Issue

Dagstuhl Manifestos, Volume 7, Issue 1

Thumbnail PDF

Publication Details


Access Numbers

Documents

No documents found matching your filter selection.
Document
Complete Issue
DOI: 10.4230/DagMan.7.1
Dagstuhl Manifestos, Volume 7, Issue 1, January - December 2018, Complete Issue
Abstract
Dagstuhl Manifestos, Volume 7, Issue 1, January - December 2018, Complete Issue
Cite as

Dagstuhl Manifestos, Volume 7, Issue 1, pp. 1-141, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)

Copy BibTex To Clipboard

@Article{DagMan.7.1,
  title =	{{Dagstuhl Manifestos, Volume 7, Issue 1, January - December 2018, Complete Issue}},
  pages =	{1--141},
  journal =	{Dagstuhl Manifestos},
  ISSN =	{2193-2433},
  year =	{2019},
  volume =	{7},
  number =	{1},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagMan.7.1},
  URN =		{urn:nbn:de:0030-drops-101808},
  doi =		{10.4230/DagMan.7.1},
  annote =	{Keywords: Dagstuhl Manifestos, Volume 7, Issue 1, January - December 2018, Complete Issue}
}
Document
Front Matter
DOI: 10.4230/DagMan.7.1.i
Dagstuhl Manifestos, Table of Contents, Volume 7, Issue 1, 2018
Abstract
Dagstuhl Manifestos, Table of Contents, Volume 7, Issue 1, 2018
Cite as

Dagstuhl Manifestos, Volume 7, Issue 1, pp. i-ii, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)

Copy BibTex To Clipboard

@Article{DagMan.7.1.i,
  title =	{{Dagstuhl Manifestos, Table of Contents, Volume 7, Issue 1, 2018}},
  pages =	{i--ii},
  journal =	{Dagstuhl Manifestos},
  ISSN =	{2193-2433},
  year =	{2019},
  volume =	{7},
  number =	{1},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagMan.7.1.i},
  URN =		{urn:nbn:de:0030-drops-101795},
  doi =		{10.4230/DagMan.7.1.i},
  annote =	{Keywords: Dagstuhl Manifestos, Table of Contents, Volume 7, Issue 1, 2018}
}
Document
DOI: 10.4230/DagMan.7.1.1
Research Directions for Principles of Data Management (Dagstuhl Perspectives Workshop 16151)

Authors: Serge Abiteboul, Marcelo Arenas, Pablo Barceló, Meghyn Bienvenu, Diego Calvanese, Claire David, Richard Hull, Eyke Hüllermeier, Benny Kimelfeld, Leonid Libkin, Wim Martens, Tova Milo, Filip Murlak, Frank Neven, Magdalena Ortiz, Thomas Schwentick, Julia Stoyanovich, Jianwen Su, Dan Suciu, Victor Vianu, and Ke Yi

Abstract
The area of Principles of Data Management (PDM) has made crucial contributions to the development of formal frameworks for understanding and managing data and knowledge. This work has involved a rich cross-fertilization between PDM and other disciplines in mathematics and computer science, including logic, complexity theory, and knowledge representation. We anticipate on-going expansion of PDM research as the technology and applications involving data management continue to grow and evolve. In particular, the lifecycle of Big Data Analytics raises a wealth of challenge areas that PDM can help with. In this report we identify some of the most important research directions where the PDM community has the potential to make significant contributions. This is done from three perspectives: potential practical relevance, results already obtained, and research questions that appear surmountable in the short and medium term.
Cite as

Serge Abiteboul, Marcelo Arenas, Pablo Barceló, Meghyn Bienvenu, Diego Calvanese, Claire David, Richard Hull, Eyke Hüllermeier, Benny Kimelfeld, Leonid Libkin, Wim Martens, Tova Milo, Filip Murlak, Frank Neven, Magdalena Ortiz, Thomas Schwentick, Julia Stoyanovich, Jianwen Su, Dan Suciu, Victor Vianu, and Ke Yi. Research Directions for Principles of Data Management (Dagstuhl Perspectives Workshop 16151). In Dagstuhl Manifestos, Volume 7, Issue 1, pp. 1-29, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)

