Symposium 2023 > Schedule

UCGIS Symposium 2023: GIScience in a Hybrid Physical-Virtual World

June 6 - June 8, 2023  (Workshops June 8-9)

Detailed schedule here: https://ucgissymposium2023.sched.com/

Tuesday June 6 | Wednesday June 7  |  Thursday June 8  |  Friday June 9

 Session Descriptions

Keynote Session

Everything everywhere all at once: Is GIScience ready for a quantum leap in a hybrid physical-virtual world?
Dr. Daniel Sui, Virginia Polytechnic Institute and State University (Virginia Tech)

With accelerated (and seemingly unstoppable) advances and innovations in artificial intelligence (AI)/machine learning(ML) in general and generative AI in particular, many fundamental concepts in GIScience (such as representations of space and time, truth/accuracy, geoethics etc.) have been disrupted and challenged.. This talk draws on basic concepts in quantum mechanics and earlier discussions on their potential applications in geography and GIScience to espouse a quantum leap for GIScience in a hybrid physical-virtual world. It explores how concepts, methods and understandings from quantum physics and emerging quantum computing and communication technologies can be translated into addressing fundamental issues posed by new advances of GeoAI. Unlike the earlier cartographic, analytical, computational, cognitive, and critical turns in GIScience, the proposed quantum turn provides a more robust and holistic perspective for the geospatial community to rethink ontological, epistemological, methodological, and ethical issues related to applications of geospatial technologies in a hybrid physical-virtual world. Distinctly different from previous paradigms, the quantum turn addresses head-on deep ontological and epistemological questions about what is really real, and how we know what we know. This talk will also explore the methodological and ethical implications of the emerging quantum turn for a better understanding of the social impacts of geospatial technologies. Quantum concepts such as complementarity, superposition, entanglement, and uncertainty provide a strong foundation for recognizing and positioning people (as opposed to technology) at the core of GIScience, as both problems and solutions facing humanity today.

Professional Papers I

Modeling the Health Benefits of Superblocks in a Physical-Virtual World Era
Kenan Li, Saint Louis University

Exploring observation hot-spots in massive VGI datasets across spatial scales: A case study of iNaturalist species sightings
Guiming Zhang, University of Denver

The Relational Reprojection Platform: Non-linear distance transformations of spatial data in R
Will B Payne, Rutgers University and Evangeline McGlynn, UC Berkeley

Pedestrian level urban outdoor heat exposure modeling and mapping
Xiaojiang Li, Temple University

Understanding public perspectives on fracking in the United States using social media big data
Xi Gong, et al., University of New Mexico 

Student Papers

Comparing human activity fragmentation in physical and virtual spaces using  massive internet records of mobile phones
Minglei Liao and Xintao Liu, The Hong Kong Polytechnic University 

Assessment of human mobility measures for revealing health disparities among socially vulnerable populations during the COVID-19 pandemic
Hoeyun Kwon  & Caglar Koylu, University of Iowa

Representation Learning of Regions using Unevenly Distributed, Incomplete Multi- Modal Data
Min Namgung, Theresa Chen & Yao-Yi Chiang, University of Minnesota 

A Unified Framework for Measuring Access Inequality in Hybrid Physical-Virtual World - A Case Study of Racial Disparity in Healthcare Access During CoVID-19
Meiliu Wu, Qunying Huang & Song Gao, University of Wisconsin-Madison

Gender Equity and Equality in the Geospatial Field in the United States
Valquiria Quirino, North Dakota State University, Courtney Walker, University of Kentucky & Shadi Maleki, Texas State University

Professional Papers II

The role of GIScience in K-12 STEM education in a hybrid world
Linna Li, CSU Long Beach

One Class, Three Modalities: Teaching GIScience in a Hyflex Learning Environment
Laura Loyola, et al., University of Southern California

