Movement Analytics in the Era of Big Data and Open Science

Posted on Published by Somayeh Dodge

Collegium Helveticum Workshop on Movement Analytics in the Era of Big Data and Open Science

June 19–20, 2024
Irchel Campus, University of Zurich

The research on movement data is developing fast, with applications spanning from health, mobility and sustainability research to movement ecology and climate change. Extensive technologies and data are available that facilitate developing new analytical methods and movement insights. However, open science remains a challenge in the field of computational movement analysis. Movement data and mobility insights are often proprietary and their usage is restricted due to inherent locational privacy and representation issues. Moreover, limited efforts have been made on investigating reproducibility and transferability of movement analytics across application domains and geographic scales.

This workshop brings researchers and technology developers from academia and industry together to discuss these challenges and new advancements in the field across disciplines. The discussions intend to identify gaps and opportunities for advancing open science using movement data through integrative and multidisciplinary approaches to study movement across different disciplines.

More information is available on the workshop website.

AMD2021: Advancing Movement Data Science

Posted on Published by Somayeh Dodge

Advancing Movement Data Science (AMD’21)

At the 11th International Conference on Geographic Information Science (GIScience 2021), 27 September 2021, Virtual workshop

AMD 2021 workshop is the 4th workshop in the pre-GIScience conference AMD workshop series, co-organized by Dr. Dodge. This workshop pursues three aims. First, to provide a platform to discuss the state of the art in this domain in the past decade. Second, to discuss the potential of data science methodologies to advance movement analytics in various domains such as human mobility and animal ecology. And third, to identify the key challenges for future research and (re-)define the research agenda towards advancing movement data science. For more information and to participate, please see the workshop webpage.

Workshop Themes

  • Data science and movement analytics
  • Integrated science of movement: converging human mobility and movement ecology research
  • From patterns to processes: Context-dependent movement analytics and bridging the semantic gap
  • From individuals to collectives: Modeling and analyzing interactions between individuals
  • Data fusion: Integrating different sensors (e.g. different positioning sensors and accelerometer or locational data with satellite remotely sensed products) and sensing models (checkpoint sensing vs continuous GPS tracking)
  • From analysis to modeling: Simulation of movement and mobility
  • Mobility and health
  • Big mobility data analytics and predictive modeling
  • Visualization and visual analytics in support of movement analysis
  • Geoprivacy issues and geomasking methods for mobility data
  • Ethics of movement data analytics

Workshop Organizers

MoVIS 2020 Workshop

Posted on Published by M0v3admin

IEEE VIS 2020 workshop on

Information Visualization of Geospatial Networks, Flows and Movement (MoVis)

26 October 2020, Virtual workshop

View the recorded live stream on YouTube

Workshop Schedule

We are one of many exciting workshops at IEEE VIS which will be held on Monday, October 26th, 2020. Our workshop starts at 12:00 pm (US Mountain Time) and ends at 3:15 pm (US Mountain Time).  Please download the visual guide to our schedule below.

Here is the link to watch the recorded live stream on YouTube: http://tinyurl.com/ieeemovis20

Invited Keynote
  • 12:00-12:40 – Jeremy White (Graphics editor for The New York Times and adjunct professor at Columbia University)
Short Paper Session Talks
Break and Social Time  1:30 pm – 2:00 pm (US Mountain Time)
Join us for breakout rooms using this link.
Session B  1:45 pm – 3:15 pm (US Mountain Time) Streaming live on YouTube
Interactive Session for Work in Progress
  • 2:00-2:10 – Jugal Patel, Jeffery Katan, Lilliana Perez and Raja Sengupta “Transferring Decision Boundaries onto a Geographic Space: Agent-Rules Extracted from Movement Data using Classification Trees
  • 2:10-2:20 – Chenxiao Guo “Framing Twitter Trajectory Visualization: A Comparison Between Hurricane Evacuation and Pandemic Lockdown”
  • 2:20-2:30 – Hanan Samet, Yunheng Han, John H. Kastner, and Hong Wei “Using Animation to Visualize Spatio-Temporal Varying COVID-19 Data”
  • 2:30-2:40 – Xiaofan Liang “An R Online Tutorial for Visualizing Spatial Social Networks”
  • 2:40-3:15 – Discussion and closing remarks by the organizers

