Volume
LIPIcs, Volume 240
15th International Conference on Spatial Information Theory (COSIT 2022)
-
Part of:
Series:
Leibniz International Proceedings in Informatics (LIPIcs)
Conference: Conference on Spatial Information Theory (COSIT)
Event
COSIT 2022, September 5-9, 2022, Kobe, JapanEditors
Publication Details
- published at: 2022-08-22
- Publisher: Schloss Dagstuhl – Leibniz-Zentrum für Informatik
- ISBN: 978-3-95977-257-0
- DBLP: db/conf/cosit/cosit2022
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Document
Complete Volume
LIPIcs, Volume 240, COSIT 2022, Complete Volume
Abstract
LIPIcs, Volume 240, COSIT 2022, Complete Volume
Cite as
15th International Conference on Spatial Information Theory (COSIT 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 240, pp. 1-316, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)
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@Proceedings{ishikawa_et_al:LIPIcs.COSIT.2022,
title = {{LIPIcs, Volume 240, COSIT 2022, Complete Volume}},
booktitle = {15th International Conference on Spatial Information Theory (COSIT 2022)},
pages = {1--316},
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-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2022},
URN = {urn:nbn:de:0030-drops-168842},
doi = {10.4230/LIPIcs.COSIT.2022},
annote = {Keywords: LIPIcs, Volume 240, COSIT 2022, Complete Volume}
}
Document
Front Matter
Front Matter, Table of Contents, Preface, Conference Organization
Abstract
Front Matter, Table of Contents, Preface, Conference Organization
Cite as
15th International Conference on Spatial Information Theory (COSIT 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 240, pp. 0:i-0:x, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)
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@InProceedings{ishikawa_et_al:LIPIcs.COSIT.2022.0,
author = {Ishikawa, Toru and Fabrikant, Sara Irina and Winter, Stephan},
title = {{Front Matter, Table of Contents, Preface, Conference Organization}},
booktitle = {15th International Conference on Spatial Information Theory (COSIT 2022)},
pages = {0:i--0:x},
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-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2022.0},
URN = {urn:nbn:de:0030-drops-168854},
doi = {10.4230/LIPIcs.COSIT.2022.0},
annote = {Keywords: Front Matter, Table of Contents, Preface, Conference Organization}
}
Document
What Do You Mean You're in Trafalgar Square? Comparing Distance Thresholds for Geospatial Prepositions
Abstract
Natural language location descriptions frequently describe object locations relative to other objects (the house near the river). Geospatial prepositions (e.g.near) are a key element of these descriptions, and the distances associated with proximity, adjacency and topological prepositions are thought to depend on the context of a specific scene. When referring to the context, we include consideration of properties of the relatum such as its feature type, size and associated image schema. In this paper, we extract spatial descriptions from the Google search engine for nine prepositions across three locations, compare their acceptance thresholds (the distances at which different prepositions are acceptable), and study variations in different contexts using cumulative graphs and scatter plots. Our results show that adjacency prepositions next to and adjacent to are used for a large range of distances, in contrast to beside; and that topological prepositions in, at and on can all be used to indicate proximity as well as containment and collocation. We also found that reference object image schema influences the selection of geospatial prepositions such as near and in.
Cite as
Niloofar Aflaki, Kristin Stock, Christopher B. Jones, Hans Guesgen, Jeremy Morley, and Yukio Fukuzawa. What Do You Mean You're in Trafalgar Square? Comparing Distance Thresholds for Geospatial Prepositions. In 15th International Conference on Spatial Information Theory (COSIT 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 240, pp. 1:1-1:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)
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@InProceedings{aflaki_et_al:LIPIcs.COSIT.2022.1,
author = {Aflaki, Niloofar and Stock, Kristin and Jones, Christopher B. and Guesgen, Hans and Morley, Jeremy and Fukuzawa, Yukio},
title = {{What Do You Mean You're in Trafalgar Square? Comparing Distance Thresholds for Geospatial Prepositions}},
booktitle = {15th International Conference on Spatial Information Theory (COSIT 2022)},
pages = {1:1--1:14},
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-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2022.1},
URN = {urn:nbn:de:0030-drops-168865},
doi = {10.4230/LIPIcs.COSIT.2022.1},
annote = {Keywords: contextual factors, spatial descriptions, acceptance model, spatial template, applicability model, geospatial prepositions}
}
Document
I Can Tell by Your Eyes! Continuous Gaze-Based Turn-Activity Prediction Reveals Spatial Familiarity
Abstract
Spatial familiarity plays an essential role in the wayfinding decision-making process. Recent findings in wayfinding activity recognition domain suggest that wayfinders' turning behavior at junctions is strongly influenced by their spatial familiarity. By continuously monitoring wayfinders' turning behavior as reflected in their eye movements during the decision-making period (i.e., immediately after an instruction is received until reaching the corresponding junction for which the instruction was given), we provide evidence that familiar and unfamiliar wayfinders can be distinguished. By applying a pre-trained XGBoost turning activity classifier on gaze data collected in a real-world wayfinding task with 33 participants, our results suggest that familiar and unfamiliar wayfinders show different onset and intensity of turning behavior. These variations are not only present between the two classes -familiar vs. unfamiliar- but also within each class. The differences in turning-behavior within each class may stem from multiple sources, including different levels of familiarity with the environment.
Cite as
Negar Alinaghi, Markus Kattenbeck, and Ioannis Giannopoulos. I Can Tell by Your Eyes! Continuous Gaze-Based Turn-Activity Prediction Reveals Spatial Familiarity. In 15th International Conference on Spatial Information Theory (COSIT 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 240, pp. 2:1-2:13, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)
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@InProceedings{alinaghi_et_al:LIPIcs.COSIT.2022.2,
author = {Alinaghi, Negar and Kattenbeck, Markus and Giannopoulos, Ioannis},
title = {{I Can Tell by Your Eyes! Continuous Gaze-Based Turn-Activity Prediction Reveals Spatial Familiarity}},
booktitle = {15th International Conference on Spatial Information Theory (COSIT 2022)},
pages = {2:1--2:13},
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-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2022.2},
URN = {urn:nbn:de:0030-drops-168872},
doi = {10.4230/LIPIcs.COSIT.2022.2},
annote = {Keywords: Spatial Familiarity, Gaze-based Activity Recognition, Wayfinding, Machine Learning}
}
Document
Automatically Discovering Conceptual Neighborhoods Using Machine Learning Methods
Abstract
Qualitative spatio-temporal reasoning (QSTR) plays a key role in spatial cognition and artificial intelligence (AI) research. In the past, research and applications of QSTR have often taken place in the context of declarative forms of knowledge representation. For instance, conceptual neighborhoods (CN) and composition tables (CT) of relations are introduced explicitly and utilized for spatial/temporal reasoning. Orthogonal to this line of study, we focus on bottom-up machine learning (ML) approaches to investigate QSTR. More specifically, we are interested in questions of whether similarities between qualitative relations can be learned from data purely based on ML models, and, if so, how these models differ from the ones studied by traditional approaches. To achieve this, we propose a graph-based approach to examine the similarity of relations by analyzing trained ML models. Using various experiments on synthetic data, we demonstrate that the relationships discovered by ML models are well-aligned with CN structures introduced in the (theoretical) literature, for both spatial and temporal reasoning. Noticeably, even with significantly limited qualitative information for training, ML models are still able to automatically construct neighborhood structures. Moreover, patterns of asymmetric similarities between relations are disclosed using such a data-driven approach. To the best of our knowledge, our work is the first to automatically discover CNs without any domain knowledge. Our results can be applied to discovering CNs of any set of jointly exhaustive and pairwise disjoint (JEPD) relations.
