15 Search Results for "Raubal, Martin"

Document
DOI: 10.4230/LIPIcs.GIScience.2025.16
What, When, and Where Do You Mean? Detecting Spatio-Temporal Concept Drift in Scientific Texts

Authors: Meilin Shi, Krzysztof Janowicz, Zilong Liu, Mina Karimi, Ivan Majic, and Alexandra Fortacz

Published in: LIPIcs, Volume 346, 13th International Conference on Geographic Information Science (GIScience 2025)

Abstract
Inundated by the rapidly expanding AI research nowadays, the research community requires more effective research data management than ever. A key challenge lies in the evolving nature of concepts embedded in the growing body of research publications. As concepts evolve over time (e.g., keywords like global warming become more commonly referred to as climate change), past research may become harder to find and interpret in a modern context. This phenomenon, known as concept drift, affects how research topics and keywords are understood, categorized, and retrieved. Beyond temporal drift, such variations also occur across geographic space, reflecting differences in local policies, research priorities, and so forth. In this work, we introduce the notion of spatio-temporal concept drift to capture how concepts in scientific texts evolve across both space and time. Using a scientometric dataset in geographic information science, we detect how research keywords drifted across countries and years using word embeddings. By detecting spatio-temporal concept drift, we can better align archival research and bridge regional differences, ensuring scientific knowledge remains findable and interoperable within evolving research landscapes.
Cite as

Meilin Shi, Krzysztof Janowicz, Zilong Liu, Mina Karimi, Ivan Majic, and Alexandra Fortacz. What, When, and Where Do You Mean? Detecting Spatio-Temporal Concept Drift in Scientific Texts. In 13th International Conference on Geographic Information Science (GIScience 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 346, pp. 16:1-16:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{shi_et_al:LIPIcs.GIScience.2025.16,
  author =	{Shi, Meilin and Janowicz, Krzysztof and Liu, Zilong and Karimi, Mina and Majic, Ivan and Fortacz, Alexandra},
  title =	{{What, When, and Where Do You Mean? Detecting Spatio-Temporal Concept Drift in Scientific Texts}},
  booktitle =	{13th International Conference on Geographic Information Science (GIScience 2025)},
  pages =	{16:1--16:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-378-2},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{346},
  editor =	{Sila-Nowicka, Katarzyna and Moore, Antoni and O'Sullivan, David and Adams, Benjamin and Gahegan, Mark},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.GIScience.2025.16},
  URN =		{urn:nbn:de:0030-drops-238450},
  doi =		{10.4230/LIPIcs.GIScience.2025.16},
  annote =	{Keywords: Concept Drift, Ontology, Large Language Models, Research Data Management}
}
Document
DOI: 10.4230/LIPIcs.GIScience.2025.5
Analysis of Points of Interests Recommended for Leisure Walk Descriptions

Authors: Ehsan Hamzei, Thi Minh Hoai Bui, Martin Tomko, and Stephan Winter

Published in: LIPIcs, Volume 346, 13th International Conference on Geographic Information Science (GIScience 2025)

Abstract
Leisure walking is a physical activity where locomotion through a natural or even urban environment is the goal in itself, e.g., in pursuit of health and wellbeing. In contrast to destination-oriented walks that are focused on navigation efficiency (i.e., shortest or simplest walk from source to destination), leisure walks emphasize experiencing the environment, engaging in activities, and discovering places that may be off route, or intermediate destinations en-route, summarily called points of interest (POIs). POIs are key for recommending leisure walks, yet a detailed analysis of POIs in the context of leisure walking is missing in the literature. This study extracts and annotates POIs of leisure walking recommendations available in WalkingMaps.com.au, creating an annotated dataset to address this research gap and provide a first analysis of leisure walking descriptions. We classify POIs using the verbal description provided in the dataset, match them with data available in OpenStreetMap (OSM), and compare the POIs with nearby alternatives in OSM. Our analysis reveals thematic and spatial patterns in POI selection, offering a machine learning approach to model POI choices for leisure walks. We further evaluate the availability of rich data in OSM for future automated leisure walking recommendation. This study contributes to automated systems for recommending leisure walks, tailoring suggestions based on available information in the spatial open data, and presents an annotated dataset to facilitate future research in this field.
Cite as

