5 Search Results for "Werner, Christian"

Document
Short Paper
DOI: 10.4230/LIPIcs.GIScience.2023.83
Betweenness Centrality in Spatial Networks: A Spatially Normalised Approach (Short Paper)

Authors: Christian Werner and Martin Loidl

Published in: LIPIcs, Volume 277, 12th International Conference on Geographic Information Science (GIScience 2023)

Abstract
Centrality metrics are essential to network analysis. They reveal important morphological properties of networks, indicating e.g. node or edge importance. Applications are manifold, ranging from biology to transport planning. However, while being commonly applied in spatial contexts such as urban analytics, the implications of the spatial configuration of network elements on these metrics are widely neglected. As a consequence, a systematic bias is introduced into spatial network analyses. When applied to real-world problems, unintended side effects and wrong conclusions might be the result. In this paper, we assess the impact of node density on betweenness centrality. Furthermore, we propose a method for computing spatially normalised betweenness centrality. We apply it to a theoretical case as well as real-world transport networks. Results show that spatial normalisation mitigates the prevalent bias of node density.
Cite as

Christian Werner and Martin Loidl. Betweenness Centrality in Spatial Networks: A Spatially Normalised Approach (Short Paper). In 12th International Conference on Geographic Information Science (GIScience 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 277, pp. 83:1-83:6, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{werner_et_al:LIPIcs.GIScience.2023.83,
  author =	{Werner, Christian and Loidl, Martin},
  title =	{{Betweenness Centrality in Spatial Networks: A Spatially Normalised Approach}},
  booktitle =	{12th International Conference on Geographic Information Science (GIScience 2023)},
  pages =	{83:1--83:6},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-288-4},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{277},
  editor =	{Beecham, Roger and Long, Jed A. and Smith, Dianna and Zhao, Qunshan and Wise, Sarah},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.GIScience.2023.83},
  URN =		{urn:nbn:de:0030-drops-189781},
  doi =		{10.4230/LIPIcs.GIScience.2023.83},
  annote =	{Keywords: spatial network analysis, edge betweenness centrality, flow estimation, SIBC, spatial interaction, spatial centrality, urban analytics}
}
Document
DOI: 10.4230/DagRep.12.1.1
Mobility Data Science (Dagstuhl Seminar 22021)

Authors: Mohamed Mokbel, Mahmoud Sakr, Li Xiong, Andreas Züfle, Jussara Almeida, Taylor Anderson, Walid Aref, Gennady Andrienko, Natalia Andrienko, Yang Cao, Sanjay Chawla, Reynold Cheng, Panos Chrysanthis, Xiqi Fei, Gabriel Ghinita, Anita Graser, Dimitrios Gunopulos, Christian Jensen, Joon-Sook Kim, Kyoung-Sook Kim, Peer Kröger, John Krumm, Johannes Lauer, Amr Magdy, Mario Nascimento, Siva Ravada, Matthias Renz, Dimitris Sacharidis, Cyrus Shahabi, Flora Salim, Mohamed Sarwat, Maxime Schoemans, Bettina Speckmann, Egemen Tanin, Yannis Theodoridis, Kristian Torp, Goce Trajcevski, Marc van Kreveld, Carola Wenk, Martin Werner, Raymond Wong, Song Wu, Jianqiu Xu, Moustafa Youssef, Demetris Zeinalipour, Mengxuan Zhang, and Esteban Zimányi

Published in: Dagstuhl Reports, Volume 12, Issue 1 (2022)

Abstract
This report documents the program and the outcomes of Dagstuhl Seminar 22021 "Mobility Data Science". This seminar was held January 9-14, 2022, including 47 participants from industry and academia. The goal of this Dagstuhl Seminar was to create a new research community of mobility data science in which the whole is greater than the sum of its parts by bringing together established leaders as well as promising young researchers from all fields related to mobility data science. Specifically, this report summarizes the main results of the seminar by (1) defining Mobility Data Science as a research domain, (2) by sketching its agenda in the coming years, and by (3) building a mobility data science community. (1) Mobility data science is defined as spatiotemporal data that additionally captures the behavior of moving entities (human, vehicle, animal, etc.). To understand, explain, and predict behavior, we note that a strong collaboration with research in behavioral and social sciences is needed. (2) Future research directions for mobility data science described in this report include a) mobility data acquisition and privacy, b) mobility data management and analysis, and c) applications of mobility data science. (3) We identify opportunities towards building a mobility data science community, towards collaborations between academic and industry, and towards a mobility data science curriculum.
Cite as