Cite as
Ling Cai, Krzysztof Janowicz, and Rui Zhu. Automatically Discovering Conceptual Neighborhoods Using Machine Learning Methods. In 15th International Conference on Spatial Information Theory (COSIT 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 240, pp. 3:1-3:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)
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@InProceedings{cai_et_al:LIPIcs.COSIT.2022.3,
author = {Cai, Ling and Janowicz, Krzysztof and Zhu, Rui},
title = {{Automatically Discovering Conceptual Neighborhoods Using Machine Learning Methods}},
booktitle = {15th International Conference on Spatial Information Theory (COSIT 2022)},
pages = {3:1--3:14},
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-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2022.3},
URN = {urn:nbn:de:0030-drops-168884},
doi = {10.4230/LIPIcs.COSIT.2022.3},
annote = {Keywords: Qualitative Spatial Reasoning, Qualitative Temporal Reasoning, Conceptual Neighborhood, Machine Learning, Knowledge Discovery}
}
Document
Predicting Distance and Direction from Text Locality Descriptions for Biological Specimen Collections
Abstract
A considerable proportion of records that describe biological specimens (flora, soil, invertebrates), and especially those that were collected decades ago, are not attached to corresponding geographical coordinates, but rather have their location described only through textual descriptions (e.g. North Canterbury, Selwyn River near bridge on Springston-Leeston Rd). Without geographical coordinates, millions of records stored in museum collections around the world cannot be mapped. We present a method for predicting the distance and direction associated with human language location descriptions which focuses on the interpretation of geospatial prepositions and the way in which they modify the location represented by an associated reference place name (e.g. near the Manawatu River). We study eight distance-oriented prepositions and eight direction-oriented prepositions and use machine learning regression to predict distance or direction, relative to the reference place name, from a collection of training data. The results show that, compared with a simple baseline, our model improved distance predictions by up to 60% and direction predictions by up to 31%.
Cite as
Ruoxuan Liao, Pragyan P. Das, Christopher B. Jones, Niloofar Aflaki, and Kristin Stock. Predicting Distance and Direction from Text Locality Descriptions for Biological Specimen Collections. In 15th International Conference on Spatial Information Theory (COSIT 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 240, pp. 4:1-4:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)
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@InProceedings{liao_et_al:LIPIcs.COSIT.2022.4,
author = {Liao, Ruoxuan and Das, Pragyan P. and Jones, Christopher B. and Aflaki, Niloofar and Stock, Kristin},
title = {{Predicting Distance and Direction from Text Locality Descriptions for Biological Specimen Collections}},
booktitle = {15th International Conference on Spatial Information Theory (COSIT 2022)},
pages = {4:1--4:15},
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-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2022.4},
URN = {urn:nbn:de:0030-drops-168892},
doi = {10.4230/LIPIcs.COSIT.2022.4},
annote = {Keywords: geospatial prepositions, biological specimen collections, georeferencing, natural language processing, locative expressions, locality descriptions, geoparsing, geocoding, geographic information retrieval, regression, machine learning}
}
Document
An Incremental Algorithm for Handling Qualitative Spatio-Temporal Information
Abstract
In this paper, we present an online (incremental) algorithm for checking the satisfiability of qualitative spatio-temporal data, with direct implications to other fundamental knowledge representation and reasoning problems for such data, like the problems of deductive closure and redundancy removal. In particular, qualitative data come in the form of human-like, symbolic, descriptions such as "region x contains or overlaps region y", which are abundant in the Web of Data. Our approach is also able to maintain, to some extent, any sparse graph structure that may be inherent in the data, i.e., it acts parsimoniously and only tries to infer new information when needed for soundness and completeness. To this end, we complement our practical algorithm with certain theoretical results to assert its correctness and efficiency. A subsequent evaluation with publicly available large-scale real-world and random datasets against the state of the art, shows the interest and promise of our method.
Cite as
Zhiguo Long, Qiyuan Hu, Hua Meng, and Michael Sioutis. An Incremental Algorithm for Handling Qualitative Spatio-Temporal Information. In 15th International Conference on Spatial Information Theory (COSIT 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 240, pp. 5:1-5:13, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)
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@InProceedings{long_et_al:LIPIcs.COSIT.2022.5,
author = {Long, Zhiguo and Hu, Qiyuan and Meng, Hua and Sioutis, Michael},
title = {{An Incremental Algorithm for Handling Qualitative Spatio-Temporal Information}},
booktitle = {15th International Conference on Spatial Information Theory (COSIT 2022)},
pages = {5:1--5:13},
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-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2022.5},
URN = {urn:nbn:de:0030-drops-168907},
doi = {10.4230/LIPIcs.COSIT.2022.5},
annote = {Keywords: Online algorithm, qualitative data, spatio-temporal reasoning, satisfiability checking, knowledge representation and reasoning}
}
Document
Rethinking Route Choices! On the Importance of Route Selection in Wayfinding Experiments
Abstract
Route selection for a wayfinding experiment is not a trivial task and is often made in an undocumented way. Only recently (2021), a systematic, reproducible and score-based approach for route selection for wayfinding experiments was published. However, it is still unclear how robust study results are across all potential routes in a particular experimental area. An important share of routes might lead to different conclusions than most routes. This share would distort and/or invert the study outcome. If so, the question of selecting routes that are unlikely to distort the results of our wayfinding experiments remains unanswered. In order to answer these questions, an agent-based simulation study with four different sample sizes (N = 15, 25, 50, 3000 agents) comparing Turn-by-Turn and Free Choice Navigation approaches (between-subject design) regarding their arrival rates on more than 11000 routes in the city center of Vienna, Austria, was run. The results of our study indicate that with decreasing sample size, there is an increase in the share of routes which lead to contradictory results regarding the arrival rate, i.e., the results become less robust. Therefore, based on simulation results, we present an approach for selecting suitable routes even for small-scale in-situ studies.