Ehsan Hamzei, Thi Minh Hoai Bui, Martin Tomko, and Stephan Winter. Analysis of Points of Interests Recommended for Leisure Walk Descriptions. In 13th International Conference on Geographic Information Science (GIScience 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 346, pp. 5:1-5:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{hamzei_et_al:LIPIcs.GIScience.2025.5,
  author =	{Hamzei, Ehsan and Bui, Thi Minh Hoai and Tomko, Martin and Winter, Stephan},
  title =	{{Analysis of Points of Interests Recommended for Leisure Walk Descriptions}},
  booktitle =	{13th International Conference on Geographic Information Science (GIScience 2025)},
  pages =	{5:1--5:16},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-378-2},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{346},
  editor =	{Sila-Nowicka, Katarzyna and Moore, Antoni and O'Sullivan, David and Adams, Benjamin and Gahegan, Mark},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.GIScience.2025.5},
  URN =		{urn:nbn:de:0030-drops-238341},
  doi =		{10.4230/LIPIcs.GIScience.2025.5},
  annote =	{Keywords: leisure walks, points of interest, places, platial information}
}
Document
DOI: 10.4230/LIPIcs.GIScience.2025.3
Enriching Location Representation with Detailed Semantic Information

Authors: Junyuan Liu, Xinglei Wang, and Tao Cheng

Published in: LIPIcs, Volume 346, 13th International Conference on Geographic Information Science (GIScience 2025)

Abstract
Spatial representations that capture both structural and semantic characteristics of urban environments are essential for urban modeling. Traditional spatial embeddings often prioritize spatial proximity while underutilizing fine-grained contextual information from places. To address this limitation, we introduce CaLLiPer+, an extension of the CaLLiPer model that systematically integrates Point-of-Interest (POI) names alongside categorical labels within a multimodal contrastive learning framework. We evaluate its effectiveness on two downstream tasks - land use classification and socioeconomic status distribution mapping - demonstrating consistent performance gains of 4% to 11% over baseline methods. Additionally, we show that incorporating POI names enhances location retrieval, enabling models to capture complex urban concepts with greater precision. Ablation studies further reveal the complementary role of POI names and the advantages of leveraging pretrained text encoders for spatial representations. Overall, our findings highlight the potential of integrating fine-grained semantic attributes and multimodal learning techniques to advance the development of urban foundation models.
Cite as

Junyuan Liu, Xinglei Wang, and Tao Cheng. Enriching Location Representation with Detailed Semantic Information. In 13th International Conference on Geographic Information Science (GIScience 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 346, pp. 3:1-3:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{liu_et_al:LIPIcs.GIScience.2025.3,
  author =	{Liu, Junyuan and Wang, Xinglei and Cheng, Tao},
  title =	{{Enriching Location Representation with Detailed Semantic Information}},
  booktitle =	{13th International Conference on Geographic Information Science (GIScience 2025)},
  pages =	{3:1--3:15},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-378-2},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{346},
  editor =	{Sila-Nowicka, Katarzyna and Moore, Antoni and O'Sullivan, David and Adams, Benjamin and Gahegan, Mark},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.GIScience.2025.3},
  URN =		{urn:nbn:de:0030-drops-238322},
  doi =		{10.4230/LIPIcs.GIScience.2025.3},
  annote =	{Keywords: Location Embedding, Contrastive Learning, Pretrained Model}
}
Artifact
Software
DOI: 10.4230/artifacts.22489
Cognitive Route Planning

Authors: Ayda Grisiute

Abstract
Cite as

Ayda Grisiute. Cognitive Route Planning (Software). Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@misc{dagstuhl-artifact-22489,
   title = {{Cognitive Route Planning}}, 
   author = {Grisiute, Ayda},
   note = {Software, swhId: \href{https://archive.softwareheritage.org/swh:1:dir:5720b0f26f85d4566df66b9fe80d47e111a00a66;origin=https://github.com/mie-lab/cognitive_route_planning;visit=swh:1:snp:1f82588f293700f4ec0fd169040a7d4498f9b234;anchor=swh:1:rev:f961ea201a28f5d0cad375fb8f52ac0949b7fba5}{\texttt{swh:1:dir:5720b0f26f85d4566df66b9fe80d47e111a00a66}} (visited on 2024-11-28)},
   url = {https://github.com/mie-lab/cognitive_route_planning},
   doi = {10.4230/artifacts.22489},
}
Document
DOI: 10.4230/LIPIcs.COSIT.2024.3
Can You Sketch in 3D? Exploring Perceived Feasibility and Use Cases of 3D Sketch Mapping

