40 Search Results for "R�misch, Werner"

Document
DOI: 10.4230/LIPIcs.GIScience.2023.7
Semi-Supervised Learning from Street-View Images and OpenStreetMap for Automatic Building Height Estimation

Authors: Hao Li, Zhendong Yuan, Gabriel Dax, Gefei Kong, Hongchao Fan, Alexander Zipf, and Martin Werner

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

Abstract
Accurate building height estimation is key to the automatic derivation of 3D city models from emerging big geospatial data, including Volunteered Geographical Information (VGI). However, an automatic solution for large-scale building height estimation based on low-cost VGI data is currently missing. The fast development of VGI data platforms, especially OpenStreetMap (OSM) and crowdsourced street-view images (SVI), offers a stimulating opportunity to fill this research gap. In this work, we propose a semi-supervised learning (SSL) method of automatically estimating building height from Mapillary SVI and OSM data to generate low-cost and open-source 3D city modeling in LoD1. The proposed method consists of three parts: first, we propose an SSL schema with the option of setting a different ratio of "pseudo label" during the supervised regression; second, we extract multi-level morphometric features from OSM data (i.e., buildings and streets) for the purposed of inferring building height; last, we design a building floor estimation workflow with a pre-trained facade object detection network to generate "pseudo label" from SVI and assign it to the corresponding OSM building footprint. In a case study, we validate the proposed SSL method in the city of Heidelberg, Germany and evaluate the model performance against the reference data of building heights. Based on three different regression models, namely Random Forest (RF), Support Vector Machine (SVM), and Convolutional Neural Network (CNN), the SSL method leads to a clear performance boosting in estimating building heights with a Mean Absolute Error (MAE) around 2.1 meters, which is competitive to state-of-the-art approaches. The preliminary result is promising and motivates our future work in scaling up the proposed method based on low-cost VGI data, with possibilities in even regions and areas with diverse data quality and availability.
Cite as

Hao Li, Zhendong Yuan, Gabriel Dax, Gefei Kong, Hongchao Fan, Alexander Zipf, and Martin Werner. Semi-Supervised Learning from Street-View Images and OpenStreetMap for Automatic Building Height Estimation. In 12th International Conference on Geographic Information Science (GIScience 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 277, pp. 7:1-7:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{li_et_al:LIPIcs.GIScience.2023.7,
  author =	{Li, Hao and Yuan, Zhendong and Dax, Gabriel and Kong, Gefei and Fan, Hongchao and Zipf, Alexander and Werner, Martin},
  title =	{{Semi-Supervised Learning from Street-View Images and OpenStreetMap for Automatic Building Height Estimation}},
  booktitle =	{12th International Conference on Geographic Information Science (GIScience 2023)},
  pages =	{7:1--7:15},
  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.2023.7},
  URN =		{urn:nbn:de:0030-drops-189028},
  doi =		{10.4230/LIPIcs.GIScience.2023.7},
  annote =	{Keywords: OpenStreetMap, Street-view Images, VGI, GeoAI, 3D city model, Facade parsing}
}
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/LIPIcs.ESA.2022.89
Combining Predicted and Live Traffic with Time-Dependent A* Potentials

Authors: Nils Werner and Tim Zeitz

Published in: LIPIcs, Volume 244, 30th Annual European Symposium on Algorithms (ESA 2022)

Abstract
We study efficient and exact shortest path algorithms for routing on road networks with realistic traffic data. For navigation applications, both current (i.e., live) traffic events and predictions of future traffic flows play an important role in routing. While preprocessing-based speedup techniques have been employed successfully to both settings individually, a combined model poses significant challenges. Supporting predicted traffic typically requires expensive preprocessing while live traffic requires fast updates for regular adjustments. We propose an A*-based solution to this problem. By generalizing A* potentials to time dependency, i.e. the estimate of the distance from a vertex to the target also depends on the time of day when the vertex is visited, we achieve significantly faster query times than previously possible. Our evaluation shows that our approach enables interactive query times on continental-sized road networks while allowing live traffic updates within a fraction of a minute. We achieve a speedup of at least two orders of magnitude over Dijkstra’s algorithm and up to one order of magnitude over state-of-the-art time-independent A* potentials.
Cite as

