Conference Program

Aug. 23 (Wednesday)
8:30 – 9:00 Registration and Refreshments
9:00 – 9:10 Welcome General co-Chairs
9:10 – 10:10 Keynote 1 – Democratizing Urban Data Exploration Juliana Freire (New York University)
10:10 – 10:40 Coffee Break
10:40 – 11:55 Research Session 1: Traffic and Transportation Session Chair: Andreas Züfle
10:40 – 11:05 Highway Systems: How Good are They, Really? (Best Paper Award) Theodoros Chondrogiannis (University of Konstanz), Michael Grossniklaus (University of Konstanz)
11:05 – 11:30 DEAR: Dynamic Electric Ambulance Redeployment Lukas Rottkamp (LMU Munich), Niklas A Strauss (LMU Munich), Matthias Schubert (Ludwig Maximilian University of Munich)
11:30 – 11:55 Traffic Spatial-Temporal Prediction Based on Neural Architecture Search Dongran Zhang (Sun Yat-sen University), Gang Luo (Sun Yat-sen University), Jun Li (Sun Yat-sen University)
11:55 – 13:30 Lunch Break (Lunch on your own)
13:30 – 15:15 Demonstration Session Session Chairs: Chiara Renso & Baihua Zheng
13:30 – 14:00 Demonstration Teaser Presentations All Demonstration Authors
14:00 – 15:15 Demonstration Poster & Demo Session All Demonstration Authors
Interactive Detection and Visualization of Ocean Carbon Regimes Sweety Mohanty (GEOMAR), Daniyal Kazempour (CAU Kiel), Lavinia Patara (GEOMAR, Kiel), Peer Kröger (Christian-Albrechst-University Kiel)
NALSD: A Natural Language Interface for Spatial Databases Mengyi Liu (Nanjing University of Aeronautics and Astronautics), Xieyang Wang (Nanjing University of Aeronautics and Astronautics), Jianqiu Xu (Nanjing University of Aeronautics and Astronautics)
An Interactive Map-based System for Visually Exploring Goods Movement based on GPS Traces (Best Demo Award) Reza Safarzadeh (University of Calgary), Yunli Wang (NRC), Sun Sun (National Research Council Canada), Xin Wang (University of Calgary, Canada)
RouteDOC: Routing with Distance, Origin and Category Constraints Thomas Frohwein (Iowa State University), Zachary Garwood (Iowa State University), Dylan Hampton (Iowa State University), Kevin Knack (Iowa State University), Nate Schenk (Iowa State University), Britney Yu (Iowa State University), Joe Zuber (Iowa State University), Goce Trajcevski (Iowa State University), Xu Teng (Iowa State University), Andreas Züfle (Emory University)
Scalable Spatial Analytics and In Situ Query Processing in DaskDB Suvam Kumar Das (University of New Brunswick), Ronnit Peter (University of New Brunswick), Suprio Ray (University of New Brunswick, Fredericton)
15:15 – 15:35 Coffee Break
15:35 – 16:50 Research Session 2: Machine Learning and Data Mining Session Chair: Matthias Schubert
15:35 – 16:00 Unveiling the Dynamic Interactions between Spatial Objects: A Graph Learning Approach with Evolving Constraints Daniel Glake (University of Hamburg), Ulfia Lenfers (University of Applied Sciences Hamburg), Thomas Clemen (University of Applied Sciences Hamburg), Norbert Ritter (University of Hamburg)
16:00 – 16:25 Towards Workload Trend Time Series Probabilistic Prediction via Probabilistic Deep Learning (Industry Track) Li Ruan (Beihang University), Heng Guo (Northeastern University), Yunzhi Xue (Institute of Software Chinese Academy of Sciences), Limin Xiao (Beihang University), Yuetiansi Ji (Beihang University)
16:25 – 16:50 VoCC: Vortex Correlation Clustering based on masked Hough Transformation in Spatial Databases Nelson Tavares de Sousa (Kiel University), Yannick Wölker (CAU Kiel University), Matthias Renz (University of Kiel), Arne Biastoch (GEOMAR Kiel)
17:00 – 19:00 Reception