Authors: Kevin Gonyop Kim, Tiffany C.K. Kwok, Sailin Zhong, Peter Kiefer, and Martin Raubal

Published in: LIPIcs, Volume 315, 16th International Conference on Spatial Information Theory (COSIT 2024)

Abstract
Sketch mapping is a research technique that has been widely used to study what people think about the spatial layout of an environment. One of the limitations of the current practice of sketch mapping is that the interface (a pen on paper or digital tablets) forces people to draw on 2D surfaces even when the information to be represented is 3D. For the purpose of studying the 3D aspect of spatial understanding, the recent advancements in extended reality (XR) technologies including virtual reality, augmented reality, and mixed reality are interesting as they provide novel ways to create 3D sketches. In this paper, we investigate how the concept of 3D sketch mapping using XR is perceived by users and explore its potential feasibility and use cases. For this, we conducted semi-structured interviews with 27 participants from three domains: aviation, architecture, and wayfinding. Our findings show that the concept is well-perceived as an intuitive way to externalize the 3D aspect of spatial information, and it has the potential to be a research tool for human cognition research as well as a practical tool that can provide added value in different professional activities.
Cite as

Kevin Gonyop Kim, Tiffany C.K. Kwok, Sailin Zhong, Peter Kiefer, and Martin Raubal. Can You Sketch in 3D? Exploring Perceived Feasibility and Use Cases of 3D Sketch Mapping. In 16th International Conference on Spatial Information Theory (COSIT 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 315, pp. 3:1-3:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{kim_et_al:LIPIcs.COSIT.2024.3,
  author =	{Kim, Kevin Gonyop and Kwok, Tiffany C.K. and Zhong, Sailin and Kiefer, Peter and Raubal, Martin},
  title =	{{Can You Sketch in 3D? Exploring Perceived Feasibility and Use Cases of 3D Sketch Mapping}},
  booktitle =	{16th International Conference on Spatial Information Theory (COSIT 2024)},
  pages =	{3:1--3:17},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-330-0},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{315},
  editor =	{Adams, Benjamin and Griffin, Amy L. and Scheider, Simon and McKenzie, Grant},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2024.3},
  URN =		{urn:nbn:de:0030-drops-208186},
  doi =		{10.4230/LIPIcs.COSIT.2024.3},
  annote =	{Keywords: Sketch maps, spatial understanding, 3D sketching, extended reality, use cases, interviews}
}
Document
DOI: 10.4230/LIPIcs.COSIT.2024.5
Spatial Nudging: Converging Persuasive Technologies, Spatial Design, and Behavioral Theories

Authors: Ayda Grisiute and Martin Raubal

Published in: LIPIcs, Volume 315, 16th International Conference on Spatial Information Theory (COSIT 2024)

Abstract
This paper presents the Spatial Nudging framework - a theory-based framework that maps out nudging strategies in the mobility domain and refines its existing definitions. We link these strategies by highlighting the role of perceived affordances across physical and digital interventions based on the Nudge Theory and the Theory of Affordances. Furthermore, we propose to use graph representation techniques as a supportive methodology to better align perceived and actual environments, thereby enhancing the intervention strategies' effectiveness. We illustrate the applicability of the Spatial Nudging framework and the supportive methodology in the context of an E-bike City vision. This paper lays the foundation for future research on theoretically integrating physical and digital interventions to promote sustainable mobility.
Cite as

Ayda Grisiute and Martin Raubal. Spatial Nudging: Converging Persuasive Technologies, Spatial Design, and Behavioral Theories. In 16th International Conference on Spatial Information Theory (COSIT 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 315, pp. 5:1-5:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{grisiute_et_al:LIPIcs.COSIT.2024.5,
  author =	{Grisiute, Ayda and Raubal, Martin},
  title =	{{Spatial Nudging: Converging Persuasive Technologies, Spatial Design, and Behavioral Theories}},
  booktitle =	{16th International Conference on Spatial Information Theory (COSIT 2024)},
  pages =	{5:1--5:19},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-330-0},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{315},
  editor =	{Adams, Benjamin and Griffin, Amy L. and Scheider, Simon and McKenzie, Grant},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2024.5},
  URN =		{urn:nbn:de:0030-drops-208206},
  doi =		{10.4230/LIPIcs.COSIT.2024.5},
  annote =	{Keywords: spatial nudging, active mobility, Nudge Theory, Theory of Affordances, cognitive graphs}
}
Document
DOI: 10.4230/LIPIcs.COSIT.2024.6
Is Familiarity Reflected in the Spatial Knowledge Revealed by Sketch Maps?