Cite as
Bartosz Mazurkiewicz, Markus Kattenbeck, and Ioannis Giannopoulos. Rethinking Route Choices! On the Importance of Route Selection in Wayfinding Experiments. In 15th International Conference on Spatial Information Theory (COSIT 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 240, pp. 6:1-6:13, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)
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@InProceedings{mazurkiewicz_et_al:LIPIcs.COSIT.2022.6,
author = {Mazurkiewicz, Bartosz and Kattenbeck, Markus and Giannopoulos, Ioannis},
title = {{Rethinking Route Choices! On the Importance of Route Selection in Wayfinding Experiments}},
booktitle = {15th International Conference on Spatial Information Theory (COSIT 2022)},
pages = {6:1--6:13},
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-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2022.6},
URN = {urn:nbn:de:0030-drops-168916},
doi = {10.4230/LIPIcs.COSIT.2022.6},
annote = {Keywords: Route Selection, Route Features, Human Wayfinding, Navigation, Experiments, Experimental Design}
}
Document
Empirical Evidence for Concepts of Spatial Information as Cognitive Means for Interpreting and Using Maps
Abstract
Due to the increasing prevalence and relevance of geo-spatial data in the age of data science, Geographic Information Systems are enjoying wider interdisciplinary adoption by communities outside of GIScience. However, properly interpreting and analysing geo-spatial information is not a trivial task due to knowledge barriers. There is a need for a trans-disciplinary framework for sharing specialized geographical knowledge and expertise to overcome these barriers. The core concepts of spatial information were proposed as such a conceptual framework. These concepts, such as object and field, were proposed as cognitive lenses that can simplify understanding of and guide the processing of spatial information. However, there is a distinct lack of empirical evidence for the existence of such concepts in the human mind or whether such concepts can be indeed useful. In this study, we have explored for such empirical evidence using behavioral experiments with human participants. The experiment adopted a contrast model to investigate whether the participants can semantically distinguish between the object and field core concepts visualized as maps. The statistically significant positive results offer evidence supporting the existence of the two concepts or cognitive concepts closely resembling them. This gives credibility to the core concepts of spatial information as tools for sharing, teaching, or even automating the process of geographical information processing.
Cite as
Enkhbold Nyamsuren, Eric J. Top, Haiqi Xu, Niels Steenbergen, and Simon Scheider. Empirical Evidence for Concepts of Spatial Information as Cognitive Means for Interpreting and Using Maps. In 15th International Conference on Spatial Information Theory (COSIT 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 240, pp. 7:1-7:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)
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@InProceedings{nyamsuren_et_al:LIPIcs.COSIT.2022.7,
author = {Nyamsuren, Enkhbold and Top, Eric J. and Xu, Haiqi and Steenbergen, Niels and Scheider, Simon},
title = {{Empirical Evidence for Concepts of Spatial Information as Cognitive Means for Interpreting and Using Maps}},
booktitle = {15th International Conference on Spatial Information Theory (COSIT 2022)},
pages = {7:1--7:14},
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-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2022.7},
URN = {urn:nbn:de:0030-drops-168926},
doi = {10.4230/LIPIcs.COSIT.2022.7},
annote = {Keywords: core concepts, cognition, map interpretation, spatial analysis}
}
Document
Generalized, Inaccurate, Incomplete: How to Comprehensively Analyze Sketch Maps Beyond Their Metric Correctness
Abstract
Sketch mapping is a method to investigate a person’s spatial perception and knowledge about the surrounding environment. While cartographic maps can be easily evaluated with respect to the represented features, map scale, and spatial accuracy, there still does not exist a comprehensive method to evaluate sketch maps. This paper aims to overcome this gap and proposes a sketch map analysis method that allows for analyzing the completeness, generalization and (qualitative) spatial accuracy of the sketched information in a three-step process. After describing the method, we illustrate how our computer-supported method performs in a use case with three sketch maps. Our approach may assist researchers in geography, psychology, and education to evaluate spatial knowledge in a systematic way independent of specific research questions and experimental scenarios.
Cite as
Angela Schwering, Jakub Krukar, Charu Manivannan, Malumbo Chipofya, and Sahib Jan. Generalized, Inaccurate, Incomplete: How to Comprehensively Analyze Sketch Maps Beyond Their Metric Correctness. In 15th International Conference on Spatial Information Theory (COSIT 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 240, pp. 8:1-8:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)
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@InProceedings{schwering_et_al:LIPIcs.COSIT.2022.8,
author = {Schwering, Angela and Krukar, Jakub and Manivannan, Charu and Chipofya, Malumbo and Jan, Sahib},
title = {{Generalized, Inaccurate, Incomplete: How to Comprehensively Analyze Sketch Maps Beyond Their Metric Correctness}},
booktitle = {15th International Conference on Spatial Information Theory (COSIT 2022)},
pages = {8:1--8:15},
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-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2022.8},
URN = {urn:nbn:de:0030-drops-168936},
doi = {10.4230/LIPIcs.COSIT.2022.8},
annote = {Keywords: sketch map analysis, spatial knowledge evaluation, cognitive map}
}
Document
Perceptions of Qualitative Spatial Arrangements of Three Objects
Abstract
Cognitive grounding of formal models of qualitative spatial relations is important to bridge between spatial data and human perceptions of spatial arrangements. Here, we report on an experimental verification of the cognitive alignment of the recently proposed Ray Intersection Model (RIM) capturing qualitative relationships between three spatial objects, and human perceptions of spatial arrangements through a grouping task. Further, we explore arrangements with an object positioned "between" two other objects. We show that RIM has sufficient expressive power and aligns well with human perceptions of ternary spatial relationships.
Cite as
Ningran Xu, Ivan Majic, and Martin Tomko. Perceptions of Qualitative Spatial Arrangements of Three Objects. In 15th International Conference on Spatial Information Theory (COSIT 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 240, pp. 9:1-9:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)
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@InProceedings{xu_et_al:LIPIcs.COSIT.2022.9,
author = {Xu, Ningran and Majic, Ivan and Tomko, Martin},
title = {{Perceptions of Qualitative Spatial Arrangements of Three Objects}},
booktitle = {15th International Conference on Spatial Information Theory (COSIT 2022)},
pages = {9:1--9:14},
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-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2022.9},
URN = {urn:nbn:de:0030-drops-168948},
doi = {10.4230/LIPIcs.COSIT.2022.9},
annote = {Keywords: Spatial Perception, Qualitative Spatial Relationships, Betweenness, Evaluation, Ternary Relationships}
}
Document
Vision Paper
Are Psychological Variables Relevant to Evaluating Geoinformatics Applications? The Case of Landmarks (Vision Paper)
Abstract
Interdisciplinary integration of spatial cognition and spatial computation promises to create better spatial technology based on findings from cognitive psychology experiments. Using the example of psychological studies and computational modelling of landmarks, this paper argues that core evaluation criteria of both disciplines are not well aligned with the goal of evaluating landmark-enhanced navigation support systems that support users in everyday wayfinding.
