Equitable Accessibility and Sustainable Mobility Workshop 2023 (EASM2023)

Further information: workshop website.

This workshop aims at bringing to the forefront discussions on how advances in geospatial data science can be leveraged to promote development that balances social, economic and environmental sustainability in transport and mobility to build more equitable neighbourhoods and sustainable communities. This may include new methods and technologies as well as applying existing geospatial technique to uncover how inequalities affect accessibility and mobility based on i.e. gender, income, race etc. Given the interdisciplinary nature of this topic, the workshop welcomes contributions by researchers coming from a wide range of backgrounds in a format that involves both short presentations and guided discussions.
The workshop is being jointly organised with the OTESAMA workshop.

Organisers:
Grant McKenzie, McGill University (grant.mckenzie@mcgill.ca)
Alessia Calafiore, University of Edinburgh
Andrea Ballatore, King’s College London
Henrikki Tenkanen, Aalto University
Rafael Pereira, Institute of Applied Economic Research
Christoph Fink, University of Helsinki
Vanessa Bastos, University of Canterbury
Eun-Kyeong Kim, Luxembourg Institute of Socio-Economic Research

Workshop on Open Tools for Equitable and Sustainable Accessibility and Mobility Analysis (OTESAMA '23)

Further information: workshop website.

OTESAMA '23 workshop aims at bringing to the forefront open scientific software, data-driven tools as well as other methodological advancements that support understanding and modelling accessibility and/or mobility and their linkages to social-environmental sustainability in urban or rural settings. Given the interdisciplinary nature of this topic, the workshop welcomes contributions by researchers coming from a wide range of backgrounds in a format that involves both short presentations and demo sessions. We invite submissions of short research papers and abstracts that describe novel open-source computational tools and methodological advancements aligned with the general theme of the workshop of equitable and sustainable accessibility and mobility.
The workshop is being jointly organised with the EASM2023 workshop.

Organisers:
Henrikki Tenkanen, Aalto University, Finland (henrikki.tenkanen@aalto.fi)
Rafael Pereira, Institute of Applied Economic Research, Brazil
Christoph Fink, University of Helsinki, Finland
Grant McKenzie, McGill University, Canada
Alessia Calafiore, University of Edinburgh, UK
Andrea Ballatore, King’s College London, UK
Vanessa Bastos, University of Canterbury, New Zealand

An Introduction to Network Analysis

This workshop offers an introduction to Network Analysis. It provides an overview of the most fundamental concepts and methods of Network Analysis, some of which are particularly relevant for GIScience. The workshop follows a hands-on approach through a series of computational activities in R. By the end of the workshop, you should be able to:

• Demonstrate an understanding of core Network Analysis concepts and methods
• Be able to import and process real-world data for Network Analysis
• Apply visualisation and exploratory techniques from Network Analysis to extract information from real world-data

The workshop will use a learn-by-doing approach where you will take an active role in your own learning process. The concepts and methods will be illustrated through real data used in peer-reviewed published research. The design of the workshop will allow for informal conversations between the participants and organisers.

Organisers:
Carmen Cabrera-Arnau , Geographic Data Science Lab, University of Liverpool, UK
Francisco Rowe, Geographic Data Science Lab, University of Liverpool, UK
Valentina Marin Maureira, Centre for Advanced Spatial Analysis, University College London, United Kingdom
Rafael Prieto-Curiel, Complexity Science Hub Vienna, Austria
Andrew Renninger, Centre for Advanced Spatial Analysis, University College London, United Kingdom

Geospatial Knowledge Graphs and GeoAI: Methods, Models, and Resources (GeoKG & GeoAI 2023)

Further information: workshop website.