Mohamed Mokbel, Mahmoud Sakr, Li Xiong, Andreas Züfle, Jussara Almeida, Taylor Anderson, Walid Aref, Gennady Andrienko, Natalia Andrienko, Yang Cao, Sanjay Chawla, Reynold Cheng, Panos Chrysanthis, Xiqi Fei, Gabriel Ghinita, Anita Graser, Dimitrios Gunopulos, Christian Jensen, Joon-Sook Kim, Kyoung-Sook Kim, Peer Kröger, John Krumm, Johannes Lauer, Amr Magdy, Mario Nascimento, Siva Ravada, Matthias Renz, Dimitris Sacharidis, Cyrus Shahabi, Flora Salim, Mohamed Sarwat, Maxime Schoemans, Bettina Speckmann, Egemen Tanin, Yannis Theodoridis, Kristian Torp, Goce Trajcevski, Marc van Kreveld, Carola Wenk, Martin Werner, Raymond Wong, Song Wu, Jianqiu Xu, Moustafa Youssef, Demetris Zeinalipour, Mengxuan Zhang, and Esteban Zimányi. Mobility Data Science (Dagstuhl Seminar 22021). In Dagstuhl Reports, Volume 12, Issue 1, pp. 1-34, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)

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@Article{mokbel_et_al:DagRep.12.1.1,
  author =	{Mokbel, Mohamed and Sakr, Mahmoud and Xiong, Li and Z\"{u}fle, Andreas and Almeida, Jussara and Anderson, Taylor and Aref, Walid and Andrienko, Gennady and Andrienko, Natalia and Cao, Yang and Chawla, Sanjay and Cheng, Reynold and Chrysanthis, Panos and Fei, Xiqi and Ghinita, Gabriel and Graser, Anita and Gunopulos, Dimitrios and Jensen, Christian and Kim, Joon-Sook and Kim, Kyoung-Sook and Kr\"{o}ger, Peer and Krumm, John and Lauer, Johannes and Magdy, Amr and Nascimento, Mario and Ravada, Siva and Renz, Matthias and Sacharidis, Dimitris and Shahabi, Cyrus and Salim, Flora and Sarwat, Mohamed and Schoemans, Maxime and Speckmann, Bettina and Tanin, Egemen and Theodoridis, Yannis and Torp, Kristian and Trajcevski, Goce and van Kreveld, Marc and Wenk, Carola and Werner, Martin and Wong, Raymond and Wu, Song and Xu, Jianqiu and Youssef, Moustafa and Zeinalipour, Demetris and Zhang, Mengxuan and Zim\'{a}nyi, Esteban},
  title =	{{Mobility Data Science (Dagstuhl Seminar 22021)}},
  pages =	{1--34},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2022},
  volume =	{12},
  number =	{1},
  editor =	{Mokbel, Mohamed and Sakr, Mahmoud and Xiong, Li and Z\"{u}fle, Andreas},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagRep.12.1.1},
  URN =		{urn:nbn:de:0030-drops-169190},
  doi =		{10.4230/DagRep.12.1.1},
  annote =	{Keywords: Spatio-temporal, Tracking, Privacy, Behavior, Data cleaning, Data management, Analytics}
}
Document
Short Paper
DOI: 10.4230/LIPIcs.GISCIENCE.2018.60
Abstract Data Types for Spatio-Temporal Remote Sensing Analysis (Short Paper)

Authors: Martin Sudmanns, Stefan Lang, Dirk Tiede, Christian Werner, Hannah Augustin, and Andrea Baraldi

Published in: LIPIcs, Volume 114, 10th International Conference on Geographic Information Science (GIScience 2018)

Abstract
Abstract data types are a helpful framework to formalise analyses and make them more transparent, reproducible and comprehensible. We are revisiting an approach based on the space, time and theme dimensions of remotely sensed data, and extending it with a more differentiated understanding of space-time representations. In contrast to existing approaches and implementations that consider only fixed spatial units (e.g. pixels), our approach allows investigations of the spatial units' spatio-temporal characteristics, such as the size and shape of their geometry, and their relationships. Five different abstract data types are identified to describe geographical phenomenon, either directly or in combination: coverage, time series, trajectory, composition and evolution.
Cite as

Martin Sudmanns, Stefan Lang, Dirk Tiede, Christian Werner, Hannah Augustin, and Andrea Baraldi. Abstract Data Types for Spatio-Temporal Remote Sensing Analysis (Short Paper). In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 60:1-60:7, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)

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@InProceedings{sudmanns_et_al:LIPIcs.GISCIENCE.2018.60,
  author =	{Sudmanns, Martin and Lang, Stefan and Tiede, Dirk and Werner, Christian and Augustin, Hannah and Baraldi, Andrea},
  title =	{{Abstract Data Types for Spatio-Temporal Remote Sensing Analysis}},
  booktitle =	{10th International Conference on Geographic Information Science (GIScience 2018)},
  pages =	{60:1--60:7},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-083-5},
  ISSN =	{1868-8969},
  year =	{2018},
  volume =	{114},
  editor =	{Winter, Stephan and Griffin, Amy and Sester, Monika},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.GISCIENCE.2018.60},
  URN =		{urn:nbn:de:0030-drops-93881},
  doi =		{10.4230/LIPIcs.GISCIENCE.2018.60},
  annote =	{Keywords: Big Earth Data, Semantic Analysis, Data Cube}
}
Document
DOI: 10.4230/LIPIcs.STACS.2011.649
On the computational complexity of Ham-Sandwich cuts, Helly sets, and related problems

