COSIT 2024 - Program

Opening remarks and logistics

Scalable Harmonious Simplification of Isolines
 (Steven van den Broek, Wouter Meulemans, Andreas Reimer, Bettina Speckmann)

Probing the Information Theoretical Roots of Spatial Dependence Measures
 (Zhangyu Wang, Krzysztof Janowicz, Gengchen Mai, Ivan Majic)

An ontology and geospatial knowledge graph for reasoning about cascading failures
 (Torsten Hahmann, David K. Kedrowski)

Towards a general framework for co-location
 (Keiran Suchak, Ed Manley)

Towards Statistically Significant Taxonomy Aware Co-location Pattern Detection
 (Subhankar Ghosh, Arun Sharma)

Lunch is on your own today. A few restaurant suggestions:
• Aux Anciens Canadiens is a historic restaurant serving classic Quebec cuisine.
• Le Casse-Crêpe Breton is an excellent French Crepery
• Paillard is a great 'boulangerie' for a fast meal

Semantic Perspectives on the Lake District Writing: Spatial Ontology Modeling and Relation Extraction for Deeper Insights
 (Erum Haris, Anthony Cohn, John Stell)

The Role of Gaze and the Semantics of Demonstratives in Referent Selection
 (Crystal H. Y. Chen, Lyn Tieu, Ana T. Perez-Leroux)

Formalizing a Unique Space-Time Grammatical Mapping in a North American Indigenous Language Family
 (Zahur Ashrafuzzaman)

Large Language Models: Testing their capabilities to understand and explain spatial concepts
 ( Majid Hojati, Rob Feick )

Geo-knowledge-guided GPT models improve the extraction of location descriptions from disaster-related social media messages
 (Hu, Yingjie, Gengchen Mai, Chris Cundy, Kristy Choi, Ni Lao, Wei Liu, Gaurish Lakhanpal, Ryan Zhenqi Zhou, and Kenneth Joseph)

Evaluating the Ability of Large Language Models to Reason about Cardinal Directions
 ( Anthony Cohn, Robert E Blackwell )

Description: Over the last decade, knowledge graphs have become more widespread to share and link all kinds of knowledge on the web. Many of them either focus on or at least include knowledge that is geospatial in nature. The applications are broad: they are used to publicly share information, semantically link information thematically and spatially, and to support advanced inferences and analyses. The development of these geospatial knowledge graphs also raises new research questions, such as how to leverage the spatial and temporal structure to scale these graphs, how to support more advanced semantic inferencing as well as machine learning over geospatial graphs, or how to provide spatio-temporal graph summaries, to name just a few of them.

This session will feature lead researchers involved in the design of a range of geospatial knowledge graphs that are being developed with funding from the National Science Foundational and US federal agencies, including from KnowWhereGraph (Janowicz, Stephen, Cogan Shimizu), The Urban Flooding Open Knowledge Network (UF-OKN: Hahmann), the Safe Agricultural Products and Water Graph (SAWGraph: Hahmann, Stephen), and USGS’s geoconnex (presenter to be confirmed) to present their unique perspectives on the spatial and temporal semantics and structure of these novel large geospatial knowledge graphs. Each will demo examples of geospatial queries and analyses these graphs support and what role semantics play in them. This is followed by a panel discussion exploring the state-of-the-art and the needs of current and potential users, applications and standards. Its primary aim is to identify the research challenges and priorities for the next generation of geospatial semantics and knowledge graphs.

Organizers:
Torsten Hahmann, University of Maine, USA
Krzysztof Janowicz, University of Vienna, Austria
Shirly Stephen, University of California, Santa Barbara, USA
Cogan Shimizu, Wright State University, USA

Drinks and hors d'oeuvre will be served

From map-supported route planning to map-assisted navigation: a VR-based study to assess context-aware mobile map adaptation
( Mona Bartling, Zhengfang Xu, Sara Fabrikant )

How exposure assessments are impacted by definitions of environmental contexts
(Csilla Vamos, Simon Scheider, Tian Tian, Roel Vermeulen )

Translational Research: Leveraging Spatial Behavior and Longitudinal Activity Space Data for Advancing Mobile Health (mHealth) Interventions
(Jeremy Mennis, J. Douglas Coatsworth, Michael Russell, Nikola Zaharakis, Nathaniel R. Riggs, Aaron Brown, Michael J. Mason)