Applying Artificial Intelligence to various geospatial problems has become mainstream in GIScience and Geography in the past few years. However, we still lack a systematic framework to make these methods spatially explicit as well as explainable in the context of geographic applications. One recent trending solution is to combine symbolic AI approaches (ontology and knowledge graphs) with those subsymbolic ones (neural networks and representation learning). This workshop, therefore, aims to provide a venue for researchers in the GIScience community to share ideas and work along this exciting track. Topics include geospatial semantics, geo-ontology and knowledge graphs, spatially explicit machine learning, etc.

Organisers:
Rui Zhu, University of Bristol, UK (rui.zhur@bristol.ac.u)
Gengchen Mai, University of Georgia, USA (gengchen.mai25@uga.edu)
Ling Cai, IBM Research, USA (lingcai@ibm.com)
Ana Basiri, University of Glasgow, UK (ana.basiri@glasgow.ac.uk)
Stefano De Sabbata, University of Leicester, UK (s.desabbata@leicester.ac.uk)
Krzysztof Janowicz, UC Santa Barbara, USA & University of Vienna, AT (krzysztof.janowicz@univie.ac.at)

Disruptive Movement Analysis (DMA2023)

Further information: DMA2023 website.

The objective of our workshop is to 'disrupt' the status quo of modern movement analysis. In recent years, we have witnessed major shifts in human mobility and animal activity patterns in response to disruptive environmental events (e.g., natural disasters, pandemics, etc.). To really develop new insights into the spatial-temporal patterns of movement we need novel, radical ideas that direct the field into exciting new directions. This workshop will focus on collecting researchers interested in developing new methods, applications, and insights using modern movement data. The workshop will feature submitted research talks, open discussion panels, and a data challenge.

Organisers:
Dr. Jed Long, Western University, Canada (jed.long@uwo.ca)
Dr. Somayeh Dodge, University of California-Santa Barbara, USA (sdodge@ucsb.edu)
Dr. Urška Demšar, University of St Andrews, UK (urska.demsar@st-andrews.ac.uk)
Prof. Dr. Rob Weibel, University of Zurich, Switzerland (robert.weibel@geo.uzh.ch)

Mapping with communities, international workshop

Further information: website or PDF.

The workshop aims at offering a space for dialogue about challenges and approaches to "map WITH communities" as well as to steer interaction between researchers working around methodologies, technologies and strategies to engage communities with mapping, geospatial data production and analysis. The workshop will also boost further collaboration between participants and integration with ongoing projects.

Among the multiple interfaces with GIScience, workshop organisers encourage participants to submit works on participatory mapping, citizen science and enabler technologies. The workshop will offer a space to analyse current and emerging challenges ranging from the ethical implications of mapping with communities to the latest development within the IDEAMAPS Network.

Organisers:
Caroline Kabaria (Ckabaria@aphrc.org)
Dana Thomson (Dana.r.thomson@gmail.com)
Diego Pajarito (Diego.pajaritograjales@glasgow.ac.uk)
Erika Upegui (Esupeguic@udistrital.edu.co)
Serkan Girgin (S.girgin@utwente.nl)

Location matters: identifying and measuring space-based inequalities for LGBT+ people

Further information: workshop website.

All individuals face some constraints in choosing where to live. However, the degree of freedom can vary considerably between individuals - perhaps in particular for people from minoritised communities. The questions on gender identity and sexual orientations in the 2021 UK Census have highlighted the importance of collecting LGBT+ data and the existing appetite for it. However, social and spatial inequality for LGBT+ people has not gained the same level of awareness as other social groups.

This workshop aims to kickstart the development of a framework to describe the factors that shape LGBT+ people’s choices of residential locations. It will explore what data exists (or does not exist) to measure the trade-offs these factors imply, for example in terms of housing costs and proximity to community spaces. Contributions are particularly welcome from all fields of research focusing on social and spatial inequalities.

Organisers:
Dr. Stef Garasto (S.Garasto@greenwich.ac.uk)
Dr. Jia Wang (J.Wang@greenwich.ac.uk)

Data models and modelling environments for field-agent based modelling

Further information: workshop website.