The paper raises two points. First, it reviews evaluation criteria used in the interdisciplinary field of landmark research. It is argued that when to consider the role of landmark-enhanced navigation support systems in everyday life of their users, different evaluation criteria are needed. If strictly-psychological or strictly-computational criteria continue being prioritised by the community, we risk undervaluing significant technological contributions. Second, it proposes one such potential criterion: testing whether the cognitive task has changed due to equipping users with the new technology.
This goal might be achieved at the expense of criteria typical to strictly-psychological studies (such as spatial memory of landmarks along the travelled route) or strictly-computational studies (such as efficiency and accuracy of a landmark-selection algorithm). Thus, promoting and implementing alternative evaluation criteria comes with methodological risks. In order to mitigate them we propose a process based on pre-registration of "postdiction" studies and hope to stimulate a further debate on a consensus-based approach in the community.
Cite as
Jakub Krukar and Angela Schwering. Are Psychological Variables Relevant to Evaluating Geoinformatics Applications? The Case of Landmarks (Vision Paper). In 15th International Conference on Spatial Information Theory (COSIT 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 240, pp. 10:1-10:13, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)
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@InProceedings{krukar_et_al:LIPIcs.COSIT.2022.10,
author = {Krukar, Jakub and Schwering, Angela},
title = {{Are Psychological Variables Relevant to Evaluating Geoinformatics Applications? The Case of Landmarks (Vision Paper)}},
booktitle = {15th International Conference on Spatial Information Theory (COSIT 2022)},
pages = {10:1--10:13},
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-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2022.10},
URN = {urn:nbn:de:0030-drops-168956},
doi = {10.4230/LIPIcs.COSIT.2022.10},
annote = {Keywords: wayfinding, navigation support systems, cognitive geoengineering, landmarks}
}
Document
Vision Paper
New Human Dynamics in the Emerging Metaverse: Towards a Quantum Phygital Approach by Integrating Space and Place (Vision Paper)
Abstract
With the convergence of mirror worlds, virtual worlds, lifelogging, and augmented/virtual reality, the emerging metaverse is rapidly becoming a major platform where humans work, shop, entertain themselves, and socialize with others. Human dynamics, which refers to all forms of human activities and interactions, will undergo profound transformations in the coming years with the advent of the metaverse. The new human dynamics will be neither physical nor digital but a seamless integration of both - phygital. The goal of this vision paper is to develop a phygital approach to support human dynamics research in the spirit of GIScience as a convergence. Built on our earlier work in human dynamics research, we argue that the current discussions on human dynamics are conceptually constrained by their physical and digital silos. The new phygital approach we are envisioning aims to transcend the simplistic dichotomy by integrating both space and place perspectives. This paper also draws on basic concepts in quantum physics and earlier discussions on their potential applications in geography and GIScience to espouse a quantum turn in exploring the human dynamics in the emerging metaverse. It explores how concepts, methods, and understandings from quantum physics and emerging quantum computing and communication technologies can be translated into addressing fundamental geographical analyses for this phygital world.
Cite as
Daniel Sui and Shih-Lung Shaw. New Human Dynamics in the Emerging Metaverse: Towards a Quantum Phygital Approach by Integrating Space and Place (Vision Paper). In 15th International Conference on Spatial Information Theory (COSIT 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 240, pp. 11:1-11:13, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)
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@InProceedings{sui_et_al:LIPIcs.COSIT.2022.11,
author = {Sui, Daniel and Shaw, Shih-Lung},
title = {{New Human Dynamics in the Emerging Metaverse: Towards a Quantum Phygital Approach by Integrating Space and Place}},
booktitle = {15th International Conference on Spatial Information Theory (COSIT 2022)},
pages = {11:1--11:13},
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-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2022.11},
URN = {urn:nbn:de:0030-drops-168961},
doi = {10.4230/LIPIcs.COSIT.2022.11},
annote = {Keywords: metaverse, human dynamics, phygital, space-place, quantum, GIScience theory}
}
Document
Short Paper
Large-Scale Spatial Prediction by Scalable Geographically Weighted Regression: Comparative Study (Short Paper)
Abstract
Although the scalable geographically weighted regression (GWR) has been developed as a fast regression approach modeling non-stationarity, its potential on spatial prediction is largely unexplored. Given that, this study applies the scalable GWR technique for large-scale spatial prediction, and compares its prediction accuracy with modern geostatistical methods including the nearest-neighbor Gaussian process, and machine learning algorithms including light gradient boosting machine. The result suggests accuracy of our scalable GWR-based prediction.
Cite as
Daisuke Murakami, Narumasa Tsutsumida, Takahiro Yoshida, and Tomoki Nakaya. Large-Scale Spatial Prediction by Scalable Geographically Weighted Regression: Comparative Study (Short Paper). In 15th International Conference on Spatial Information Theory (COSIT 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 240, pp. 12:1-12:5, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)
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@InProceedings{murakami_et_al:LIPIcs.COSIT.2022.12,
author = {Murakami, Daisuke and Tsutsumida, Narumasa and Yoshida, Takahiro and Nakaya, Tomoki},
title = {{Large-Scale Spatial Prediction by Scalable Geographically Weighted Regression: Comparative Study}},
booktitle = {15th International Conference on Spatial Information Theory (COSIT 2022)},
pages = {12:1--12:5},
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-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2022.12},
URN = {urn:nbn:de:0030-drops-168971},
doi = {10.4230/LIPIcs.COSIT.2022.12},
annote = {Keywords: Spatial prediction, Scalable geographically weighted regression, Large data, Housing price}
}
Document
Short Paper
Geographically Varying Coefficient Regression: GWR-Exit and GAM-On? (Short Paper)
Abstract
This paper describes initial work exploring two spatially varying coefficient models: multi-scale GWR and GAM Gaussian Process spline parameterised by observation location. Both approaches accommodate process spatial heterogeneity and both generate outputs that can be mapped indicating the nature of the process heterogeneity. However the nature of the process heterogeneity they each describe are very different. This suggests that the underlying semantics of such models need to be considered in order to refine the specificity of the questions that are asked of data: simply seeking to understand process spatial heterogeneity may be too semantically coarse.