Authors: Markus Kattenbeck, Daniel R. Montello, Martin Raubal, and Ioannis Giannopoulos

Published in: LIPIcs, Volume 315, 16th International Conference on Spatial Information Theory (COSIT 2024)

Abstract
Despite the frequent use of sketch maps in assessing environmental knowledge, it remains unclear how and to what degree familiarity impacts sketch map content. In the present study, we assess whether different levels of familiarity relate to differences in the content and spatial accuracy of environmental knowledge depicted in sketch maps drawn for the purpose of route instructions. To this end, we conduct a real-world wayfinding study with 91 participants, all of whom have to walk along a pre-defined route of approximately 2.3km length. Prior to the walk, we collect self-report familiarity ratings from participants for both a set of 15 landmarks and a set of areas we define as hexagons along the route. Once participants finished walking the route, they were asked to sketch a map of the route, specifically a sketch that would enable a person who had never walked the route to follow it. We found that participants unfamiliar with the areas along the route sketched fewer features than familiar people did. Contrary to our expectations, however, we found that landmarks were sketched or not regardless of participants' level of familiarity with the landmarks. We were also surprised that the level of familiarity was not correlated to the accuracy of the sketched order of features along the route, of the position of sketched features in relation to the route, nor to the metric locational accuracy of feature placement on the sketches. These results lead us to conclude that different aspects of feature salience influence whether the features are included on sketch maps, independent of familiarity. They also point to the influence of task context on the content of sketch maps, again independent of familiarity. We propose further studies to more fully explore these ideas.
Cite as

Markus Kattenbeck, Daniel R. Montello, Martin Raubal, and Ioannis Giannopoulos. Is Familiarity Reflected in the Spatial Knowledge Revealed by Sketch Maps?. In 16th International Conference on Spatial Information Theory (COSIT 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 315, pp. 6:1-6:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{kattenbeck_et_al:LIPIcs.COSIT.2024.6,
  author =	{Kattenbeck, Markus and Montello, Daniel R. and Raubal, Martin and Giannopoulos, Ioannis},
  title =	{{Is Familiarity Reflected in the Spatial Knowledge Revealed by Sketch Maps?}},
  booktitle =	{16th International Conference on Spatial Information Theory (COSIT 2024)},
  pages =	{6:1--6:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-330-0},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{315},
  editor =	{Adams, Benjamin and Griffin, Amy L. and Scheider, Simon and McKenzie, Grant},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2024.6},
  URN =		{urn:nbn:de:0030-drops-208215},
  doi =		{10.4230/LIPIcs.COSIT.2024.6},
  annote =	{Keywords: Familiarity, Spatial Knowledge, Sketch Maps}
}
Document
DOI: 10.4230/LIPIcs.GIScience.2023.11
Benchmarking Regression Models Under Spatial Heterogeneity

Authors: Nina Wiedemann, Henry Martin, and René Westerholt

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

Abstract
Machine learning methods have recently found much application on spatial data, for example in weather forecasting, traffic prediction, and soil analysis. At the same time, methods from spatial statistics were developed over the past decades to explicitly account for spatial structuring in analytical and inference tasks. In the light of this duality of having both types of methods available, we explore the following question: Under what circumstances are local, spatially-explicit models preferable over machine learning models that do not incorporate spatial structure explicitly in their specification? Local models are typically used to capture spatial non-stationarity. Thus, we study the effect of strength and type of spatial heterogeneity, which may originate from non-stationarity of a process itself or from heterogeneous noise, on the performance of different linear and non-linear, local and global machine learning and regression models. The results suggest that it is necessary to assess the performance of linear local models on an independent hold-out dataset, since models may overfit under certain conditions. We further show that local models are advantageous in settings with small sample size and high degrees of spatial heterogeneity. Our findings allow deriving model selection criteria, which are validated in benchmarking experiments on five well-known spatial datasets.
Cite as