Evaluating the Effectiveness of AI Foundation Models in Representing and Understanding Movement Trajectories
(Yuhan Ji, Song Gao )

A graph-based conflation framework for building footprints
(Jack Joseph Gonzales, Taylor Hauser, Robert Stewart )

Towards Spatio Temporal Graph Representations for Historical Spatial Data
(Anne-Pauline Couteaud, Géraldine DEL Mondo, Benoit Gauzere, Florent Hautefeuille, Clement Chatelain )

Modelling surface and underground streams in drainage network computation
(Yassmine Zada, Eric Guilbert, Sylvain Jutras )

Learning-based Clustering Method for Semantic Place Retrieval
(Jiamin Lu, Jiahao Liu, Zhendong Fan, Zhenyu Zhou, Xu Kong, Jun Feng )

How do Humans and Computers Perform Differently in Site Selection? Insights from an Ambulance Station Placement Game
(Lars De Sloover, Bart De Wit, Haosheng Huang, Nico Van de Weghe )

Teaching about spatial navigation: some (inter)disciplinary insights
(Angélique Lydia Montuwy )

Predictive cognitive mapping of geographic spaces
(Ed Manley, Daniel C McNamee )

Quo vadis Map-based Search?
(Krzysztof Janowicz, Meilin Shi, Zilong Liu, Noemi Beluli, Glenys Laetitia Bischoff, Laura Marlene Huber, Paul Huber, Moritz Imrecke, Manuel Kastner, Dominik Knabe, Franziska König, Rainhard Neuhauser, Niklas Neustätter, Selina Stephanie Straßburger, Stefan Karl Thurnhofer, Florian Mathias Venier, Laura Welz )

Comparing the acquisition of spatial knowledge through augmented reality landmarks on windshield: Online vs. Virtual Reality
(Muxu Wang, Rui Li, Jiayan Zhao )

Uncovering Regional Defaults from Photorealistic Forests in Text-to-Image Generation with DALL·E 2
(Zilong Liu, Krzysztof Janowicz, Kitty Currier, Meilin Shi )

An Investigation of Strategy Use on The Block Design Task
(Danielle Rothschild, Kiley McKee, Mackenzie Drummond, David Uttal )

Achieving Improved Geospatial Data Integrity Through Spatio-Semantic Conflation of Disparate Sources of Volunteered Geographic Data
(Joseph Bentley, Kelly Sims, Gautam Malviya Thakur )

Description: Research on spatial cognition has been conducted in various disciplines and used different methods and empirical measures, for example, behavioral responses such as pointing, self-report questionnaires, and psychometric ability tests. Nowadays, technologies enable researchers to collect new types of data, such as eye tracking data, neurophysiological observations, and GPS tracking records. With these traditional and new data available, researchers can look into various aspects of human spatial cognition, but at the same time, need to consider how different insights from different methods can be integrated.

The past decade has also seen a growth of interest in the role of spatial cognition in GIScience, primarily through the lens of urban mobility. There is equally a growing availability of data and technologies capable of deepening insight into human behavior and spatial cognition in cities. Despite attempts to widen the accessibility of spatial cognition within GIScience, the broader geo-spatial community has not fully embraced the cognitive mechanisms and representations that shape and are shaped by urban phenomena. More importantly, formalizations of spatial cognition research are still scarce in GIS and urban analytics processing.

This thematic discussion session is designed to resonate with the COSIT community's interest in how the interpretation and representation of spatial information influences human behavior. The aim is to bring together a new community of researchers, with diverse perspectives, interested in the interface of spatial cognition and GIScience. To that end, we will discuss what methods are available to study spatial cognition, how to collect data with these methods, how to analyze and interpret the data collected, and how data from different methods relate to each other, so that we can broaden our knowledge of human spatial cognition in interdisciplinary collaboration.