Cite as
Alexis Comber, Paul Harris, Daisuke Murakami, Narumasa Tsutsumida, and Chris Brunsdon. Geographically Varying Coefficient Regression: GWR-Exit and GAM-On? (Short Paper). In 15th International Conference on Spatial Information Theory (COSIT 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 240, pp. 13:1-13:10, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)
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@InProceedings{comber_et_al:LIPIcs.COSIT.2022.13,
author = {Comber, Alexis and Harris, Paul and Murakami, Daisuke and Tsutsumida, Narumasa and Brunsdon, Chris},
title = {{Geographically Varying Coefficient Regression: GWR-Exit and GAM-On?}},
booktitle = {15th International Conference on Spatial Information Theory (COSIT 2022)},
pages = {13:1--13:10},
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-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2022.13},
URN = {urn:nbn:de:0030-drops-168986},
doi = {10.4230/LIPIcs.COSIT.2022.13},
annote = {Keywords: Geographically weighted regression, Spatial Analysis, Process Spatial Heterogeneity, Model Semantics}
}
Document
Short Paper
3D Sketch Maps: Concept, Potential Benefits, and Challenges (Short Paper)
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-dev.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
Short Paper
The Effect of Abstract vs. Realistic 3D Visualization on Landmark and Route Knowledge Acquisition (Short Paper)
Abstract
Even though humans perform it daily, navigation is a cognitively challenging process. Landmarks have been shown to facilitate navigation by scaffolding humans’ mental representation of space. However, how landmarks can be effectively communicated to pedestrians to support spatial learning of the traversed environment remains an open question. Therefore, we assessed how the visualization of landmarks on a mobile map (i.e., abstract 3D vs. realistic 3D symbols) influences participants’ spatial learning, visual attention allocation, and cognitive load during an outdoor map-assisted navigation task. We report initial results on how exposing pedestrians to different landmark visualization styles on mobile maps while navigating along a given route in an urban environment can have differing effects on how they remember landmarks and routes. Specifically, we find that navigators better remember landmarks visualized as 3D realistic-looking symbols compared to 3D abstract landmark symbols on the mobile map. The pattern of results shows that displaying realistic 3D landmark symbols at intersections potentially helps participants to remember route directions better than with landmarks depicted as abstract 3D symbols. The presented methodological approach contributes ecologically valid insights to further understand how the design of landmarks on mobile maps could support wayfinders' spatial learning during map-assisted navigation.
Cite as
Armand Kapaj, Enru Lin, and Sara Lanini-Maggi. The Effect of Abstract vs. Realistic 3D Visualization on Landmark and Route Knowledge Acquisition (Short Paper). In 15th International Conference on Spatial Information Theory (COSIT 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 240, pp. 15:1-15:8, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)
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@InProceedings{kapaj_et_al:LIPIcs.COSIT.2022.15,
author = {Kapaj, Armand and Lin, Enru and Lanini-Maggi, Sara},
title = {{The Effect of Abstract vs. Realistic 3D Visualization on Landmark and Route Knowledge Acquisition}},
booktitle = {15th International Conference on Spatial Information Theory (COSIT 2022)},
pages = {15:1--15:8},
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-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2022.15},
URN = {urn:nbn:de:0030-drops-169000},
doi = {10.4230/LIPIcs.COSIT.2022.15},
annote = {Keywords: Abstraction, realism, 3D, landmark visualization, mobile map design, cartography, real-world navigation, spatial learning}
}
Document
Short Paper
Smart Crowd Management: The Data, the Users and the Solution (Short Paper)
Abstract
This research project is situated in the domain of smart crowd management, a domain that is gaining importance because of the challenges that arise from urbanization, but also the opportunities that come with smart cities. While our cities become more crowded every day, they also become smarter, for example by employing pedestrian tracking sensors. However, the datasets that are generated by these sensors do not allow smart crowd management yet, because they are sparse and not linked to the perception of the crowd. This research will tackle these issues in three steps. First, pedestrian counts will be estimated on streets that have no tracking data by use of deep learning and space syntax data. Next, the perception of crowdedness within the crowd will be linked to the objective pedestrian counts by conducting two user studies, and finally, the resulting subjective pedestrian counts will be used as weights for a routing algorithm. The last step has already been developed as a proof of concept. The routing algorithm, that uses partly simulated data and partly real-time tracking data, has been embedded in a webtool to show stakeholders the potential and goal of this innovative project.
Cite as
Laure De Cock, Steven Verstockt, Christophe Vandeviver, and Nico Van de Weghe. Smart Crowd Management: The Data, the Users and the Solution (Short Paper). In 15th International Conference on Spatial Information Theory (COSIT 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 240, pp. 16:1-16:7, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)
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@InProceedings{decock_et_al:LIPIcs.COSIT.2022.16,
author = {De Cock, Laure and Verstockt, Steven and Vandeviver, Christophe and Van de Weghe, Nico},
title = {{Smart Crowd Management: The Data, the Users and the Solution}},
booktitle = {15th International Conference on Spatial Information Theory (COSIT 2022)},
pages = {16:1--16:7},
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.2022.16},
URN = {urn:nbn:de:0030-drops-169013},
doi = {10.4230/LIPIcs.COSIT.2022.16},
annote = {Keywords: crowd tracking, crowd modeling, space syntax, deep learning, perception, routing}
}
Document
Short Paper
A Weather-Aware Framework for Population Mobility Modelling (Short Paper)
Abstract
The widespread availability of GPS-enabled mobile devices has contributed towards an unprecedented volume of data on human movement. Human mobility data are the key input for developing accurate mobility models that can support decision-making in, for example, urban planning, transportation planning and disease spread. However, the increasing geoprivacy concerns have been limiting the use of and access to such data. For this reason, the WHO-WHERE-WHEN (3W) model, a privacy-protective model for generating synthetic mobility data, has been developed. However, human mobility is affected by multiple factors that must be accounted for to produce synthetic mobility trajectories that accurately simulate the fluctuations of population in a study area. The 3W model already considers four main factors affecting human mobility: size and shape of activity spaces, circadian rhythm, and home and work locations. Yet, meteorological factors are known to affect human mobility patterns but, to our knowledge, there is not a model that accounts for weather conditions. In this paper, we propose a theoretical framework to extend the 3W model to a 4W model: WHO-WHERE-WHEN-WEATHER. We hypothesise that accounting for weather conditions in human mobility predictions will increase the overall accuracy of predicted mobility patterns.
Cite as
Vanessa Brum-Bastos, Kamil Smolak, Witold Rohm, and Katarzyna Sila-Nowicka. A Weather-Aware Framework for Population Mobility Modelling (Short Paper). In 15th International Conference on Spatial Information Theory (COSIT 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 240, pp. 17:1-17:9, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)
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@InProceedings{brumbastos_et_al:LIPIcs.COSIT.2022.17,
author = {Brum-Bastos, Vanessa and Smolak, Kamil and Rohm, Witold and Sila-Nowicka, Katarzyna},
title = {{A Weather-Aware Framework for Population Mobility Modelling}},
booktitle = {15th International Conference on Spatial Information Theory (COSIT 2022)},
pages = {17:1--17:9},
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-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2022.17},
URN = {urn:nbn:de:0030-drops-169020},
doi = {10.4230/LIPIcs.COSIT.2022.17},
annote = {Keywords: movement analytics, human movement, mobility models, context-awareness}
}
Document
Short Paper
Qualitative Spatial Reasoning over Questions (Short Paper)
Abstract
Although geospatial question answering systems have received increasing attention in recent years, existing prototype systems struggle to properly answer qualitative spatial questions. In this work, we propose a unique framework for answering qualitative spatial questions, which comprises three main components: a geoparser that takes the input questions and extracts place semantic information from text, a reasoning system which is embedded with a crisp reasoner, and finally, answer extraction, which refines the solution space and generates final answers. We present an experimental design to evaluate our framework for point-based cardinal direction calculus (CDC) relations by developing an automated approach for generating three types of synthetic qualitative spatial questions. The initial evaluations of generated answers in our system are promising because a high proportion of answers were labelled correct.
