Methods - From Theory to Implementation (Dagstuhl Seminar 21432). In Dagstuhl Reports, Volume 11, Issue 9, pp. 102-119, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)
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@Article{hennig_et_al:DagRep.11.9.102,
author = {Hennig, Philipp and Ipsen, Ilse C.F. and Mahsereci, Maren and Sullivan, Tim},
title = {{Probabilistic Numerical Methods - From Theory to Implementation (Dagstuhl Seminar 21432)}},
pages = {102--119},
journal = {Dagstuhl Reports},
ISSN = {2192-5283},
year = {2022},
volume = {11},
number = {9},
editor = {Hennig, Philipp and Ipsen, Ilse C.F. and Mahsereci, Maren and Sullivan, Tim},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops-dev.dagstuhl.de/entities/document/10.4230/DagRep.11.9.102},
URN = {urn:nbn:de:0030-drops-159208},
doi = {10.4230/DagRep.11.9.102},
annote = {Keywords: Machine learning, Numerical analysis, Probabilistic numerics}
}