Nils Werner and Tim Zeitz. Combining Predicted and Live Traffic with Time-Dependent A* Potentials. In 30th Annual European Symposium on Algorithms (ESA 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 244, pp. 89:1-89:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)

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@InProceedings{werner_et_al:LIPIcs.ESA.2022.89,
  author =	{Werner, Nils and Zeitz, Tim},
  title =	{{Combining Predicted and Live Traffic with Time-Dependent A* Potentials}},
  booktitle =	{30th Annual European Symposium on Algorithms (ESA 2022)},
  pages =	{89:1--89:15},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-247-1},
  ISSN =	{1868-8969},
  year =	{2022},
  volume =	{244},
  editor =	{Chechik, Shiri and Navarro, Gonzalo and Rotenberg, Eva and Herman, Grzegorz},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.ESA.2022.89},
  URN =		{urn:nbn:de:0030-drops-170271},
  doi =		{10.4230/LIPIcs.ESA.2022.89},
  annote =	{Keywords: realistic road networks, shortest paths, live traffic, time-dependent routing}
}
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
DOI: 10.4230/LIPIcs.CP.2021.23
Bounds on Weighted CSPs Using Constraint Propagation and Super-Reparametrizations

Authors: Tomáš Dlask, Tomáš Werner, and Simon de Givry

Published in: LIPIcs, Volume 210, 27th International Conference on Principles and Practice of Constraint Programming (CP 2021)

Abstract
We propose a framework for computing upper bounds on the optimal value of the (maximization version of) Weighted CSP (WCSP) using super-reparametrizations, which are changes of the weights that keep or increase the WCSP objective for every assignment. We show that it is in principle possible to employ arbitrary (under certain technical conditions) constraint propagation rules to improve the bound. For arc consistency in particular, the method reduces to the known Virtual AC (VAC) algorithm. Newly, we implemented the method for singleton arc consistency (SAC) and compared it to other strong local consistencies in WCSPs on a public benchmark. The results show that the bounds obtained from SAC are superior for many instance groups.
Cite as

Tomáš Dlask, Tomáš Werner, and Simon de Givry. Bounds on Weighted CSPs Using Constraint Propagation and Super-Reparametrizations. In 27th International Conference on Principles and Practice of Constraint Programming (CP 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 210, pp. 23:1-23:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)

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@InProceedings{dlask_et_al:LIPIcs.CP.2021.23,
  author =	{Dlask, Tom\'{a}\v{s} and Werner, Tom\'{a}\v{s} and de Givry, Simon},
  title =	{{Bounds on Weighted CSPs Using Constraint Propagation and Super-Reparametrizations}},
  booktitle =	{27th International Conference on Principles and Practice of Constraint Programming (CP 2021)},
  pages =	{23:1--23:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-211-2},
  ISSN =	{1868-8969},
  year =	{2021},
  volume =	{210},
  editor =	{Michel, Laurent D.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CP.2021.23},
  URN =		{urn:nbn:de:0030-drops-153149},
  doi =		{10.4230/LIPIcs.CP.2021.23},
  annote =	{Keywords: Weighted CSP, Super-Reparametrization, Linear Programming, Constraint Propagation}
}
Document
DOI: 10.4230/OASIcs.LDK.2021.29
AAA4LLL - Acquisition, Annotation, Augmentation for Lively Language Learning

Authors: Bartholomäus Wloka and Werner Winiwarter

Published in: OASIcs, Volume 93, 3rd Conference on Language, Data and Knowledge (LDK 2021)

Abstract
In this paper we describe a method for enhancing the process of studying Japanese by a user-centered approach. This approach includes three parts: an innovative way of acquiring learning material from topic seeds, multifaceted sentence analysis to present sentence annotations, and the browser-integrated augmentation of perusing Wikipedia pages of special interest for the learner. This may result in new topic seeds to yield additional learning content, thus repeating the cycle.
Cite as