Cite as
Mohammad Kazemi Beydokhti, Matt Duckham, Yaguang Tao, Maria Vasardani, and Amy Griffin. Qualitative Spatial Reasoning over Questions (Short Paper). In 15th International Conference on Spatial Information Theory (COSIT 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 240, pp. 18:1-18:7, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)
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@InProceedings{beydokhti_et_al:LIPIcs.COSIT.2022.18,
author = {Beydokhti, Mohammad Kazemi and Duckham, Matt and Tao, Yaguang and Vasardani, Maria and Griffin, Amy},
title = {{Qualitative Spatial Reasoning over Questions}},
booktitle = {15th International Conference on Spatial Information Theory (COSIT 2022)},
pages = {18:1--18:7},
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-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2022.18},
URN = {urn:nbn:de:0030-drops-169039},
doi = {10.4230/LIPIcs.COSIT.2022.18},
annote = {Keywords: Qualitative spatial reasoning, geospatial question answering, Qualitative spatial questions}
}
Document
Short Paper
Transcepts: Connecting Entity Representations Across Conceptual Views on Spatial Information (Short Paper)
Abstract
Analysts interpret geographic and other spatial data to check the validity of methods in reaching an analytical goal. However, the meaning of data is elusive. The same data may constitute one concept in one view and another concept in another. For example, the same set of air pollution points may be regarded as field values if they are considered pollution measurements and objects if they are considered locations of measurement devices. In this work we adopt a framework of conceptual spaces and viewpoints and show how entity representations in one semantic interpretation may be related to entity representations in others in terms of what we call transcepts. A transcept captures which things represent the same entity. We define and use transcepts in the framework to explain how different views of geographic data may relate to one another.
Cite as
Eric J. Top and Simon Scheider. Transcepts: Connecting Entity Representations Across Conceptual Views on Spatial Information (Short Paper). In 15th International Conference on Spatial Information Theory (COSIT 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 240, pp. 19:1-19:7, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)
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@InProceedings{top_et_al:LIPIcs.COSIT.2022.19,
author = {Top, Eric J. and Scheider, Simon},
title = {{Transcepts: Connecting Entity Representations Across Conceptual Views on Spatial Information}},
booktitle = {15th International Conference on Spatial Information Theory (COSIT 2022)},
pages = {19:1--19:7},
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-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2022.19},
URN = {urn:nbn:de:0030-drops-169048},
doi = {10.4230/LIPIcs.COSIT.2022.19},
annote = {Keywords: Transcept, Spatial Information, Knowledge Representation, Conceptual Space, View, Point Of View, Viewpoint, Object, Event, Network, Field, Relation}
}
Document
Short Paper
A Computational Method for the Classification of Mental Representations of Objects in 3D Space (Short Paper)
Abstract
The structure mapping task is a simple method to test people’s mental representations of spatial relationships, and has recently been particularly useful in the study of volumetric spatial cognition such as the spatial memory for locations in multilevel buildings. However, there does not exist a standardised method to analyse such data and structure mapping tasks are typically analysed by human raters, based on criteria defined by the researchers. In this article, we introduce a computational method to assess spatial relationships of objects in the vertical and horizontal domains, which are realized through the structure mapping task. Here, we reanalyse participants' digitised structure maps from an earlier study (N=41) using the proposed computational methodology. Our results show that the new method successfully distinguishes between different types of structure map representations, and is sensitive to learning order effects. This method can be useful to advance the study of volumetric spatial cognition.
Cite as
Samuel S. Sohn, Panagiotis Mavros, Mubbasir Kapadia, and Christoph Hölscher. A Computational Method for the Classification of Mental Representations of Objects in 3D Space (Short Paper). In 15th International Conference on Spatial Information Theory (COSIT 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 240, pp. 20:1-20:8, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)
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@InProceedings{sohn_et_al:LIPIcs.COSIT.2022.20,
author = {Sohn, Samuel S. and Mavros, Panagiotis and Kapadia, Mubbasir and H\"{o}lscher, Christoph},
title = {{A Computational Method for the Classification of Mental Representations of Objects in 3D Space}},
booktitle = {15th International Conference on Spatial Information Theory (COSIT 2022)},
pages = {20:1--20:8},
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-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2022.20},
URN = {urn:nbn:de:0030-drops-169058},
doi = {10.4230/LIPIcs.COSIT.2022.20},
annote = {Keywords: mental representations of space, spatial cognition, structure mapping task, 3D space, volumetric space}
}
Document
Short Paper
A Comparison of Geographically Weighted Principal Components Analysis Methodologies (Short Paper)
Abstract
Principal components analysis (PCA) is a useful analytical tool to represent key characteristics of multivariate data, but does not account for spatial effects when applied in geographical situations. A geographically weighted PCA (GWPCA) caters to this issue, specifically in terms of capturing spatial heterogeneity. However, in certain situations, a GWPCA provides outputs that vary discontinuously spatially, which are difficult to interpret and are not associated with the output from a conventional (global) PCA any more. This study underlines a GW non-negative PCA, a geographically weighted version of non-negative PCA, to overcome this issue by constraining loading values non-negatively. Case study results with a complex multivariate spatial dataset demonstrate such benefits, where GW non-negative PCA allows improved interpretations than that found with conventional GWPCA.
Cite as
Narumasa Tsutsumida, Daisuke Murakami, Takahiro Yoshida, Tomoki Nakaya, Binbin Lu, Paul Harris, and Alexis Comber. A Comparison of Geographically Weighted Principal Components Analysis Methodologies (Short Paper). In 15th International Conference on Spatial Information Theory (COSIT 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 240, pp. 21:1-21:6, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)
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@InProceedings{tsutsumida_et_al:LIPIcs.COSIT.2022.21,
author = {Tsutsumida, Narumasa and Murakami, Daisuke and Yoshida, Takahiro and Nakaya, Tomoki and Lu, Binbin and Harris, Paul and Comber, Alexis},
title = {{A Comparison of Geographically Weighted Principal Components Analysis Methodologies}},
booktitle = {15th International Conference on Spatial Information Theory (COSIT 2022)},
pages = {21:1--21:6},
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-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2022.21},
URN = {urn:nbn:de:0030-drops-169062},
doi = {10.4230/LIPIcs.COSIT.2022.21},
annote = {Keywords: Spatial heterogeneity, Geographically weighted, Sparsity, PCA}
}
Document
Short Paper
Abnormal Situation Simulation and Dynamic Causality Discovery in Urban Traffic Networks (Short Paper)
Abstract
Various participants in urban traffic systems intertwine a highly complicated coupling network. An interpretable analysis of underlying correlations is one of the keys to understanding traffic anomalies. Unfortunately, abnormal situation analysis in real scenarios faces severe limitations in negative sample deficiency, data integrity, and verifiability. In view of this, we developed a simulation tool - the Traffic Anomaly Situation Simulator (TASS). Through configurable scripts, TASS simulates real traffic networks by road editing, data collection, and fault injection. Given the generated cases, we designed a dynamic causal discovery algorithm, Dycause-Traffic, to demonstrate the features of causality in traffic anomalies.