Organizers:
Gabriele Filomena, University of Liverpool, UK
Toru Ishikawa, Toyo University, Japan
Armand Kapaj, University of Zurich, Switzerland
Ed Manley, University of Leeds, UK
Angela Schwering, University of Muenster, Germany

A Salience-based Framework for Terrain Modelling: From the Surface Network to Topo-Contexts
 (Eric Guilbert, Bernard Moulin)

Revealing differences in public transport share through district-wise comparison and relating them to network properties
 (Manuela Canestrini, Ioanna Gogousou, Dimitrios Michail, Ioannis Giannopoulos)

The Senators Problem: A Design Space of Node Placement Methods for Geospatial Network Visualization
 (Arnav Mardia, Sichen Jin, Kathleen M. Carley, Yu-Ru Lin, Zachary Neal, Patrick Park, Clio Andris)

Exploring Discrete Spatial Heterogeneity across Quantiles: A Combination Approach of Generalized Lasso and Conditional Quantile Regression
 (Ryo Inoue, Kenya Aoki)

Location retrieval using qualitative place signatures of visible landmarks
 (Wei, Lijun, Valérie Gouet-Brunet, and Anthony G. Cohn)

Box lunch will be provided. We need to be down at the harbor for the boat cruise starting at 13:30. It is roughly a 10 minute walk downhill.

The COSIT conference series traditionally enriches its academic program with a local excursion, offering participants, many from international locales, a unique glimpse into the local environment and culture. This year, conference participants are invited on a boat cruise of the St. Lawrence River. One of North America's most significant waterways, the St. Lawrence River offers a wealth of natural beauty, historical significance, and economic importance.

Address: Gare fluviale de Québec | Traverse Québec-Lévis, 10 Rue des Traversiers, Québec, QC G1K 8L8

Please arrive by 13:30 as the boat departs promptly at 14:00.

Qualitative Formalization of a Curve on a Two-Dimensional Plane
 (Kazuko Takahashi)

Towards Formalizing Concept Drift and Its Variants: A Case Study Using Past COSIT Proceedings
 (Meilin Shi, Krzysztof Janowicz, Zilong Liu, Kitty Currier)

A Logic of East and West for Intervals
 (Zekai Li, Amin Farjudian, Heshan Du)

Can You Sketch in 3D? Exploring Perceived Feasibility and Use Cases of 3D Sketch Mapping
 (Kevin Gonyop Kim, Tiffany C.K. Kwok, Sailin Zhong, Peter Kiefer, Martin Raubal)

Inferring the origin of linguistic features from an atlas: a case study of Swiss-German dialects
 (Takuya Takahashi, Elvira Glaser, Peter Ranacher)

Comparisons of Chicago Neighborhood Boundaries from Crowdsourced Resident Drawings
 (Crystal Bae, Lydia Wileden, Emily Talen)

How do people parse dynamic maps? Insights from event segmentation experiments
 (Reena Pauly, Stephan Schwan)

Spatial Nudging: Converging Persuasive Technologies, Spatial Design, and Behavioral Theories
 (Ayda Grisiute, Martin Raubal)

Exploring the Relation Between Sense of Direction and Spatial Anxiety in Everyday Mobile Map App Use
 (Donatella Zingaro, Tumasch Reichenbacher, Mona Bartling, Sara Fabrikant)

Wheelchair users navigational behavior: insights from eye movement data and environment legibility
 (Sanaz Azimi, Mir Abolfazl Mostafavi, Angélique Lydia Montuwy, Krista Lynn Best, Aurélie Dommes)

Collective Spatial Cognition: A Research Agenda
 (Curtin, Kevin and Daniel R. Montello)

Empirical characterisation of agents; spatial behaviour in pedestrian movement simulation
 (Filomena, Gabriele, Lia Kirsch, Angela Schwering, and Judith A. Verstegen)

The influence of landmark visualization style on task performance, visual attention, and spatial learning in a real-world navigation task
 (Kapaj, Armand, Christopher Hilton, Sara Lanini-Maggi, and Sara I. Fabrikant)

Lunch is on your own today. A list of eateries is available here.