Bartholomäus Wloka and Werner Winiwarter. AAA4LLL - Acquisition, Annotation, Augmentation for Lively Language Learning. In 3rd Conference on Language, Data and Knowledge (LDK 2021). Open Access Series in Informatics (OASIcs), Volume 93, pp. 29:1-29:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)

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@InProceedings{wloka_et_al:OASIcs.LDK.2021.29,
  author =	{Wloka, Bartholom\"{a}us and Winiwarter, Werner},
  title =	{{AAA4LLL - Acquisition, Annotation, Augmentation for Lively Language Learning}},
  booktitle =	{3rd Conference on Language, Data and Knowledge (LDK 2021)},
  pages =	{29:1--29:15},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-199-3},
  ISSN =	{2190-6807},
  year =	{2021},
  volume =	{93},
  editor =	{Gromann, Dagmar and S\'{e}rasset, Gilles and Declerck, Thierry and McCrae, John P. and Gracia, Jorge and Bosque-Gil, Julia and Bobillo, Fernando and Heinisch, Barbara},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/OASIcs.LDK.2021.29},
  URN =		{urn:nbn:de:0030-drops-145654},
  doi =		{10.4230/OASIcs.LDK.2021.29},
  annote =	{Keywords: Web-based language learning, augmented browsing, natural language annotation, corpus alignment, Japanese computing, semantic representation}
}
Document
DOI: 10.4230/LIPIcs.FSTTCS.2020.44
Nivat-Theorem and Logic for Weighted Pushdown Automata on Infinite Words

Authors: Manfred Droste, Sven Dziadek, and Werner Kuich

Published in: LIPIcs, Volume 182, 40th IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS 2020)

Abstract
Recently, weighted ω-pushdown automata have been introduced by Droste, Ésik, Kuich. This new type of automaton has access to a stack and models quantitative aspects of infinite words. Here, we consider a simple version of those automata. The simple ω-pushdown automata do not use ε-transitions and have a very restricted stack access. In previous work, we could show this automaton model to be expressively equivalent to context-free ω-languages in the unweighted case. Furthermore, semiring-weighted simple ω-pushdown automata recognize all ω-algebraic series. Here, we consider ω-valuation monoids as weight structures. As a first result, we prove that for this weight structure and for simple ω-pushdown automata, Büchi-acceptance and Muller-acceptance are expressively equivalent. In our second result, we derive a Nivat theorem for these automata stating that the behaviors of weighted ω-pushdown automata are precisely the projections of very simple ω-series restricted to ω-context-free languages. The third result is a weighted logic with the same expressive power as the new automaton model. To prove the equivalence, we use a similar result for weighted nested ω-word automata and apply our present result of expressive equivalence of Muller and Büchi acceptance.
Cite as

Manfred Droste, Sven Dziadek, and Werner Kuich. Nivat-Theorem and Logic for Weighted Pushdown Automata on Infinite Words. In 40th IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS 2020). Leibniz International Proceedings in Informatics (LIPIcs), Volume 182, pp. 44:1-44:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)

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@InProceedings{droste_et_al:LIPIcs.FSTTCS.2020.44,
  author =	{Droste, Manfred and Dziadek, Sven and Kuich, Werner},
  title =	{{Nivat-Theorem and Logic for Weighted Pushdown Automata on Infinite Words}},
  booktitle =	{40th IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS 2020)},
  pages =	{44:1--44:14},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-174-0},
  ISSN =	{1868-8969},
  year =	{2020},
  volume =	{182},
  editor =	{Saxena, Nitin and Simon, Sunil},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.FSTTCS.2020.44},
  URN =		{urn:nbn:de:0030-drops-132850},
  doi =		{10.4230/LIPIcs.FSTTCS.2020.44},
  annote =	{Keywords: Weighted automata, Pushdown automata, Infinite words, Weighted logic}
}
Document
DOI: 10.4230/LIPIcs.GIScience.2021.I.5
Search Facets and Ranking in Geospatial Dataset Search