Cite as
Yadi Wang, Yicheng Pan, Meng Ma, and Ping Wang. Abnormal Situation Simulation and Dynamic Causality Discovery in Urban Traffic Networks (Short Paper). In 15th International Conference on Spatial Information Theory (COSIT 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 240, pp. 22:1-22:7, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)
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@InProceedings{wang_et_al:LIPIcs.COSIT.2022.22,
author = {Wang, Yadi and Pan, Yicheng and Ma, Meng and Wang, Ping},
title = {{Abnormal Situation Simulation and Dynamic Causality Discovery in Urban Traffic Networks}},
booktitle = {15th International Conference on Spatial Information Theory (COSIT 2022)},
pages = {22:1--22:7},
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-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2022.22},
URN = {urn:nbn:de:0030-drops-169077},
doi = {10.4230/LIPIcs.COSIT.2022.22},
annote = {Keywords: SUMO simulation, dynamic causality discovery, congestion propagation}
}
Document
Short Paper
Spatial and Spatiotemporal Matching Framework for Causal Inference (Short Paper)
Abstract
Matching is a procedure aimed at reducing the impact of observational data bias in causal analysis. Designing matching methods for spatial data reflecting static spatial or dynamic spatio-temporal processes is complex because of the effects of spatial dependence and spatial heterogeneity. Both may be compounded with temporal lag in the dependency effects on the study units. Current matching techniques based on similarity indexes and pairing strategies need to be extended with optimal spatial matching procedures. Here, we propose a decision framework to support analysts through the choice of existing matching methods and anticipate the development of specialized matching methods for spatial data. This framework thus enables to identify knowledge gaps.
Cite as
Kamal Akbari and Martin Tomko. Spatial and Spatiotemporal Matching Framework for Causal Inference (Short Paper). In 15th International Conference on Spatial Information Theory (COSIT 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 240, pp. 23:1-23:7, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)
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@InProceedings{akbari_et_al:LIPIcs.COSIT.2022.23,
author = {Akbari, Kamal and Tomko, Martin},
title = {{Spatial and Spatiotemporal Matching Framework for Causal Inference}},
booktitle = {15th International Conference on Spatial Information Theory (COSIT 2022)},
pages = {23:1--23:7},
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-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2022.23},
URN = {urn:nbn:de:0030-drops-169087},
doi = {10.4230/LIPIcs.COSIT.2022.23},
annote = {Keywords: Framework, Spatial, Spatiotemporal, Matching, Causal Inference}
}
Document
Short Paper
An Entropy-Based Model for Indoor Self-Localization Through Dialogue (Short Paper)
Abstract
People can be localized at a particular location in an indoor environment using verbal descriptions referring to distinct visible objects (e.g., landmarks). When a user provides an incomplete initial location description their location may remain ambiguous. Here, we consider a dialogue initiated to update the initial description, which continues until the updated description can be related to a location in the environment. In each interaction, the wayfinder is incrementally asked about the visibility of a particular object to update the initial description. This paper presents an entropy-based model to minimize the number of interactions. We show how this entropy-based model leads to a significant reduction of interactions (i.e., reduction of conversation length, measured by the number of additional referents) compared to baseline models. Moreover, the effect of the initial description, i.e., the first set of visible objects with different combinations, is investigated.
Cite as
Kimia Amoozandeh, Ehsan Hamzei, and Martin Tomko. An Entropy-Based Model for Indoor Self-Localization Through Dialogue (Short Paper). In 15th International Conference on Spatial Information Theory (COSIT 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 240, pp. 24:1-24:7, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)
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@InProceedings{amoozandeh_et_al:LIPIcs.COSIT.2022.24,
author = {Amoozandeh, Kimia and Hamzei, Ehsan and Tomko, Martin},
title = {{An Entropy-Based Model for Indoor Self-Localization Through Dialogue}},
booktitle = {15th International Conference on Spatial Information Theory (COSIT 2022)},
pages = {24:1--24:7},
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-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2022.24},
URN = {urn:nbn:de:0030-drops-169095},
doi = {10.4230/LIPIcs.COSIT.2022.24},
annote = {Keywords: Indoor self-localization, Dialogue, Entropy}
}
Document
Short Paper
Collaborative Wayfinding Under Distributed Spatial Knowledge (Short Paper)
Abstract
In many everyday situations, two or more people navigate collaboratively but their spatial knowledge does not necessarily overlap. However, most research to date, has investigated social wayfinding under either 1-sided or fully shared spatial information. Here, we present the pilot experiment of a novel, computerised, non-verbal experimental paradigm to study collaborative wayfinding under the face of spatial information uncertainty. Participants (N=32) learned two different neighbourhoods individually, and then navigated together as dyads (D=16), from one neighbourhood to the other. Our pilot results reveal that overall participants share navigational control, but are in control more when the task leads them to a familiar destination. We discuss the effects of spatial ability and motivation to lead, as well as the outlook of the paradigm.
Cite as
Panagiotis Mavros, Saskia Kuliga, Ed Manley, Hilal Rohaidi Fitri, Michael Joos, and Christoph Hölscher. Collaborative Wayfinding Under Distributed Spatial Knowledge (Short Paper). In 15th International Conference on Spatial Information Theory (COSIT 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 240, pp. 25:1-25:10, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)
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@InProceedings{mavros_et_al:LIPIcs.COSIT.2022.25,
author = {Mavros, Panagiotis and Kuliga, Saskia and Manley, Ed and Fitri, Hilal Rohaidi and Joos, Michael and H\"{o}lscher, Christoph},
title = {{Collaborative Wayfinding Under Distributed Spatial Knowledge}},
booktitle = {15th International Conference on Spatial Information Theory (COSIT 2022)},
pages = {25:1--25:10},
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-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2022.25},
URN = {urn:nbn:de:0030-drops-169105},
doi = {10.4230/LIPIcs.COSIT.2022.25},
annote = {Keywords: navigation, wayfinding, collaboration, dyad, online}
}
Document
Short Paper
Abnormal Trajectory-Gap Detection: A Summary (Short Paper)
Abstract
Given trajectories with gaps (i.e., missing data), we investigate algorithms to identify abnormal gaps for testing possible hypotheses of anomalous regions. Here, an abnormal gap within a trajectory is defined as an area where a given moving object did not report its location, but other moving objects did periodically. The problem is important due to its societal applications, such as improving maritime safety and regulatory enforcement for global security concerns such as illegal fishing, illegal oil transfer, and trans-shipments. The problem is challenging due to the difficulty of interpreting missing data within a trajectory gap, and the high computational cost of detecting gaps in such a large volume of location data proves computationally very expensive. The current literature assumes linear interpolation within gaps, which may not be able to detect abnormal gaps since objects within a given region may have traveled away from their shortest path. To overcome this limitation, we propose an abnormal gap detection (AGD) algorithm that leverages the concepts of a space-time prism model where we assume space-time interpolation. We then propose a refined memoized abnormal gap detection (Memo-AGD) algorithm that reduces comparison operations. We validated both algorithms using synthetic and real-world data. The results show that abnormal gaps detected by our algorithms give better estimates of abnormality than linear interpolation and can be used for further investigation from the human analysts.