Copy BibTex To Clipboard

@Article{abiteboul_et_al:DagMan.7.1.1,
  author =	{Abiteboul, Serge and Arenas, Marcelo and Barcel\'{o}, Pablo and Bienvenu, Meghyn and Calvanese, Diego and David, Claire and Hull, Richard and H\"{u}llermeier, Eyke and Kimelfeld, Benny and Libkin, Leonid and Martens, Wim and Milo, Tova and Murlak, Filip and Neven, Frank and Ortiz, Magdalena and Schwentick, Thomas and Stoyanovich, Julia and Su, Jianwen and Suciu, Dan and Vianu, Victor and Yi, Ke},
  title =	{{Research Directions for Principles of Data Management (Dagstuhl Perspectives Workshop 16151)}},
  pages =	{1--29},
  journal =	{Dagstuhl Manifestos},
  ISSN =	{2193-2433},
  year =	{2018},
  volume =	{7},
  number =	{1},
  editor =	{Abiteboul, Serge and Arenas, Marcelo and Barcel\'{o}, Pablo and Bienvenu, Meghyn and Calvanese, Diego and David, Claire and Hull, Richard and H\"{u}llermeier, Eyke and Kimelfeld, Benny and Libkin, Leonid and Martens, Wim and Milo, Tova and Murlak, Filip and Neven, Frank and Ortiz, Magdalena and Schwentick, Thomas and Stoyanovich, Julia and Su, Jianwen and Suciu, Dan and Vianu, Victor and Yi, Ke},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagMan.7.1.1},
  URN =		{urn:nbn:de:0030-drops-86772},
  doi =		{10.4230/DagMan.7.1.1},
  annote =	{Keywords: database theory, principles of data management, query languages, efficient query processing, query optimization, heterogeneous data, uncertainty, knowledge-enriched data management, machine learning, workflows, human-related data, ethics}
}
Document
DOI: 10.4230/DagMan.7.1.30
QoE Vadis? (Dagstuhl Perspectives Workshop 16472)

Authors: Markus Fiedler, Sebastian Möller, Peter Reichl, and Min Xie

Abstract
The goal of the Dagstuhl Perspectives Workshop 16472 has been to discuss and outline the strategic evolution of Quality of Experience as a key topic for future Internet research. The resulting manifesto, which is presented here, reviews the state of the art in the Quality of Experience (QoE) domain, along with a SWOT analysis. Based on those, it discusses how the QoE research area might develop in the future, and how QoE research will lead to innovative and improved products and services. It closes by providing a set of recommendations for the scientific community and industry, as well as for future funding of QoE-related activities.
Cite as

Markus Fiedler, Sebastian Möller, Peter Reichl, and Min Xie. QoE Vadis? (Dagstuhl Perspectives Workshop 16472). In Dagstuhl Manifestos, Volume 7, Issue 1, pp. 30-51, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)

Copy BibTex To Clipboard

@Article{fiedler_et_al:DagMan.7.1.30,
  author =	{Fiedler, Markus and M\"{o}ller, Sebastian and Reichl, Peter and Xie, Min},
  title =	{{QoE Vadis? (Dagstuhl Perspectives Workshop 16472)}},
  pages =	{30--51},
  journal =	{Dagstuhl Manifestos},
  ISSN =	{2193-2433},
  year =	{2018},
  volume =	{7},
  number =	{1},
  editor =	{Fiedler, Markus and M\"{o}ller, Sebastian and Reichl, Peter and Xie, Min},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagMan.7.1.30},
  URN =		{urn:nbn:de:0030-drops-86830},
  doi =		{10.4230/DagMan.7.1.30},
  annote =	{Keywords: multimedia, network and application management, network quality monitoring and measurement, quality of experience, socio-economic and business aspects}
}
Document
DOI: 10.4230/DagMan.7.1.52
Tensor Computing for Internet of Things (Dagstuhl Perspectives Workshop 16152)