Authors: Thomas Hervey, Sara Lafia, and Werner Kuhn

Published in: LIPIcs, Volume 177, 11th International Conference on Geographic Information Science (GIScience 2021) - Part I (2020)

Abstract
This study surveys the state of search on open geospatial data portals. We seek to understand 1) what users are able to control when searching for geospatial data, 2) how these portals process and interpret a user’s query, and 3) if and how user query reformulations alter search results. We find that most users initiate a search using a text input and several pre-created facets (such as a filter for tags or format). Some portals supply a map-view of data or topic explorers. To process and interpret queries, most portals use a vertical full-text search engine like Apache Solr to query data from a content-management system like CKAN. When processing queries, most portals initially filter results and then rank the remaining results using a common keyword frequency relevance metric (e.g., TF-IDF). Some portals use query expansion. We identify and discuss several recurring usability constraints across portals. For example, users are typically only given text lists to interact with search results. Furthermore, ranking is rarely extended beyond syntactic comparison of keyword similarity. We discuss several avenues for improving search for geospatial data including alternative interfaces and query processing pipelines.
Cite as

Thomas Hervey, Sara Lafia, and Werner Kuhn. Search Facets and Ranking in Geospatial Dataset Search. In 11th International Conference on Geographic Information Science (GIScience 2021) - Part I. Leibniz International Proceedings in Informatics (LIPIcs), Volume 177, pp. 5:1-5:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)

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@InProceedings{hervey_et_al:LIPIcs.GIScience.2021.I.5,
  author =	{Hervey, Thomas and Lafia, Sara and Kuhn, Werner},
  title =	{{Search Facets and Ranking in Geospatial Dataset Search}},
  booktitle =	{11th International Conference on Geographic Information Science (GIScience 2021) - Part I},
  pages =	{5:1--5:15},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-166-5},
  ISSN =	{1868-8969},
  year =	{2020},
  volume =	{177},
  editor =	{Janowicz, Krzysztof and Verstegen, Judith A.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.GIScience.2021.I.5},
  URN =		{urn:nbn:de:0030-drops-130405},
  doi =		{10.4230/LIPIcs.GIScience.2021.I.5},
  annote =	{Keywords: search, portal, discovery, GIR, facet, relevance, ranking}
}
Document
DOI: 10.4230/LIPIcs.FSTTCS.2019.38
Greibach Normal Form for omega-Algebraic Systems and Weighted Simple omega-Pushdown Automata

Authors: Manfred Droste, Sven Dziadek, and Werner Kuich

Published in: LIPIcs, Volume 150, 39th IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS 2019)

Abstract
In weighted automata theory, many classical results on formal languages have been extended into a quantitative setting. Here, we investigate weighted context-free languages of infinite words, a generalization of omega-context-free languages (Cohen, Gold 1977) and an extension of weighted context-free languages of finite words (Chomsky, Schützenberger 1963). As in the theory of formal grammars, these weighted languages, or omega-algebraic series, can be represented as solutions of mixed omega-algebraic systems of equations and by weighted omega-pushdown automata. In our first main result, we show that mixed omega-algebraic systems can be transformed into Greibach normal form. Our second main result proves that simple omega-reset pushdown automata recognize all omega-algebraic series that are a solution of an omega-algebraic system in Greibach normal form. Simple reset automata do not use epsilon-transitions and can change the stack only by at most one symbol. These results generalize fundamental properties of context-free languages to weighted languages.
Cite as

Manfred Droste, Sven Dziadek, and Werner Kuich. Greibach Normal Form for omega-Algebraic Systems and Weighted Simple omega-Pushdown Automata. In 39th IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 150, pp. 38:1-38:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)