Workshop Summary

Researchers frequently access and visualize data that represent spatial connections. These include GPS trajectories, migration movement, mobile phone-based movement, social networks, flights, commutes, SMS/phone call connections, human and animal movement trajectories, commuter flows, international trade, disease transmission flows, remittance flows, online friendship connections and transportation magnitudes.  They are important in the study of globalization, wealth distribution, information spreading, epidemiological modeling, economics and infrastructure management.  At the same time, analyzing these data requires advanced visualization methods. The objectives of this workshop are to explore the best ways to visualize large, spatio-temporal flow systems with both node and edge attribute data; describe the best visualization methods to unearth meaningful results; facilitate the use of diverse big data sets, communicate these results through visualization and description; and reflect upon how visualization is best communicated for urban and regional studies, geography, urban planning, public health, civil engineering, sociology and related fields.

The MoVIS ’20 workshop is situated in a larger body of research on geovisualization, geospatial data analytics and exploratory spatial data analysis (ESDA). This body of work includes mapping spatial datasets using different visual techniques, and assessing how humans interact and gain insights from spatial data. Spatial flow data is a special type of data that presents issues like the “haystack” problem of overlapping flows, edge effects, issues of using polygon centroids as origins or destinations, and issues of scale and modifiable areal units.

Goals. The purpose of this workshop is to help advance the scientific capabilities of visualizing and interacting with large spatial connectivity datasets of movement, telecommunications and social relationship data. This workshop aims to provide a strategic link between the geographic information science (GIScience) and information visualization communities. The workshop will also expose researchers to a variety of flow data sources and enrich our knowledge of geospatial connectivity through innovative dynamic and static visualization tools and methods.

Workshop Themes

We invite submissions of short research papers (1500 words) or short abstracts of  ‘work in progress’ (500 words) that describe new research ideas that fit the general theme of Information Visualization of Geospatial Networks, Flows and Movement, including, but not limited to, the following topics:

  • Integrating thematic flows data with and reference maps
  • Evaluating interaction methods with flows
  • Comparing static vs. dynamic geographic flow visualization
  • 3D visualization of flows
  • Protecting privacy in visualizing GPS trace and movement data
  • Expressing temporal dynamics
  • Use of novel symbology combinations of transparency, color, thickness and interweaving techniques
  • Integrating multi-modal flows into one visualization
  • Dashboards and linked visualizations for data exploration with other data.
  • Spatial social network visualization
  • Interactive flow and network tools
  • Flow bundling algorithms
  • HCI considerations for user types and applications/case studies
  • Capturing bias and behavior patterns with flow data
  • Applying (a-spatial), force-directed, network visualization and graph drawing techniques to spatial problems

We will put special emphasis on supporting and nurturing the growth of emerging, nascent topics, including:

  • Cross-scale (multi-scale) flows
  • Multiplex networks (with multiple edge weights)
  • Flow uncertainty
  • Visual comparison of actual vs expected flows
  • Visualizing flow predictions
  • Open geospatial tools for flow analytics
  • Machine learning for visualizing flow growth and expansion

Program Committee

  • Anita Graser, Austrian Institute of Technology
  • Caglar Koylu, University of Iowa
  • Mauro Martino, IBM Software Group
  • Sara Irina Fabrikant, University of Zurich
  • Ming-Hsiang Tsou, San Diego State University
  • Anthony Robinson, The Pennsylvania State University
  • Alex Endert, Georgia Institute of Technology
  • Charles Perin, University of Victoria
  • Gennady Andrienko, Fraunhofer
  • Natalia Andrienko, Fraunhofer
  • John Stasko, Georgia Institute of Technology
  • Alasdair Rae, University of Sheffield
  • Polo Chau, Georgia Institute of Technology
  • Jo Wood, City University London
  • Menno-Jan Kraak, University of Twente
  • Aidan Slingsby, City University London
  • James Cheshire, University College London

Organizers contact details