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

Abstract
"The fundamental laws necessary for the mathematical treatment of large part of physics and the whole of chemistry are thus completely known, and the difficulty lies only in the fact that application of these laws leads to equations that are too complex to be solved." - Dirac 1929 The digital world of Internet of Things (IoT) will provide a high-resolution depiction of our physical world through measurements and other data - even high-definition "video," if you consider streaming data frames coming from a myriad of sensors embedded in everything we use. This depiction will have captured our interactions with the physical world and the interactions of digitally enhanced machines and devices. Tensors, as generalizations of vectors and matrices, provide a natural and scalable framework for handling data with such inherent structures and complex dependencies. Scalable tensor methods have attracted considerable amount of attention, with successes in a series of learning tasks, such as learning latent variable models, relational learning, spatio-temporal forecasting as well as training [19] and compression [20] of deep neural networks. In a Dagstuhl Perspectives Workshop on Tensor Computing for IoT, we validated the fundamental suitability of tensor methods for handling the massive amounts of data coming from connected cyber-physical systems (CPS). The multidisciplinary discourse among academics, industrial researchers and practitioners in the IoT/CPS domain and in the field of machine learning and tensor methods, exposed open issues that need to be addressed to reap value from the technological opportunity. This Manifesto summarizes the immediate action fields for advancement: IoT Tensor Data Benchmarks, Tensor Tools for IoT, and the evolution of a Knowledge Hub. The activities will also be channeled to create best practices and a common tensor language across the disciplines. In a not so distant future, basic infrastructures for living will be mainly data-driven, automated by digitally enhanced devices and machines. The tools and frameworks used to engineer such systems will ensure production-ready machine learning code which utilizes tensor-based, hence better interpretable, models and runs on distributed, decentralized, and embedded computing resources in a robust and reliable way. We conclude the manifesto with a strategy how to move towards this vision with concrete steps in the identified action fields.
Cite as

Evrim Acar, Animashree Anandkumar, Lenore Mullin, Sebnem Rusitschka, and Volker Tresp. Tensor Computing for Internet of Things (Dagstuhl Perspectives Workshop 16152). In Dagstuhl Manifestos, Volume 7, Issue 1, pp. 52-68, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)

Copy BibTex To Clipboard

@Article{acar_et_al:DagMan.7.1.52,
  author =	{Acar, Evrim and Anandkumar, Animashree and Mullin, Lenore and Rusitschka, Sebnem and Tresp, Volker},
  title =	{{Tensor Computing for Internet of Things (Dagstuhl Perspectives Workshop 16152)}},
  pages =	{52--68},
  journal =	{Dagstuhl Manifestos},
  ISSN =	{2193-2433},
  year =	{2018},
  volume =	{7},
  number =	{1},
  editor =	{Acar, Evrim 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/DagMan.7.1.52},
  URN =		{urn:nbn:de:0030-drops-88244},
  doi =		{10.4230/DagMan.7.1.52},
  annote =	{Keywords: Distributed Systems, Real-time and embedded systems, Signal processing systems, Learning, Multiagent systems}
}
Document
DOI: 10.4230/DagMan.7.1.69
Present and Future of Formal Argumentation (Dagstuhl Perspectives Workshop 15362)

Authors: Dov M. Gabbay, Massimiliano Giacomin, Beishui Liao, and Leendert van der Torre

Abstract
Formal Argumentation is emerging as a key reasoning paradigm building bridges among knowledge representation and reasoning in artificial intelligence, informal argumentation in philosophy and linguistics, legal and ethical argumentation, mathematical and logical reasoning, and graph-theoretic reasoning. It aims to capture diverse kinds of reasoning and dialogue activities in the presence of uncertainty and conflicting information in a formal and intuitive way, with potential applications ranging from argumentation mining, via LegalTech and machine ethics, to therapy in clinical psychology. The turning point for the modern stage of formal argumentation theory, much similar to the introduction of possible worlds semantics for the theory of modality, is the framework and language of Dung's abstract argumentation theory introduced in 1995. This means that nothing could remain the same as before 1995 - it should be a focal point of reference for any study of argumentation, even if it is critical about it. Now, in modal logic, the introduction of the possible worlds semantics has led to a complete paradigm shift, both in tools and new subjects of studies. This is still not fully true for what is going on in argumentation theory. The Dagstuhl workshop led to the first volume of a handbook series in formal argumentation, reflecting the new stage of the development of argumentation theory.
Cite as