Nina Wiedemann, Henry Martin, and René Westerholt. Benchmarking Regression Models Under Spatial Heterogeneity. In 12th International Conference on Geographic Information Science (GIScience 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 277, pp. 11:1-11:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{wiedemann_et_al:LIPIcs.GIScience.2023.11,
  author =	{Wiedemann, Nina and Martin, Henry and Westerholt, Ren\'{e}},
  title =	{{Benchmarking Regression Models Under Spatial Heterogeneity}},
  booktitle =	{12th International Conference on Geographic Information Science (GIScience 2023)},
  pages =	{11:1--11:15},
  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.dagstuhl.de/entities/document/10.4230/LIPIcs.GIScience.2023.11},
  URN =		{urn:nbn:de:0030-drops-189064},
  doi =		{10.4230/LIPIcs.GIScience.2023.11},
  annote =	{Keywords: spatial machine learning, spatial non-stationarity, Geographically Weighted Regression, local models, geostatistics}
}
Document
Short Paper
DOI: 10.4230/LIPIcs.GIScience.2023.84
Predicting visit frequencies to new places (Short Paper)

Authors: Nina Wiedemann, Ye Hong, and Martin Raubal

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

Abstract
Human mobility exhibits power-law distributed visitation patterns; i.e., a few locations are visited frequently and many locations only once. Current research focuses on the important locations of users or on recommending new places based on collective behaviour, neglecting the existence of scarcely visited locations. However, assessing whether a user will return to a location in the future is highly relevant for personalized location-based services. Therefore, we propose a new problem formulation aimed at predicting the future visit frequency to a new location, focusing on the previous mobility behaviour of a single user. Our preliminary results demonstrate that visit frequency prediction is a difficult task, but sophisticated learning models can detect insightful patterns in the historic mobility indicative of future visit frequency. We believe these models can uncover valuable insights into the spatial factors that drive individual mobility behaviour.
Cite as

Nina Wiedemann, Ye Hong, and Martin Raubal. Predicting visit frequencies to new places (Short Paper). In 12th International Conference on Geographic Information Science (GIScience 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 277, pp. 84:1-84:6, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{wiedemann_et_al:LIPIcs.GIScience.2023.84,
  author =	{Wiedemann, Nina and Hong, Ye and Raubal, Martin},
  title =	{{Predicting visit frequencies to new places}},
  booktitle =	{12th International Conference on Geographic Information Science (GIScience 2023)},
  pages =	{84:1--84:6},
  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.dagstuhl.de/entities/document/10.4230/LIPIcs.GIScience.2023.84},
  URN =		{urn:nbn:de:0030-drops-189794},
  doi =		{10.4230/LIPIcs.GIScience.2023.84},
  annote =	{Keywords: Human mobility, Visitation patterns, Place recommendation, Next location prediction}
}
Document
Short Paper
DOI: 10.4230/LIPIcs.COSIT.2022.14
3D Sketch Maps: Concept, Potential Benefits, and Challenges (Short Paper)

Authors: Kevin Gonyop Kim, Jakub Krukar, Panagiotis Mavros, Jiayan Zhao, Peter Kiefer, Angela Schwering, Christoph Hölscher, and Martin Raubal

Published in: LIPIcs, Volume 240, 15th International Conference on Spatial Information Theory (COSIT 2022)

Abstract
Studying the 3D aspect of spatial information has become increasingly important due to changes in the way we interact with the surrounding environments as well as technological innovations. Current pen-and-paper approaches of sketch mapping have a limitation in investigating 3D spatial knowledge as they are forced to be drawn on 2D interfaces. In this paper, we propose the concept of 3D sketch mapping as a tool to study human spatial knowledge by externalizing the mental models of spatial information with 3D representations. The goal of this paper is to introduce the concept, discuss its potential importance and challenges, and share our vision for future research directions.
Cite as

Kevin Gonyop Kim, Jakub Krukar, Panagiotis Mavros, Jiayan Zhao, Peter Kiefer, Angela Schwering, Christoph Hölscher, and Martin Raubal. 3D Sketch Maps: Concept, Potential Benefits, and Challenges (Short Paper). In 15th International Conference on Spatial Information Theory (COSIT 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 240, pp. 14:1-14:7, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)