Wayfinding Stages: The Role of Familiarity, Gaze Events, and Visual Attention
 (Negar Alinaghi, Ioannis Giannopoulos)

Is Familiarity Reflected in the Spatial Knowledge Revealed by Sketch Maps?
 (Markus Kattenbeck, Daniel R Montello, Martin Raubal, Ioannis Giannopoulos)

Long-term landmark and route memory retention acquired in a real-world map-aided navigation task
 (Armand Kapaj, Christopher Hilton, Sara Fabrikant)

Navigation challenges in urban areas for persons with mobility restrictions
 (Hoda Allahbakhshi, Annina Ardüser)

Assessing perceived route difficulty in environments with different complexity
 (Arvid Horned, Zoe Falomir, Kai-Florian Richter)

Description: This session explores the intersection of Geographic Information Science (GIScience) and Large Language Models (LLMs). We focus on the opportunities that emerge when these two fields converge, particularly in enhancing methods for spatiotemporal data analysis and visualization.

To bridge the gap between theoretical advancements and practical applications, we will delve into a specific research question: Can human descriptions of the evolution of a particular attribute on a time series of maps, processed through advanced language models, effectively match quantitative clustering methods? This inquiry not only tests the capabilities of LLMs in capturing and analyzing the nuances of temporal changes depicted on spatial maps but also challenges our understanding of how humans perceive and articulate these changes.

In the workshop, we will present an experimental approach where participants will observe and describe the evolution of a non-spatial attribute on a time series of maps. These textual descriptions, entered via mobile devices by the workshop participants, will be processed using an LLM, to generate a distance matrix that represents the perceptual (dis)similarities between the observed spatial entities. We will try and examine whether human descriptions, and the inferred similarities between entities can match quantitative clustering, highlighting the potential of LLMs to bridge the gap between qualitative perceptions and quantitative analyses. This exploration will help us understand the spatiotemporal reasoning and cognition involved in natural language descriptions of spatial phenomena.

We will discuss how integrating LLMs with GIScience can aid in unraveling the complexities of spatiotemporal information and how this can transform the theory and practice of spatial information processing. Further, the session will offer a platform for participants to exchange ideas, discuss challenges, and collaboratively explore future directions in this field of research. In addition to the interactive workshop activities, we aim to use the insights gained from this experimental approach, as well as the discussions that emerge during the session, as foundational elements for a scholarly paper. This future publication will detail our findings and methodologies, offering a comprehensive analysis of the potential and limitations of integrating LLMs with GIScience. We welcome the possibility of collaborating with interested workshop participants on our upcoming scholarly paper. Participants can express their interest during the workshop.

Organizers:
Nico Van de Weghe, Ghent University, Belgium
Lars De Sloover, Ghent University, Belgium

The conference dinner will take place at the Morrin Cultural Centre, within walking distance (10 minutes) of the conference venue. Hors d'oeuvre will start at 18:00 with plated dinner being served at 19:00.

Towards knowledge-aware spatiotemporal data analytics in AI systems

Elena Demidova

Professor, University of Bonn & Lamarr Institute for Machine Learning and Artificial Intelligence

Abstract
The objective of my research is to establish a comprehensive knowledge- and learning-based paradigm for spatiotemporal knowledge representation at the intersection of semantic and data-driven artificial intelligence. This involves AI algorithms with a deeper understanding of the spatiotemporal domain and next-generation AI models that significantly enhance prediction accuracy, interpretability, and user interaction. In this talk, I will discuss selected methods and algorithms developed by my research group towards this goal, including robust knowledge-aware predictive models for spatiotemporal data and knowledge graphs for semantic geospatial data management.

Speaker biography at https://cosit.ca

Description: This session was designed as a platform for doctoral students to showcase their research. During this session, graduate students at both early and advanced stages of their studies will present short lightning talks, offering a rapid and concise overview of their work across a diverse range of research topics. This format not only facilitates the exchange of innovative ideas and methodologies but also provides a unique opportunity for students to receive feedback, engage with COSIT peers and established scholars, and refine their communication skills in a supportive environment.

Facilitator:
Marcela, Suarez, Penn State University, USA (Doctoral Mentorship Chair)

What is a spatio-temporal model good for?
 (Simon Scheider, Judith Verstegen)

Four Arguments Why Places and Information About Places Are Linked
 (Franz-Benjamin Mocnik)

Handbook of Geospatial Artificial Intelligence
 (Gao, Song, Yingjie Hu and Wenwen Li)

Awards for best full paper, short paper, poster, and student papers