Dov M. Gabbay, Massimiliano Giacomin, Beishui Liao, and Leendert van der Torre. Present and Future of Formal Argumentation (Dagstuhl Perspectives Workshop 15362). In Dagstuhl Manifestos, Volume 7, Issue 1, pp. 69-95, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)

Copy BibTex To Clipboard

@Article{gabbay_et_al:DagMan.7.1.69,
  author =	{Gabbay, Dov M. and Giacomin, Massimiliano and Liao, Beishui and van der Torre, Leendert},
  title =	{{Present and Future of Formal Argumentation (Dagstuhl Perspectives Workshop 15362)}},
  pages =	{69--95},
  journal =	{Dagstuhl Manifestos},
  ISSN =	{2193-2433},
  year =	{2018},
  volume =	{7},
  number =	{1},
  editor =	{Gabbay, Dov M. and Giacomin, Massimiliano and Liao, Beishui and van der Torre, Leendert},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagMan.7.1.69},
  URN =		{urn:nbn:de:0030-drops-98957},
  doi =		{10.4230/DagMan.7.1.69},
  annote =	{Keywords: Artificial Intelligence, Knowledge Representation and Reasoning, Multi-Agent Systems, Argumentation, Non-monotonic Logic}
}
Document
DOI: 10.4230/DagMan.7.1.96
From Evaluating to Forecasting Performance: How to Turn Information Retrieval, Natural Language Processing and Recommender Systems into Predictive Sciences (Dagstuhl Perspectives Workshop 17442)

Authors: Nicola Ferro, Norbert Fuhr, Gregory Grefenstette, Joseph A. Konstan, Pablo Castells, Elizabeth M. Daly, Thierry Declerck, Michael D. Ekstrand, Werner Geyer, Julio Gonzalo, Tsvi Kuflik, Krister Lindén, Bernardo Magnini, Jian-Yun Nie, Raffaele Perego, Bracha Shapira, Ian Soboroff, Nava Tintarev, Karin Verspoor, Martijn C. Willemsen, and Justin Zobel

Abstract
We describe the state-of-the-art in performance modeling and prediction for Information Retrieval (IR), Natural Language Processing (NLP) and Recommender Systems (RecSys) along with its shortcomings and strengths. We present a framework for further research, identifying five major problem areas: understanding measures, performance analysis, making underlying assumptions explicit, identifying application features determining performance, and the development of prediction models describing the relationship between assumptions, features and resulting performance.
Cite as

Nicola Ferro, Norbert Fuhr, Gregory Grefenstette, Joseph A. Konstan, Pablo Castells, Elizabeth M. Daly, Thierry Declerck, Michael D. Ekstrand, Werner Geyer, Julio Gonzalo, Tsvi Kuflik, Krister Lindén, Bernardo Magnini, Jian-Yun Nie, Raffaele Perego, Bracha Shapira, Ian Soboroff, Nava Tintarev, Karin Verspoor, Martijn C. Willemsen, and Justin Zobel. From Evaluating to Forecasting Performance: How to Turn Information Retrieval, Natural Language Processing and Recommender Systems into Predictive Sciences (Dagstuhl Perspectives Workshop 17442). In Dagstuhl Manifestos, Volume 7, Issue 1, pp. 96-139, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)