Many simulation models needed for instance for hydrological, ecological, or health studies require the combination of fields representing spatially distributed values (e.g. elevation, catchments, land use or contamination) and agents representing individual objects (e.g. trees, agricultural farms, or humans).

This workshop invites participants dealing with the challenge of combining fields and agents in their simulation models to give a lightning talk about their work. Furthermore, it provides hands-on exercises for Campo, a Python modelling environment providing operations accepting both fields and agents as arguments. Campo resembles and extends the map algebra approach to field-agent modelling and allows for the construction of static or dynamic models. Campo builds upon LUE, a conceptual and physical data model for storage and access of field or agent data.

Organisers:
Dr. Oliver Schmitz, Utrecht University Faculty of Geosciences, Dept Physical Geography (o.schmitz@uu.nl)
Dr. Judith Verstegen, Utrecht University Faculty of Geosciences, Dept Human Geography and Spatial Planning (j.a.verstegen@uu.nl)
Prof. Dr. Derek Karssenberg, Utrecht University Faculty of Geosciences, Dept Physical Geography (d.karssenberg@uu.nl)

Geographic question-answering (geoQA)

Further information: website or PDF.

Question-answering (QA) is a form of verbal, dialogue-based interaction with information. Research on the technologies and challenges of QA has surged in information science, including phrase analysis, phrase mappings, entity disambiguation and the construction of formal queries. Since geography is an important part of human-asked questions, geographic question answering (geoQA) has recently become an area of intensive research. This workshop focuses on geoQA from a practical hands-on perspective to learn about the state-of-the-art as well as knowledge and technology gaps. In the workshop, we will demonstrate and compare systems and approaches, and identify suitable directions for future research.

Organisers:
Haiqi Xu¹, Ehsan Hamzei³, Manolis Koubarakis², Martin Tomko³, Gengchen Mai⁴, Simon Scheider¹

1. Department of Human Geography and Planning, Utrecht University, NL;
2. Department of Informatics and Telecommunications, National and Kapodistrian University of Athens, GR;
3. Infrastructure Engineering, University of Melbourne, AU; 4Department of Geography, University of Georgia, USA;

Geospatial Web Apps in Python and R

Further information: PDF (download).

This full day workshop will teach participants the basics of transforming spatial models into interactive web apps which allow the public to explore and understand the results of their research using visualisation and interactivity libraries in Python and R. Web apps can be a powerful communication tool which allow users to tune parameters and understand specific scenarios relevant to them, which is particularly important for geospatial data which often relates to the environment. Through using off the shelf tools in Python and R, and free hosting platforms, participants will build a simple example application and learn how to host and share it with others.

Organisers:
Josh Redmond (jr725@exeter.ac.uk)
Liam Berrisford (L.berrisford@exeter.ac.uk)
Nathanael Sheehan (ns651@exeter.ac.uk)

Centrality indicators for road network analysis: from concept to implementation

Further information: Please note that participants who would like to attend this workshop must register with the workshop organisers separately before 30th June. Instructions are on the workshop website.

Road networks form an integral component of global infrastructures, and understanding how parts of these networks are used is important in many use-cases. Through the use of centrality indicators which can identify important nodes and edges in a graph network, it is possible to perform valuable analyses such as modelling traffic speeds and identifying critical roads to support disaster preparedness. This workshop – facilitated using an “open space” approach - will provide a platform to learn about centrality indicators and discuss current challenges both at a conceptual as well as a technical implementation level.

Organisers:
Christina Ludwig^1,2 (christina.ludwig@uni-heidelberg.de)
Marcel Reinmuth² (marcel.reinmuth@heigit.org)
Adam Rousell² (adam.rousell@heigit.org)
Alexander Zipf^1,2 (zipf@uni-heidelberg.de)

1. GIScience Research Group, Institute of Geography, Heidelberg University, Germany
2. Heidelberg Institute for Geoinformation Technology (HeiGIT) gGmbH at Heidelberg University, Germany

CartoAI: AI for cartography

Further information: workshop website.