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@InProceedings{kim_et_al:LIPIcs.COSIT.2022.14,
  author =	{Kim, Kevin Gonyop and Krukar, Jakub and Mavros, Panagiotis and Zhao, Jiayan and Kiefer, Peter and Schwering, Angela and H\"{o}lscher, Christoph and Raubal, Martin},
  title =	{{3D Sketch Maps: Concept, Potential Benefits, and Challenges}},
  booktitle =	{15th International Conference on Spatial Information Theory (COSIT 2022)},
  pages =	{14:1--14:7},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-257-0},
  ISSN =	{1868-8969},
  year =	{2022},
  volume =	{240},
  editor =	{Ishikawa, Toru and Fabrikant, Sara Irina and Winter, Stephan},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2022.14},
  URN =		{urn:nbn:de:0030-drops-168992},
  doi =		{10.4230/LIPIcs.COSIT.2022.14},
  annote =	{Keywords: Sketch maps, mental representations, spatial knowledge}
}
Document
DOI: 10.4230/LIPIcs.GIScience.2021.II.4
A Clustering-Based Framework for Individual Travel Behaviour Change Detection

Authors: Ye Hong, Yanan Xin, Henry Martin, Dominik Bucher, and Martin Raubal

Published in: LIPIcs, Volume 208, 11th International Conference on Geographic Information Science (GIScience 2021) - Part II

Abstract
The emergence of passively and continuously recorded movement data offers new opportunities to study the long-term change of individual travel behaviour from data-driven perspectives. This study proposes a clustering-based framework to identify travel behaviour patterns and detect potential change periods on the individual level. First, we extract important trips that depict individual characteristic movement. Then, considering trip mode, trip distance, and trip duration as travel behaviour dimensions, we measure the similarities of trips and group them into clusters using hierarchical clustering. The trip clusters represent dimensions of travel behaviours, and the change of their relative proportions over time reflect the development of travel preferences. We use two different methods to detect changes in travel behaviour patterns: the Herfindahl-Hirschman index-based method and the sliding window-based method. The framework is tested using data from a large-scale longitudinal GPS tracking data study in which participants had access to a Mobility-as-a-Service (MaaS) offer. The methods successfully identify significant travel behaviour changes for users. Moreover, we analyse the impact of the MaaS offer on individual travel behaviours with the obtained change information. The proposed framework for behaviour change detection provides valuable insights for travel demand management and evaluating people’s reactions to sustainable mobility options.
Cite as

Ye Hong, Yanan Xin, Henry Martin, Dominik Bucher, and Martin Raubal. A Clustering-Based Framework for Individual Travel Behaviour Change Detection. In 11th International Conference on Geographic Information Science (GIScience 2021) - Part II. Leibniz International Proceedings in Informatics (LIPIcs), Volume 208, pp. 4:1-4:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)

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@InProceedings{hong_et_al:LIPIcs.GIScience.2021.II.4,
  author =	{Hong, Ye and Xin, Yanan and Martin, Henry and Bucher, Dominik and Raubal, Martin},
  title =	{{A Clustering-Based Framework for Individual Travel Behaviour Change Detection}},
  booktitle =	{11th International Conference on Geographic Information Science (GIScience 2021) - Part II},
  pages =	{4:1--4:15},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-208-2},
  ISSN =	{1868-8969},
  year =	{2021},
  volume =	{208},
  editor =	{Janowicz, Krzysztof and Verstegen, Judith A.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.GIScience.2021.II.4},
  URN =		{urn:nbn:de:0030-drops-147635},
  doi =		{10.4230/LIPIcs.GIScience.2021.II.4},
  annote =	{Keywords: Human mobility, Travel behaviour, Change detection, Trip clustering}
}
Document
DOI: 10.4230/LIPIcs.GIScience.2021.I.2
Estimation of Moran’s I in the Context of Uncertain Mobile Sensor Measurements

Authors: Dominik Bucher, Henry Martin, David Jonietz, Martin Raubal, and René Westerholt