Copy BibTex To Clipboard

@Article{ferro_et_al:DagMan.7.1.96,
  author =	{Ferro, Nicola and Fuhr, Norbert and Grefenstette, Gregory and Konstan, Joseph A. and Castells, Pablo and Daly, Elizabeth M. and Declerck, Thierry and Ekstrand, Michael D. and Geyer, Werner and Gonzalo, Julio and Kuflik, Tsvi and Lind\'{e}n, Krister and Magnini, Bernardo and Nie, Jian-Yun and Perego, Raffaele and Shapira, Bracha and Soboroff, Ian and Tintarev, Nava and Verspoor, Karin and Willemsen, Martijn C. and Zobel, Justin},
  title =	{{From Evaluating to Forecasting Performance: How to Turn Information Retrieval, Natural Language Processing and Recommender Systems into Predictive Sciences (Dagstuhl Perspectives Workshop 17442)}},
  pages =	{96--139},
  journal =	{Dagstuhl Manifestos},
  ISSN =	{2193-2433},
  year =	{2018},
  volume =	{7},
  number =	{1},
  editor =	{Ferro, Nicola and Fuhr, Norbert and Grefenstette, Gregory and Konstan, Joseph A. and Castells, Pablo and Daly, Elizabeth M. and Declerck, Thierry and Ekstrand, Michael D. and Geyer, Werner and Gonzalo, Julio and Kuflik, Tsvi and Lind\'{e}n, Krister and Magnini, Bernardo and Nie, Jian-Yun and Perego, Raffaele and Shapira, Bracha and Soboroff, Ian and Tintarev, Nava and Verspoor, Karin and Willemsen, Martijn C. and Zobel, Justin},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagMan.7.1.96},
  URN =		{urn:nbn:de:0030-drops-98987},
  doi =		{10.4230/DagMan.7.1.96},
  annote =	{Keywords: Information Systems, Formal models, Evaluation, Simulation, User Interaction}
}

Filters

  • Authors
  • A
  • Abiteboul, Serge
  • Acar, Evrim
  • Anandkumar, Animashree
  • Arenas, Marcelo
  • B
  • Barceló, Pablo
  • Bienvenu, Meghyn
  • C
  • Calvanese, Diego
  • Castells, Pablo
  • D
  • Daly, Elizabeth M.
  • David, Claire
  • Declerck, Thierry
  • E
  • Ekstrand, Michael D.
  • F
  • Ferro, Nicola
  • Fiedler, Markus
  • Fuhr, Norbert
  • G
  • Gabbay, Dov M.
  • Geyer, Werner
  • Giacomin, Massimiliano
  • Gonzalo, Julio
  • Grefenstette, Gregory
  • H
  • Hull, Richard
  • Hüllermeier, Eyke
  • K
  • Kimelfeld, Benny
  • Konstan, Joseph A.
  • Kuflik, Tsvi
  • L
  • Liao, Beishui
  • Libkin, Leonid
  • Lindén, Krister
  • M
  • Magnini, Bernardo
  • Martens, Wim
  • Milo, Tova
  • Möller, Sebastian
  • Mullin, Lenore
  • Murlak, Filip
  • N
  • Neven, Frank
  • Nie, Jian-Yun
  • O
  • Ortiz, Magdalena
  • P
  • Perego, Raffaele
  • R
  • Reichl, Peter
  • Rusitschka, Sebnem
  • S
  • Schwentick, Thomas
  • Shapira, Bracha
  • Soboroff, Ian
  • Stoyanovich, Julia
  • Su, Jianwen
  • Suciu, Dan
  • T
  • Tintarev, Nava
  • Tresp, Volker
  • V
  • van der Torre, Leendert
  • Verspoor, Karin
  • Vianu, Victor
  • W
  • Willemsen, Martijn C.
  • X
  • Xie, Min
  • Y
  • Yi, Ke
  • Z
  • Zobel, Justin

Questions / Remarks / Feedback
X

Feedback for Dagstuhl Publishing


Thanks for your feedback!

Feedback submitted

Could not send message

Please try again later or send an E-mail
© 2023-2024 Schloss Dagstuhl – LZI GmbH Imprint Privacy Contact