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@InProceedings{droste_et_al:LIPIcs.FSTTCS.2019.38,
  author =	{Droste, Manfred and Dziadek, Sven and Kuich, Werner},
  title =	{{Greibach Normal Form for omega-Algebraic Systems and Weighted Simple omega-Pushdown Automata}},
  booktitle =	{39th IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS 2019)},
  pages =	{38:1--38:14},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-131-3},
  ISSN =	{1868-8969},
  year =	{2019},
  volume =	{150},
  editor =	{Chattopadhyay, Arkadev and Gastin, Paul},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.FSTTCS.2019.38},
  URN =		{urn:nbn:de:0030-drops-116003},
  doi =		{10.4230/LIPIcs.FSTTCS.2019.38},
  annote =	{Keywords: Weighted omega-Context-Free Grammars, Algebraic Systems, Greibach Normal Form, Weighted Automata, omega-Pushdown Automata}
}
Document
Short Paper
DOI: 10.4230/LIPIcs.COSIT.2019.10
Talk of the Town: Discovering Open Public Data via Voice Assistants (Short Paper)

Authors: Sara Lafia, Jingyi Xiao, Thomas Hervey, and Werner Kuhn

Published in: LIPIcs, Volume 142, 14th International Conference on Spatial Information Theory (COSIT 2019)

Abstract
Access to public data in the United States and elsewhere has steadily increased as governments have launched geospatially-enabled web portals like Socrata, CKAN, and Esri Hub. However, data discovery in these portals remains a challenge for the average user. Differences between users' colloquial search terms and authoritative metadata impede data discovery. For example, a motivated user with expertise can leverage valuable public data about transportation, real estate values, and crime, yet it remains difficult for the average user to discover and leverage data. To close this gap, community dashboards that use public data are being developed to track initiatives for public consumption; however, dashboards still require users to discover and interpret data. Alternatively, local governments are now developing data discovery systems that use voice assistants like Amazon Alexa and Google Home as conversational interfaces to public data portals. We explore these emerging technologies, examining the application areas they are designed to address and the degree to which they currently leverage existing open public geospatial data. In the context of ongoing technological advances, we envision using core concepts of spatial information to organize the geospatial themes of data exposed through voice assistant applications. This will allow us to curate them for improved discovery, ultimately supporting more meaningful user questions and their translation into spatial computations.
Cite as

Sara Lafia, Jingyi Xiao, Thomas Hervey, and Werner Kuhn. Talk of the Town: Discovering Open Public Data via Voice Assistants (Short Paper). In 14th International Conference on Spatial Information Theory (COSIT 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 142, pp. 10:1-10:7, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)

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@InProceedings{lafia_et_al:LIPIcs.COSIT.2019.10,
  author =	{Lafia, Sara and Xiao, Jingyi and Hervey, Thomas and Kuhn, Werner},
  title =	{{Talk of the Town: Discovering Open Public Data via Voice Assistants}},
  booktitle =	{14th International Conference on Spatial Information Theory (COSIT 2019)},
  pages =	{10:1--10:7},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-115-3},
  ISSN =	{1868-8969},
  year =	{2019},
  volume =	{142},
  editor =	{Timpf, Sabine and Schlieder, Christoph and Kattenbeck, Markus and Ludwig, Bernd and Stewart, Kathleen},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2019.10},
  URN =		{urn:nbn:de:0030-drops-111026},
  doi =		{10.4230/LIPIcs.COSIT.2019.10},
  annote =	{Keywords: data discovery, open public data, voice assistants, essential model, GIS}
}
Document
DOI: 10.4230/LIPIcs.COSIT.2019.18
Enabling the Discovery of Thematically Related Research Objects with Systematic Spatializations

Authors: Sara Lafia, Christina Last, and Werner Kuhn

Published in: LIPIcs, Volume 142, 14th International Conference on Spatial Information Theory (COSIT 2019)