Implementing Virtual Fieldwork in Feminist GIS Research: Lessons from Online Activity Diaries, Interviews, and Surveys
Fikriyah Winata, Department of Geosciences, Mississippi State University

GeoAI for Privacy-Preserving Trajectory Data Generation
Song Gao & Jinmeng Rao, University of Wisconsin-Madison

Insights from Two Surveys on the Reproducibility and Replicability of Geographic Research
Peter Kedron, Arizona State University, Joseph Holler, Middlebury College & Sarah Bardin, Arizona State University

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Workshop Descriptions

Workshop A: Cloud-Based Coding: Using Google Colab for Geospatial Education and Research

Thursday, June 8 | 1:30 - 3:00 pm

Presenter: Will B Payne, Rutgers University

As members of the UCGIS community are well aware, desktop GIS software (ArcGIS, QGIS, etc.) is not always the best tool to acquire, analyze, and represent spatial data about cities, or to scale workflows up for collaborative projects. Writing scripts in Python or R can be more powerful and efficient approaches, but can have significant learning curves for students and technical challenges for instructors compared to a traditional GIS lab. In a setting where students are all working on their own computers, inordinate amounts of time can be spent on ensuring a harmonized technical stack for the whole class. Managing your own Python environment and libraries can be a headache on its own, but scaling that to a group of 20 or more students across a variety of machines and operating systems can quickly spiral out of control.

In this workshop, I will demonstrate how using Google Colab interactive Python notebooks (essentially Google-hosted Jupyter notebooks) can help to solve this problem for GIS educators, based on a graduate course I taught at Rutgers University in the Fall 2022 semester. In the course, students used the Python language (and popular geospatial libraries including geopandas, osmnx, and folium) to acquire and clean real urban data, join attribute data to geometries, generate high-quality maps and charts (both static and interactive), conduct spatial statistical and network analyses, export maps and data to use elsewhere.

Over the course of the 90-minute workshop, participants will learn how to set up geospatial workflows in interactive Colab notebooks, pull in data stored on Google Drive, external websites, or accessed via APIs, and help students publish interactive Folium maps for free on GitHub Pages. In addition to formal courses, this method can come in handy for research collaborations, especially with rotating personnel who have varying levels of familiarity with programming.

Workshop B: Learning SQL in QGIS

Thursday, June 8 | 3:30 - 5:00 pm

Presenters: Xiang Chen, Congcong Miao, University of Connecticut; Lu Liang, University of North Texas

The workshop is a hands-on training session about using basic Structured Query Language (SQL) queries in SpatiaLite, which is the spatial database used in QGIS.

Participants need to bring a laptop (Windows or Mac) to the workshop. It is suggested that participants install QGIS, which is free and open access, on their laptop prior to the workshop.

Workshop C: Open Educational Resources for Geospatial Teaching & Learning

Friday, June 9 | 8:30 - 10:00 am

Presenter: Diana Sinton, UCGIS

This workshop will focus on the formal and informal roles of open educational resources (OERs).  We will share tips and tricks for search & discovery and integration into our academic workflows. We will review an evaluation framework that has been designed especially for geospatial OERs. Activities underway to expand the OER functionalities of the GIS&T Body of Knowledge will be presented. This workshop is supported with funding from the Institute for Museum & Library Services as part of the GLOW project (GIS Librarians for Open Workflows), based at the University of Chicago. 

Workshop D: Applying Spatial Data Science: A Complete Workflow

Friday, June 9 | 8:30 - 10:00 am

Presenters: Brian Baldwin, Geri Miller, and Angela Lee, Esri

Spatial data science is an iterative process that extends beyond the run of one tool. We’ll demonstrate an analysis workflow from start to finish, providing a framework for the spatial data science process. Starting with data engineering and visualization, we’ll prepare our data and begin exploration through visual analysis. Next, we’ll explore how to compare and evaluate different modeling techniques and learn how to apply them to make predictions. Finally, we’ll tie it all together and see how we can use our predictions to drive action.