Cite as
Arun Sharma, Jayant Gupta, and Shashi Shekhar. Abnormal Trajectory-Gap Detection: A Summary (Short Paper). In 15th International Conference on Spatial Information Theory (COSIT 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 240, pp. 26:1-26:10, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)
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@InProceedings{sharma_et_al:LIPIcs.COSIT.2022.26,
author = {Sharma, Arun and Gupta, Jayant and Shekhar, Shashi},
title = {{Abnormal Trajectory-Gap Detection: A Summary}},
booktitle = {15th International Conference on Spatial Information Theory (COSIT 2022)},
pages = {26:1--26:10},
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-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2022.26},
URN = {urn:nbn:de:0030-drops-169115},
doi = {10.4230/LIPIcs.COSIT.2022.26},
annote = {Keywords: Spatial Data Mining, Trajectory Mining, Time Geography}
}
Document
Short Paper
Improving Pedestrians Traffic Priority via Grouping and Virtual Lanes in Shared Spaces (Short Paper)
Abstract
The shared space design is applied in urban streets to support barrier-free movement and integrate traffic participants (such as pedestrians, cyclists and vehicles) into a common road space. Regardless of the low-speed environment, sharing space with motor vehicles can make vulnerable road users feel uneasy. Yet, walking in groups increases their confidence as well as influence the yielding behavior of drivers. Therefore, we propose an innovative approach to support the crossing of pedestrians via grouping and project the virtual lanes in shared spaces. This paper presents the important components of the crowd steering system, discusses the enablers and gaps in the current approach, and illustrates the proposed idea with concept diagrams.
Cite as
Yao Li, Vinu Kamalasanan, Mariana Batista, and Monika Sester. Improving Pedestrians Traffic Priority via Grouping and Virtual Lanes in Shared Spaces (Short Paper). In 15th International Conference on Spatial Information Theory (COSIT 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 240, pp. 27:1-27:8, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)
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@InProceedings{li_et_al:LIPIcs.COSIT.2022.27,
author = {Li, Yao and Kamalasanan, Vinu and Batista, Mariana and Sester, Monika},
title = {{Improving Pedestrians Traffic Priority via Grouping and Virtual Lanes in Shared Spaces}},
booktitle = {15th International Conference on Spatial Information Theory (COSIT 2022)},
pages = {27:1--27:8},
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-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2022.27},
URN = {urn:nbn:de:0030-drops-169125},
doi = {10.4230/LIPIcs.COSIT.2022.27},
annote = {Keywords: shared space, urban traffic system, augmented reality, pedestrian grouping}
}
Document
Short Paper
Eye Blink-Related Brain Potentials During Landmark-Based Navigation in Virtual Reality (Short Paper)
Abstract
Landmarks support navigation and spatial learning of environments by serving as cognitive anchors. However, little research has been done to investigate how the design of landmarks on mobile maps affects cognitive processing. To address this gap, the present study utilized a within-subjects design to experimentally examine how three different landmark densities (3 vs. 5 vs. 7 landmarks) on mobile maps influence users' spatial learning and cognitive load during navigation. Cognitive load was measured using electroencephalography (EEG). We applied an event-related analysis approach by utilizing eye blinks as naturalistic event markers to segment the EEG data. Results demonstrate that showing five landmarks along a given route to follow on a mobile map, compared to three and seven landmarks, improved spatial learning performance without taxing more cognitive resources. Our study shows that users' cognitive load and spatial learning outcomes should be considered when designing landmark-based navigation assistance systems.
Cite as
Bingjie Cheng, Enru Lin, Klaus Gramann, and Anna Wunderlich. Eye Blink-Related Brain Potentials During Landmark-Based Navigation in Virtual Reality (Short Paper). In 15th International Conference on Spatial Information Theory (COSIT 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 240, pp. 28:1-28:8, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)
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@InProceedings{cheng_et_al:LIPIcs.COSIT.2022.28,
author = {Cheng, Bingjie and Lin, Enru and Gramann, Klaus and Wunderlich, Anna},
title = {{Eye Blink-Related Brain Potentials During Landmark-Based Navigation in Virtual Reality}},
booktitle = {15th International Conference on Spatial Information Theory (COSIT 2022)},
pages = {28:1--28:8},
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-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2022.28},
URN = {urn:nbn:de:0030-drops-169130},
doi = {10.4230/LIPIcs.COSIT.2022.28},
annote = {Keywords: spatial navigation, landmark, blink-related potentials, spatial learning, cognitive load, mobile map}
}
Document
Short Paper
Representing Computational Relations in Knowledge Graphs Using Functional Languages (Short Paper)
Abstract
Knowledge representation is the cornerstone of constructing a GKG. The existing representations of spatial and computational relations in GKGs, however, are inadequate. In this paper, we use DE-9IM to represent spatial topological relations. To represent computational relations, we use typed lambda calculus via its implementation in the functional language Haskell, in which functions are first-class primitives. We exemplify our ideas through some basic examples in Haskell.
Cite as
Yanmin Qi, Heshan Du, Amin Farjudian, and Yunqiang Zhu. Representing Computational Relations in Knowledge Graphs Using Functional Languages (Short Paper). In 15th International Conference on Spatial Information Theory (COSIT 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 240, pp. 29:1-29:7, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)
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@InProceedings{qi_et_al:LIPIcs.COSIT.2022.29,
author = {Qi, Yanmin and Du, Heshan and Farjudian, Amin and Zhu, Yunqiang},
title = {{Representing Computational Relations in Knowledge Graphs Using Functional Languages}},
booktitle = {15th International Conference on Spatial Information Theory (COSIT 2022)},
pages = {29:1--29:7},
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-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2022.29},
URN = {urn:nbn:de:0030-drops-169147},
doi = {10.4230/LIPIcs.COSIT.2022.29},
annote = {Keywords: spatial relation, computational relation, functional programming, Haskell, geo-knowledge graph}
}