Aug. 24 (Thursday)
8:30 – 9:00 Refreshments
9:00 – 10:00 Keynote 2 – Harnessing Spatiotemporal Data for Pandemic Preparedness with Privacy-Enhancing Technologies (PETs) Li Xiong (Emory University)
10:00 – 10:20 Coffee Break
10:20 – 11:35 Research Session 3: Maritime Data Session Chair: Karine Zeitouni
10:20 – 10:45 Towards a fixed-gear AIS trajectory differentiation (Vision Paper) Mirjam R Bayer (University Kiel), Daniyal Kazempour (University of Kiel), Peer Kröger (Christian-Albrechst-University Kiel)
10:45 – 11:10 Evaluation of Vessel CO2 Emissions Methods using AIS Trajectories Song Wu (Free University of Brussels), Kristian Torp (Aalborg University), Mahmoud A Sakr (ULB), Esteban Zimányi (Free University of Brussels)
11:10 – 11:35 DAISTIN: A Data-Driven AIS Trajectory Interpolation Method Búgvi Benjamin J Magnussen (Roskilde University), Nikolaj Bläser (Roskilde University), Hua Lu (Roskilde University)
11:35 – 13:00 Lunch Break (Lunch on your own)
13:00 – 14:30 Panel: New Applications for Spatiotemporal Data: Walid Aref, Cyrus Shahabi, Shashi Shekar, Goce Trajcevski, Jia Yu Session Chair: Andreas Züfle
14:30 – 18:30 Travel to Banff & Time for Social Program
18:30 – 21:30 Banquet



Aug. 25 (Friday)
8:30 – 9:00 Refreshments
9:00 – 10:05 Research Session 4: Data Processing Session Chair: Goce Trajcevski
9:00 – 9:25 Scalable Overlay Operations over DCEL Polygon Layers Andres Calderon (University of California, Riverside), Vassilis J. Tsotras (UC Riverside), Amr Magdy (University of California Riverside)
9:25 – 9:50 A Scalable Unified System for Seeding Regionalization Queries (Industry Track) Hussah Alrashid (University of California Riverside), Amr Magdy (University of California Riverside)
9:50 – 10:05 A New Primitive for Processing Temporal Joins (Short Paper) Meghdad Mirabi (Technical University of Darmstadt), Leila Fathi (Technical University of Darmstadt), Anton Dignös (Free University of Bozen-Bolzano, Italy), Johann Gamper (Free University of Bozen-Bolzano), Carsten Binnig (TU Darmstadt)
10:05 – 10:25 Coffee Break
10:25 – 11:40 Research Session 5: Recommendation Systems Session Chair: Amr Magdy
10:25 – 10:50 Social Community Recommendation based on Large-scale Semantic Trajectory Analysis Using Deep Learning Chaoquan Cai (Vanderbilt University), Wei Jiang (Oracle Labs), Dan Lin (Vanderbilt University)
10:50 – 11:15 Recommending the Least Congested Indoor-Outdoor Paths without Ignoring Time Vasilis E Sarris (University of Pittsburgh), Panos K. Chrysanthis (University of Pittsburgh), Constantinos Costa (Rinnoco Ltd)
11:15 – 11:40 A Design of Activity-Based Mobility Intervention Joon-Seok Kim (Oak Ridge National Laboratory), Gautam Thakur (Oak Ridge National Laboratory ), Carter Christopher (Oak Ridge National Laboratory)
11:40 – 13:10 Lunch Break (Lunch on your own)
13:10 – 14:25 Research Session 6: Satellite and Sensor Data Session Chair: Kyoungsook Kim
13:10 – 13:35 Viper: Interactive Exploration of Large Satellite Data Zhuocheng Shang (University of California, Riverside), Ahmed Eldawy (University of California, Riverside)
13:35 – 14:00 Harmonization-guided deep residual network for imputing under clouds with multi-sensor satellite imagery Xian Yang (North Carolina State University), Yifan Zhao (North Carolina State University), Ranga Raju Vatsavai (North Carolina State University)
14:00 – 14:25 An Energy Aware adaptive Clustering Protocol for Energy Harvesting Wireless Sensor Networks Ning Li (Inner Mongolia University), Winston Seah (Victoria University of Wellington), hou zhengyu (Inner Mongolia University), Bing Jia (Inner Mongolia University), Baoqi Huang ( Inner Mongolia University), Wuyungerile Li (Inner Mongolia University)
14:25 – 14:40 Closing Remarks General co-Chairs

Keynotes

Keynote 1 – Democratizing Urban Data Exploration

The growing ability to collect data from urban environments through a variety of sensors, coupled with a push towards openness and transparency by governments, has resulted in the availability of a plethora of spatio-temporal datasets. By analyzing these data, we have the opportunity to better understand how different urban components behave and interact over space and time, and obtain insights to make city operations more efficient, inform policies and planning, and improve the quality of life for residents. While there have been successful efforts in this direction, they are few and far between because analyzing urban data often requires a staggering amount of work: from identifying and wrangling relevant data, to performing exploratory analyses and creating predictive models. These tasks are often out of reach for domain experts that lack training in computing and data science. In this talk, I will discuss work we have done at the NYU Visualization, Imaging and Data Analysis (VIDA) Center that aims to democratize data exploration and empower domain experts to crack the code of cities by freely exploring urban data. I will present methods and systems which combine data management, analytics, and visualization to increase the level of interactivity, scalability, and usability for spatio-temporal data analyses.