Abstract
It is challenging for scholars to discover thematically related research in a multidisciplinary setting, such as that of a university library. In this work, we use spatialization techniques to convey the relatedness of research themes without requiring scholars to have specific knowledge of disciplinary search terminology. We approach this task conceptually by revisiting existing spatialization techniques and reframing them in terms of core concepts of spatial information, highlighting their different capacities. To apply our design, we spatialize masters and doctoral theses (two kinds of research objects available through a university library repository) using topic modeling to assign a relatively small number of research topics to the objects. We discuss and implement two distinct spaces for exploration: a field view of research topics and a network view of research objects. We find that each space enables distinct visual perceptions and questions about the relatedness of research themes. A field view enables questions about the distribution of research objects in the topic space, while a network view enables questions about connections between research objects or about their centrality. Our work contributes to spatialization theory a systematic choice of spaces informed by core concepts of spatial information. Its application to the design of library discovery tools offers two distinct and intuitive ways to gain insights into the thematic relatedness of research objects, regardless of the disciplinary terms used to describe them.
Cite as

Sara Lafia, Christina Last, and Werner Kuhn. Enabling the Discovery of Thematically Related Research Objects with Systematic Spatializations. In 14th International Conference on Spatial Information Theory (COSIT 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 142, pp. 18:1-18:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)

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@InProceedings{lafia_et_al:LIPIcs.COSIT.2019.18,
  author =	{Lafia, Sara and Last, Christina and Kuhn, Werner},
  title =	{{Enabling the Discovery of Thematically Related Research Objects with Systematic Spatializations}},
  booktitle =	{14th International Conference on Spatial Information Theory (COSIT 2019)},
  pages =	{18:1--18:14},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-115-3},
  ISSN =	{1868-8969},
  year =	{2019},
  volume =	{142},
  editor =	{Timpf, Sabine and Schlieder, Christoph and Kattenbeck, Markus and Ludwig, Bernd and Stewart, Kathleen},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2019.18},
  URN =		{urn:nbn:de:0030-drops-111102},
  doi =		{10.4230/LIPIcs.COSIT.2019.18},
  annote =	{Keywords: spatialization, core concepts of spatial information, information discovery}
}
Document
DOI: 10.4230/LIPIcs.TQC.2019.9
Approximate Unitary n^{2/3}-Designs Give Rise to Quantum Channels with Super Additive Classical Holevo Capacity

Authors: Aditya Nema and Pranab Sen

Published in: LIPIcs, Volume 135, 14th Conference on the Theory of Quantum Computation, Communication and Cryptography (TQC 2019)

Abstract
In a breakthrough, Hastings [2009] showed that there exist quantum channels whose classical Holevo capacity is superadditive i.e. more classical information can be transmitted by quantum encoding strategies entangled across multiple channel uses as compared to unentangled quantum encoding strategies. Hastings' proof used Haar random unitaries to exhibit superadditivity. In this paper we show that a unitary chosen uniformly at random from an approximate n^{2/3}-design gives rise to a quantum channel with superadditive classical Holevo capacity, where n is the dimension of the unitary exhibiting the Stinespring dilation of the channel superoperator. We do so by showing that the minimum output von Neumann entropy of a quantum channel arising from an approximate unitary n^{2/3}-design is subadditive, which by Shor’s work [2002] implies superadditivity of classical Holevo capacity of quantum channels. We follow the geometric functional analytic approach of Aubrun, Szarek and Werner [Aubrun et al., 2010] in order to prove our result. More precisely we prove a sharp Dvoretzky-like theorem stating that, with high probability under the choice of a unitary from an approximate t-design, random subspaces of large dimension make a Lipschitz function take almost constant value. Such theorems were known earlier only for Haar random unitaries. We obtain our result by appealing to Low’s technique [2009] for proving concentration of measure for an approximate t-design, combined with a stratified analysis of the variational behaviour of Lipschitz functions on the unit sphere in high dimension. The stratified analysis is the main technical advance of this work. Haar random unitaries require at least Omega(n^2) random bits in order to describe them with good precision. In contrast, there exist exact n^{2/3}-designs using only O(n^{2/3} log n) random bits [Kuperberg, 2006]. Thus, our work can be viewed as a partial derandomisation of Hastings' result, and a step towards the quest of finding an explicit quantum channel with superadditive classical Holevo capacity.
Cite as