Participants should bring a laptop with ArcGIS Pro installed.

Workshop E: Sustaining Geospatial Dashboards in the Post-COVID-19 Virtual to Physical World

Friday, June 9 | 10:30 am - noon

Presenter: Sarbeswar Praharaj, Arizona State University

Dashboards are software tools that allow data visualization through maps, charts, graphs, and indicators to present the most critical information needed to achieve one or more objectives. Dashboards can consolidate and communicate a complex set of big data from different agencies and sources on a single screen or a webpage for monitoring information and events in real-time for responding to urban issues. Urban planning and management of cities through big data and real-time dashboards are hallmarks of smart cities. Although there are many benefits and applications of dashboards established in scholarly literature, and several ready-to-use technologies and proven design approaches available, the use of dashboards in urban settings as a decision-support system has been limited. The recent flurry of dashboards during the COVID-19 pandemic developed and disseminated by various actors, ranging from local community groups, public organizations, universities, and international agencies have given new momentum and purpose to the debates around geospatial information dashboards. Although many articles discussed dashboards as a tool to contain the pandemic, one has to wonder what role these technologies will play in the post-pandemic world and the overall sustainability of such digital ventures. This session will explore the relevance and applicability of geospatial dashboards to contribute to long-term community resilience as we move back from a predominantly virtual life during COVID-19 to the real physical space. We will examine the major challenges in sustaining geospatial dashboard projects and reveal the enduring opportunities offered by this powerful GIScience application in supporting climate resilience and social justice. 

Workshop F: Leveraging Language Models for Learning Geo-Entity Representation

Friday, June 9 | 10:30 am - noon

Presenters: Jina Kim, Yao-Yi Chiang, Malcolm Grossman, Min Namgung, University of Minnesota

Topic geo-entity detection from documents and geo-entity typing and linking are essential tasks for enabling various applications. This workshop provides a unique opportunity for participants to learn about open-source machine learning tools and pre-trained language models, such as SpaBERT, for these tasks. Through hands-on exercises, attendees will gain the skills and knowledge necessary to 1) use and train the tools to identify the topic geo-entity of a document, and 2) use and fine-tune SpaBERT for geo-entity typing and linking. Participants are encouraged to bring text documents they would like to test.

Note: This workshop also has a virtual option.  Please select it when registering to receive a link join virtually.

Participants should bring a laptop with Python installed. Basic knowledge of Python is required to complete the experiments.

Workshop G: How Universities Use Data for Road Safety Innovation CANCELLED

Friday, June 9 | 1:00 - 2:30 pm

Presenter: Wejo staff

Big Data is complex. While its sheer vastness brings unprecedented potential, its actual impact comes down to how it is processed and organized. That's why making Big Data accessible and easy to use is critical for solving problems, informing decisions, and seizing new opportunities. Wejo recognizes this gap and has focused on building solutions that take its source data - which includes trillions of data points generated from tens of millions of active connected vehicles - and making it more digestible and easy to use for research and real-world applications. 

Wejo's university partners are experts at translating raw Connected Vehicle Data (CVD) into purpose-built solutions that are uniquely positioned to serve the Departments of Transportation (DOTs) they support. Leading transportation research organization, UCONN's Connecticut Transportation Institute (CTI), is one example of a university partner working with Wejo smart mobility data to fuel their safety research.

In this workshop, Wejo and CTI will provide examples of real-world projects using Connected Vehicle Data. Specifically, CTI will walk you through their Crash Data Repository, and demonstrate how CVD guides their recommendations to make roadways safer.

This workshop will also cover:

• CTI's current capabilities and how they expect their research will change with the implementation of smart mobility data.
• Smart mobility data in action via product demonstrations

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GIScience Bowl

1.  After the question and choices have been read, your team has ten seconds!

2.  Hold up your card with the answer facing you.

3.  When told, turn the card around.

4.  If correct, supply your team cheer and self score.

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