Juliana Freire is an Institute Professor at the Tandon School of Engineering and Professor of Computer Science and Engineering and Data Science at New York University. She served as the elected chair of the ACM SIGMOD and as a council member of the Computing Community Consortium (CCC), and was the NYU lead investigator for the Moore-Sloan Data Science Environment, a grant awarded jointly to UW, NYU, and UC Berkeley. She develops methods and systems that enable a wide range of users to obtain trustworthy insights from data. This spans topics in large-scale data analysis and integration, visualization, machine learning, provenance management, and web information discovery, as well as different application areas, including urban analytics, predictive modeling, and computational reproducibility. She is an active member of the database and Web research communities, with over 250 technical papers (including 12 award-winning papers), several open-source systems, and 12 U.S. patents. According to Google Scholar, her h-index is 65 and her work has received over 18,000 citations. She is an ACM Fellow, a AAAS Fellow, and the recipient of an NSF CAREER, two IBM Faculty awards, and a Google Faculty Research award. She was awarded the ACM SIGMOD Contributions Award in 2020. Her research has been funded by the National Science Foundation, DARPA, Department of Energy, National Institutes of Health, Sloan Foundation, Gordon and Betty Moore Foundation, W. M. Keck Foundation, Google, Amazon, AT&T Research, Microsoft Research, Yahoo! and IBM. She has received M.Sc. and Ph.D. degrees in computer science from the State University of New York at Stony Brook, and a B.S. degree in computer science from the Federal University of Ceara (Brazil).

Keynote 2 – Harnessing Spatiotemporal Data for Pandemic Preparedness with Privacy-Enhancing Technologies (PETs)

The COVID-19 pandemic has demonstrated the importance of data for pandemic preparedness, in particular, human mobility and social interactions data that are strongly tied to the spatiotemporal spread of infectious diseases. Such data are sensitive, thus privacy enhancing technologies (PETs) become key enablers for data-driven pandemic preparedness. In this talk, I will review the landscape of PETs and their applicability for spatiotemporal data collection and analysis for pandemic preparedness. I will then highlight some of our recent and ongoing related efforts: 1) privacy-enhanced mobility trackingand contact tracing; 2) mobility data collection with local differential privacy to enable accurate mobility pattern analysis; 3) mobility data synthesization to enable downstream epidemic modeling (and other applications), and 4) federated learning to enable modeling on data distributed across institutions (and our support of the recent US-UK federated learning challenge for pandemic). I will conclude with a set of open research questions.

Li Xiong is a Samuel Dobbs Professor of Computer Science and Biomedical Informatics at Emory University. She held a Winship Distinguished Research Professorship from 2015-2018. She has a Ph.D. from Georgia Institute of Technology, an MS from Johns Hopkins University, and a BS from the University of Science and Technology of China. She and her research lab, Assured Information Management and Sharing (AIMS), conduct research on the intersection of data management, machine earning, and privacy and security, with a recent focus on privacy-enhanced and trustworthy data driven AI solutions for spatial intelligence, public health, and healthcare. Her research has been supported by both government agencies including NSF, NIH, IARPA, AFOSR, and PCORI, and industry companiesincluding Mitsubishi, Kaiser Permanente, Google, Cisco, AT&T, and IBM. She is an IEEE fellow.

Accepted Papers

Research Track

  • Social Community Recommendation based on Large-scale Semantic Trajectory Analysis Using Deep Learning
    Chaoquan Cai (Vanderbilt University), Wei Jiang (Oracle Labs), Dan Lin (Vanderbilt University)

  • An Energy Aware adaptive Clustering Protocol for Energy Harvesting Wireless Sensor Networks
    Ning Li (Inner Mongolia University)*, Winston Seah (Victoria University of Wellington), hou zhengyu (Inner Mongolia University), Bing Jia (Inner Mongolia University), Baoqi Huang ( Inner Mongolia University), Wuyungerile Li (Inner Mongolia University)

  • DEAR: Dynamic Electric Ambulance Redeployment
    Lukas Rottkamp (LMU Munich)*, Niklas A Strauss (LMU Munich), Matthias Schubert (Ludwig Maximilian University of Munich)

  • Evaluation of Vessel CO2 Emissions Methods using AIS Trajectories
    Song Wu (Free University of Brussels)*, Kristian Torp (Aalborg University), Mahmoud A Sakr (ULB), Esteban Zimányi (Free University of Brussels)

  • DAISTIN: A Data-Driven AIS Trajectory Interpolation Method
    Búgvi Benjamin J Magnussen (Roskilde University)*, Nikolaj Bläser (Roskilde University), Hua Lu (Roskilde University)