Aditya Nema and Pranab Sen. Approximate Unitary n^{2/3}-Designs Give Rise to Quantum Channels with Super Additive Classical Holevo Capacity. In 14th Conference on the Theory of Quantum Computation, Communication and Cryptography (TQC 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 135, pp. 9:1-9:22, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)

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@InProceedings{nema_et_al:LIPIcs.TQC.2019.9,
  author =	{Nema, Aditya and Sen, Pranab},
  title =	{{Approximate Unitary n^\{2/3\}-Designs Give Rise to Quantum Channels with Super Additive Classical Holevo Capacity}},
  booktitle =	{14th Conference on the Theory of Quantum Computation, Communication and Cryptography (TQC 2019)},
  pages =	{9:1--9:22},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-112-2},
  ISSN =	{1868-8969},
  year =	{2019},
  volume =	{135},
  editor =	{van Dam, Wim and Man\v{c}inska, Laura},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.TQC.2019.9},
  URN =		{urn:nbn:de:0030-drops-104015},
  doi =		{10.4230/LIPIcs.TQC.2019.9},
  annote =	{Keywords: classical Holevo capacity, super additivity, Haar measure, approximate unitary t-design, polyomial approximation}
}
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

Published in: Dagstuhl Manifestos, Volume 7, Issue 1 (2018)

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)

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@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-dev.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}
}
Document
DOI: 10.4230/LIPIcs.GISCIENCE.2018.9
Improving Discovery of Open Civic Data

Authors: Sara Lafia, Andrew Turner, and Werner Kuhn

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

Abstract
We describe a method and system design for improved data discovery in an integrated network of open geospatial data that supports collaborative policy development between governments and local constituents. Metadata about civic data (such as thematic categories, user-generated tags, geo-references, or attribute schemata) primarily rely on technical vocabularies that reflect scientific or organizational hierarchies. By contrast, public consumers of data often search for information using colloquial terminology that does not align with official metadata vocabularies. For example, citizens searching for data about bicycle collisions in an area are unlikely to use the search terms with which organizations like Departments of Transportation describe relevant data. Users may also search with broad terms, such as "traffic safety", and will then not discover data tagged with narrower official terms, such as "vehicular crash". This mismatch raises the question of how to bridge the users' ways of talking and searching with the language of technical metadata. In similar situations, it has been beneficial to augment official metadata with semantic annotations that expand the discoverability and relevance recommendations of data, supporting more inclusive access. Adopting this strategy, we develop a method for automated semantic annotation, which aggregates similar thematic and geographic information. A novelty of our approach is the development and application of a crosscutting base vocabulary that supports the description of geospatial themes. The resulting annotation method is integrated into a novel open access collaboration platform (Esri's ArcGIS Hub) that supports public dissemination of civic data and is in use by thousands of government agencies. Our semantic annotation method improves data discovery for users across organizational repositories and has the potential to facilitate the coordination of community and organizational work, improving the transparency and efficacy of government policies.
Cite as

Sara Lafia, Andrew Turner, and Werner Kuhn. Improving Discovery of Open Civic Data. In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 9:1-9:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)

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@InProceedings{lafia_et_al:LIPIcs.GISCIENCE.2018.9,
  author =	{Lafia, Sara and Turner, Andrew and Kuhn, Werner},
  title =	{{Improving Discovery of Open Civic Data}},
  booktitle =	{10th International Conference on Geographic Information Science (GIScience 2018)},
  pages =	{9:1--9:15},
  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.2018.9},
  URN =		{urn:nbn:de:0030-drops-93376},
  doi =		{10.4230/LIPIcs.GISCIENCE.2018.9},
  annote =	{Keywords: data discovery, metadata, query expansion, interoperability}
}
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}
}
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