Authors: Christian Knauer, Hans Raj Tiwary, and Daniel Werner

Published in: LIPIcs, Volume 9, 28th International Symposium on Theoretical Aspects of Computer Science (STACS 2011)

Abstract
We study several canonical decision problems arising from some well-known theorems from combinatorial geometry. Among others, we show that computing the minimum size of a Caratheodory set and a Helly set and certain decision versions of the hs cut problem are W[1]-hard (and NP-hard) if the dimension is part of the input. This is done by fpt-reductions (which are actually ptime-reductions) from the d-Sum problem. Our reductions also imply that the problems we consider cannot be solved in time n^{o(d)} (where n is the size of the input), unless the Exponential-Time Hypothesis (ETH) is false. The technique of embedding d-Sum into a geometric setting is conceptually much simpler than direct fpt-reductions from purely combinatorial W[1]-hard problems (like the clique problem) and has great potential to show (parameterized) hardness and (conditional) lower bounds for many other problems.
Cite as

Christian Knauer, Hans Raj Tiwary, and Daniel Werner. On the computational complexity of Ham-Sandwich cuts, Helly sets, and related problems. In 28th International Symposium on Theoretical Aspects of Computer Science (STACS 2011). Leibniz International Proceedings in Informatics (LIPIcs), Volume 9, pp. 649-660, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2011)

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@InProceedings{knauer_et_al:LIPIcs.STACS.2011.649,
  author =	{Knauer, Christian and Tiwary, Hans Raj and Werner, Daniel},
  title =	{{On the computational complexity of Ham-Sandwich cuts, Helly sets, and related problems}},
  booktitle =	{28th International Symposium on Theoretical Aspects of Computer Science (STACS 2011)},
  pages =	{649--660},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-939897-25-5},
  ISSN =	{1868-8969},
  year =	{2011},
  volume =	{9},
  editor =	{Schwentick, Thomas and D\"{u}rr, Christoph},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.STACS.2011.649},
  URN =		{urn:nbn:de:0030-drops-30514},
  doi =		{10.4230/LIPIcs.STACS.2011.649},
  annote =	{Keywords: computational geometry, combinatorial geometry, ham-sandwich cuts, parameterized complexity.}
}
Document
DOI: 10.4230/OASIcs.KiVS.2011.26
A Service-Oriented Operating System and an Application Development Infrastructure for Distributed Embedded Systems

Authors: Martin Lipphardt, Nils Glombitza, Jana Neumann, Christian Werner, and Stefan Fischer

Published in: OASIcs, Volume 17, 17th GI/ITG Conference on Communication in Distributed Systems (KiVS 2011)

Abstract
The paradigm of service-orientation promises a significant ease of use in creating and managing distributed software systems. A very important aspect here is that also application domain experts and stakeholders, who are not necessarily skilled in computer programming, get a chance to create, analyze, and adapt distributed applications. However, up to now, service-oriented architectures have been mainly discussed in the context of complex business applications. In this paper we will investigate how to transfer the benefits of a service-oriented architecture into the field of embedded systems, so that this technology gets accessible to a much wider range of users. As an example, we will demonstrate this scheme for sensor network applications. In order to address the problem of limited device resources we will introduce a minimal operating system for such devices. It organizes all pieces of code running on a sensor node in a service-oriented fashion and also features the relocation of code to a different node at runtime. We will demonstrate that it is possible to design a sensor network application from a set of already existing services in a highly modular way by employing already existing technologies and standards.
Cite as

Martin Lipphardt, Nils Glombitza, Jana Neumann, Christian Werner, and Stefan Fischer. A Service-Oriented Operating System and an Application Development Infrastructure for Distributed Embedded Systems. In 17th GI/ITG Conference on Communication in Distributed Systems (KiVS 2011). Open Access Series in Informatics (OASIcs), Volume 17, pp. 26-37, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2011)

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@InProceedings{lipphardt_et_al:OASIcs.KiVS.2011.26,
  author =	{Lipphardt, Martin and Glombitza, Nils and Neumann, Jana and Werner, Christian and Fischer, Stefan},
  title =	{{A Service-Oriented Operating System and an Application Development Infrastructure for Distributed Embedded Systems}},
  booktitle =	{17th GI/ITG Conference on Communication in Distributed Systems (KiVS 2011)},
  pages =	{26--37},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-939897-27-9},
  ISSN =	{2190-6807},
  year =	{2011},
  volume =	{17},
  editor =	{Luttenberger, Norbert and Peters, Hagen},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/OASIcs.KiVS.2011.26},
  URN =		{urn:nbn:de:0030-drops-29550},
  doi =		{10.4230/OASIcs.KiVS.2011.26},
  annote =	{Keywords: service-oriented OS, sensor network, distributed embedded systems}
}
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