  • Traffic Spatial-Temporal Prediction Based on Neural Architecture Search
    Dongran Zhang (Sun Yat-sen University)*, Gang Luo (Sun Yat-sen University), Jun Li (Sun Yat-sen University)

  • Highway Systems: How Good are They, Really? (Best Paper Award)
    Theodoros Chondrogiannis (University of Konstanz)*, Michael Grossniklaus (University of Konstanz)

  • Scalable Overlay Operations over DCEL Polygon Layers
    Andres Calderon (University of California, Riverside)*, Vassilis J. Tsotras (UC Riverside), Amr Magdy (University of California Riverside)

  • Unveiling the Dynamic Interactions between Spatial Objects: A Graph Learning Approach with Evolving Constraints
    Daniel Glake (University of Hamburg)*, Ulfia Lenfers (University of Applied Sciences Hamburg), Thomas Clemen (University of Applied Sciences Hamburg), Norbert Ritter (University of Hamburg)

  • Viper: Interactive Exploration of Large Satellite Data
    Zhuocheng Shang (University of California, Riverside)*, Ahmed Eldawy (University of California, Riverside)

  • Harmonization-guided deep residual network for imputing under clouds with multi-sensor satellite imagery
    Xian Yang (North Carolina State University)*, Yifan Zhao (North Carolina State University), Ranga Raju Vatsavai (North Carolina State University)

  • A New Primitive for Processing Temporal Joins
    Meghdad Mirabi (Technical University of Darmstadt)*, Leila Fathi (Technical University of Darmstadt), Anton Dignös (Free University of Bozen-Bolzano, Italy), Johann Gamper (Free University of Bozen-Bolzano), Carsten Binnig (TU Darmstadt)

  • Recommending the Least Congested Indoor-Outdoor Paths without Ignoring Time
    Vasilis E Sarris (University of Pittsburgh)*, Panos K. Chrysanthis (University of Pittsburgh), Constantinos Costa (Rinnoco Ltd)

  • A Design of Activity-Based Mobility Intervention
    Joon-Seok Kim (Oak Ridge National Laboratory)*, Gautam Thakur (Oak Ridge National Laboratory ), Carter Christopher (Oak Ridge National Laboratory)

  • VoCC: Vortex Correlation Clustering based on masked Hough Transformation in Spatial Databases
    Nelson Tavares de Sousa (Kiel University)*, Yannick Wölker (CAU Kiel University), Matthias Renz (University of Kiel), Arne Biastoch (GEOMAR Kiel)

Demo Track

  • Interactive Detection and Visualization of Ocean Carbon Regimes
    Sweety Mohanty (GEOMAR)*, Daniyal Kazempour (CAU Kiel), Lavinia Patara (GEOMAR, Kiel), Peer Kröger (Christian-Albrechst-University Kiel)

  • NALSD: A Natural Language Interface for Spatial Databases
    Mengyi Liu (Nanjing University of Aeronautics and Astronautics), Xieyang Wang (Nanjing University of Aeronautics and Astronautics), Jianqiu Xu (Nanjing University of Aeronautics and Astronautics)*

  • An Interactive Map-based System for Visually Exploring Goods Movement based on GPS Traces (Best Demo Award)
    Reza Safarzadeh (University of Calgary), Yunli Wang (NRC), Sun Sun (National Research Council Canada), Xin Wang (University of Calgary, Canada)*

  • RouteDOC: Routing with Distance, Origin and Category Constraints
    Thomas Frohwein (Iowa State University), Zachary Garwood (Iowa State University), Dylan Hampton (Iowa State University), Kevin Knack (Iowa State University), Nate Schenk (Iowa State University), Britney Yu (Iowa State University), Joe Zuber (Iowa State University), Goce Trajcevski (Iowa State University)*, Xu Teng (Iowa State University), Andreas Züfle (Emory University)

  • Scalable Spatial Analytics and In Situ Query Processing in DaskDB
    Suvam Kumar Das (University of New Brunswick)*, Ronnit Peter (University of New Brunswick), Suprio Ray (University of New Brunswick, Fredericton)

Industry Track

  • Towards Workload Trend Time Series Probabilistic Prediction via Probabilistic Deep Learning
    Li Ruan (Beihang University)*, Heng Guo (Northeastern University), Yunzhi Xue (Institute of Software Chinese Academy of Sciences), Limin Xiao (Beihang University), Yuetiansi Ji (Beihang University)

  • A Scalable Unified System for Seeding Regionalization Queries
    Hussah Alrashid (University of California Riverside)*, Amr Magdy (University of California Riverside)

Vision Track

  • Towards a fixed-gear AIS trajectory differentiation
    Mirjam R Bayer (University Kiel)*, Daniyal Kazempour (University of Kiel), Peer Kröger (Christian-Albrechst-University Kiel)