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

Abstract
Measures of spatial autocorrelation like Moran’s I do not take into account information about the reliability of observations. In a context of mobile sensors, however, this is an important aspect to consider. Mobile sensors record data asynchronously and capture different contexts, which leads to considerable heterogeneity. In this paper we propose two different ways to integrate the reliability of observations with Moran’s I. These proposals are tested in the light of two case studies, one based on real temperatures and movement data and the other using synthetic data. The results show that the way reliability information is incorporated into the Moran’s I estimates has a strong impact on how the measure responds to volatile available information. It is shown that absolute reliability information is much less powerful in addressing the problem of differing contexts than relative concepts that give more weight to more reliable observations, regardless of the general degree of uncertainty. The results presented are seen as an important stimulus for the discourse on spatial autocorrelation measures in the light of uncertainties.
Cite as

Dominik Bucher, Henry Martin, David Jonietz, Martin Raubal, and René Westerholt. Estimation of Moran’s I in the Context of Uncertain Mobile Sensor Measurements. In 11th International Conference on Geographic Information Science (GIScience 2021) - Part I. Leibniz International Proceedings in Informatics (LIPIcs), Volume 177, pp. 2:1-2:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)

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@InProceedings{bucher_et_al:LIPIcs.GIScience.2021.I.2,
  author =	{Bucher, Dominik and Martin, Henry and Jonietz, David and Raubal, Martin and Westerholt, Ren\'{e}},
  title =	{{Estimation of Moran’s I in the Context of Uncertain Mobile Sensor Measurements}},
  booktitle =	{11th International Conference on Geographic Information Science (GIScience 2021) - Part I},
  pages =	{2:1--2:15},
  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.dagstuhl.de/entities/document/10.4230/LIPIcs.GIScience.2021.I.2},
  URN =		{urn:nbn:de:0030-drops-130375},
  doi =		{10.4230/LIPIcs.GIScience.2021.I.2},
  annote =	{Keywords: mobile sensors, Moran’s I, uncertainty, probabilistic forecasting}
}
Document
DOI: 10.4230/LIPIcs.GISCIENCE.2018.15
Enhanced Multi Criteria Decision Analysis for Planning Power Transmission Lines

Authors: Joram Schito, Ulrike Wissen Hayek, and Martin Raubal

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

Abstract
The energy transition towards alternative energy sources requires new power transmission lines to connect these additional energy production plants with electricity distribution centers. For this reason, Multi Criteria Decision Analysis (MCDA) offers a useful approach to determine the optimal path of future transmission lines with minimum impact on the environment, on the landscape, and on affected citizens. As objections could deteriorate such a project and in turn increase costs, transparent communication regarding the planning procedure is required that fosters citizens' acceptance. In this context, GIS-based information on the criteria taken into account and for modeling possible power transmission lines is essential. However, planners often forget that the underlying multi criteria decision model and the used data might lead to biased results. Therefore, this study empirically investigates the effect of various MCDA parameters by applying a sensitivity analysis on a multi criteria decision model. The output of this analysis is evaluated combining a Cluster Analysis, a Principal Component Analysis, and a Multivariate Analysis of Variance. Our results indicate that the variability of different corridor alternatives can be increased by using different MCDA parameter combinations. In particular, we found that applying continuous boundary models on areas leads to more distinct corridor alternatives than using a sharp-edged model, and better reflects actual planning practice for protecting areas against transmission lines. Comparing the results of two study areas, we conclude that our decision model behaved similarly across both sites and, hence, that the proposed procedure for enhancing the decision model is applicable to other study areas with comparable topographies. These results can help decision-makers and transmission line planners in simplifying and improving their decision models in order to increase credibility, legitimacy, and thus practical applicability.
Cite as

Joram Schito, Ulrike Wissen Hayek, and Martin Raubal. Enhanced Multi Criteria Decision Analysis for Planning Power Transmission Lines. In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 15:1-15:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)

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@InProceedings{schito_et_al:LIPIcs.GISCIENCE.2018.15,
  author =	{Schito, Joram and Wissen Hayek, Ulrike and Raubal, Martin},
  title =	{{Enhanced Multi Criteria Decision Analysis for Planning Power Transmission Lines}},
  booktitle =	{10th International Conference on Geographic Information Science (GIScience 2018)},
  pages =	{15:1--15:16},
  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.dagstuhl.de/entities/document/10.4230/LIPIcs.GISCIENCE.2018.15},
  URN =		{urn:nbn:de:0030-drops-93438},
  doi =		{10.4230/LIPIcs.GISCIENCE.2018.15},
  annote =	{Keywords: Geographic Information Systems, Transmission Line Planning, Multi-Criteria Decision Analysis, Sensitivity Analysis, Cluster Analysis}
}
Document
Short Paper
DOI: 10.4230/LIPIcs.GISCIENCE.2018.30
Gaze Sequences and Map Task Complexity (Short Paper)