Following the recent evolutions of cartography, and a successful workshop in 2022 on Computational Cartography and Map Generalisation with Deep Learning, this CartoAI workshop seeks to gather the researchers working on artificial intelligence techniques applied to cartography. For this workshop, contributions on all AI techniques are welcome including, e.g., machine learning, optimization, and multi-agent systems. The workshop will give the opportunity to the participants to give short presentations of recent and on-going research. It will also include a keynote and time for discussions. The workshop is endorsed by the ICA commission on map generalisation and multiple representation.

Organisers:
Yu Feng, TU Munich, Germany (y.feng@tum.de)
Cheng Fu, University of Zurich, Switzerland (cheng.fu@geo.uzh.ch)
Jan-Henrik Haunert, University of Bonn, Germany (haunert@igg.uni-bonn.de)
Rachid Oucheikh, Norwegian University of Science and Technology, Norway (rachid.oucheikh@ntnu.no)
Guillaume Touya, IGN, Univ. Gustave Eiffel, France (guillaume.touya@ign.fr)
Zhiyong Zhou, University of Zurich, Switzerland (zhiyong.zhou@geo.uzh.ch)

GI Science education in an AI world: educating scientists and practitioners

Further information and registration:
The workshop is open to all but please contact mgould@esri.com if you would like to be a presenter.

GI Science conferences tend to focus on research but teaching should not be ignored or disconnected. As technology and society evolve, datasets grow and the value of GIS across new and existing industries strengthens, opportunities for graduate students are increasing. To bridge these transformations we need to think of how to educate and what to teach so as to prepare students.
This workshop facilitates an open discussion on our purpose as GIS educators and helps to define a common direction for both the academic and non-academic sectors. What GI theory and skills are we embedding in these students, what motivates our decisions on what is relevant, where do our students go to work after graduation? Will they become GI Scientists or entrepreneurs or GIS consults? Do our GI academic programs compete well with emerging data science and other related programs?
Hello, LLMs and other revolutionary AI !! What are the challenges and opportunities afforded by these breakthroughs?
The discussion will focus on what we do now, post-COVID, and as we enter new challenges. What should we be adopting in GIScience education over the next 5 years. To tailor discussion topics and speaker slots we encourage participants to participate in a short survey. Results of the survey and of the workshop output will feed a journal article coauthored by active participants.

Organisers:
Prof. Michael Gould (Esri, U. Jaume I)
Dr. Addy Pope (Esri UK)
Prof. Justine Blanford (U. Twente)
Dr. Damien Mansell (U. Exeter)
Prof. Ana Basiri (U. Glasgow)
Prof. Josef Strobl (U. Salzburg)

Deep learning for urban analytics

Further information: PDF

In recent years, GeoAI has emerged as an important topic in GIScience, leveraging advances in deep learning and artificial intelligence for geographical and spatio-temporal data analysis (SpaceTimeAI). One of the principal application domains has been in urban analytics, which uses the vast quantities of data generated in cities for tasks such as monitoring, forecasting and optimisation. In this workshop, we will introduce the key technologies underpinning GeoAI and SpaceTimeAI, supported by instructor led computer sessions focussing on applications in urban analytics. The workshop is suitable for early career researchers, industry participants, as well as established researchers interested in how AI could benefit their work. The language of instruction will be Python and a good knowledge of Python programming language is essential.

Organisers:
James Haworth (j.haworth@ucl.ac.uk)
Meihui Wang (meihui.wang.20@ucl.ac.uk)
Xiaowei Gao (xiaowei.gao.20@ucl.ac.uk)
Mustafa Can (mustafa.ozkan.18@ucl.ac.uk)
Xianghui Zhang (xianghui.zhang@ucl.ac.uk)