Authors: Fabian Göbel, Peter Kiefer, Ioannis Giannopoulos, and Martin Raubal

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

Abstract
As maps are visual representations of spatial context to communicate geographic information, analysis of gaze behavior is promising to improve map design. In this research we investigate the impact of map task complexity and different legend types on the visual attention of a user. With an eye tracking experiment we could show that the complexity of two map tasks can be measured and compared based on AOI sequences analysis. This knowledge can help to improve map design for static maps or in the context of interactive systems, create better map interfaces, that adapt to the user's current task.
Cite as

Fabian Göbel, Peter Kiefer, Ioannis Giannopoulos, and Martin Raubal. Gaze Sequences and Map Task Complexity (Short Paper). In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 30:1-30:6, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)

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@InProceedings{gobel_et_al:LIPIcs.GISCIENCE.2018.30,
  author =	{G\"{o}bel, Fabian and Kiefer, Peter and Giannopoulos, Ioannis and Raubal, Martin},
  title =	{{Gaze Sequences and Map Task Complexity}},
  booktitle =	{10th International Conference on Geographic Information Science (GIScience 2018)},
  pages =	{30:1--30:6},
  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.dagstuhl.de/entities/document/10.4230/LIPIcs.GISCIENCE.2018.30},
  URN =		{urn:nbn:de:0030-drops-93587},
  doi =		{10.4230/LIPIcs.GISCIENCE.2018.30},
  annote =	{Keywords: eye tracking, sequence analysis, map task complexity}
}
Document
DOI: 10.4230/LIPIcs.COSIT.2017.16
Timing of Pedestrian Navigation Instructions

Authors: Ioannis Giannopoulos, David Jonietz, Martin Raubal, Georgios Sarlas, and Lisa Stähli

Published in: LIPIcs, Volume 86, 13th International Conference on Spatial Information Theory (COSIT 2017)

Abstract
During pedestrian navigation in outdoor urban environments we often utilize assistance systems to support decision-making. These systems help wayfinders by providing relevant information withing the context of their surroundings, e.g., landmark-based instructions of the type "turn left at the church". Next to the instruction type and content, also the timing of the instruction must be considered in order to facilitate the wayfinding process. In this work we present our findings concerning the user and environmental factors that have an impact on the timing of instructions. We applied a survival analysis on data collected through an experiment in a realistic virtual environment in order to analyze the expected distance to the decision point until instructions are needed. The presented results can be used by navigation systems for instruction timing based on the characteristics of the current wayfinder and environment.
Cite as

Ioannis Giannopoulos, David Jonietz, Martin Raubal, Georgios Sarlas, and Lisa Stähli. Timing of Pedestrian Navigation Instructions. In 13th International Conference on Spatial Information Theory (COSIT 2017). Leibniz International Proceedings in Informatics (LIPIcs), Volume 86, pp. 16:1-16:13, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2017)

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@InProceedings{giannopoulos_et_al:LIPIcs.COSIT.2017.16,
  author =	{Giannopoulos, Ioannis and Jonietz, David and Raubal, Martin and Sarlas, Georgios and St\"{a}hli, Lisa},
  title =	{{Timing of Pedestrian Navigation Instructions}},
  booktitle =	{13th International Conference on Spatial Information Theory (COSIT 2017)},
  pages =	{16:1--16:13},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-043-9},
  ISSN =	{1868-8969},
  year =	{2017},
  volume =	{86},
  editor =	{Clementini, Eliseo and Donnelly, Maureen and Yuan, May and Kray, Christian and Fogliaroni, Paolo and Ballatore, Andrea},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2017.16},
  URN =		{urn:nbn:de:0030-drops-77606},
  doi =		{10.4230/LIPIcs.COSIT.2017.16},
  annote =	{Keywords: navigation, wayfinding, instructions, timing, survival analysis}
}
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