2018 CGA Conference: Illuminating Space and Time in Data Science
Date and Time
Location
AUDIO recordings of the Conference are linked below.
The rapid proliferation of ‘smart’ objects have enabled a variety of sensors operating a wide range of scales -- from the body to the planet -- resulting in unprecedented volumes of digital data. The field of Data Science has been increasingly called upon to take on the unique challenges represented by this proliferation. Lacking any singular identity, Data Science may include discovering, understanding and communicating complex behaviors, patterns, relationships and trends from “big data” using mathematics/statistics, computation/automation, and domain knowledge -- combined. Data Science has as its subject nearly any field for which there exists high-volume, high-velocity and/or high-variety information assets that demand cost-effective, innovative forms of information processing that enable enhanced insight, decision making, and process automation (Gartner 2012).
The emergence of Data Science has provided a renewed opportunity to consider the importance of spatial relationships at the heart of these smart sensors and Internet of Things (IoT). Indeed, space and time are core properties of ‘big data’, so called, and spatiotemporal analysis is inherently an important facet in Data Science. From satellite images to social media streams, from census and parcels to records of trade, food, energy, climate, disease, crime, conflicts, etc., big data with space and time signatures are essential for understanding our world and responding to its challenges.
This conference aims at bringing together mainstream data scientists and geographic information scientists, to review the status of both fields, explore commonalities between the two, and identify the relevance of space and time in Data Science. The program will highlight new breakthroughs in Data Science; examine how to incorporate them into GIScience; demonstrate GIScience contributions to Data Science, particularly in terms of handling space and time; explore the proper relationship between Data Science and GIScience; discuss opportunities for reaching new audiences; and identify common educational needs for a data scientist and a GIScientist.
The event will start with a half-day hands-on demo and training workshop on Thursday afternoon, followed by a full day of plenary sessions on Friday, which will include a keynote address, presentation sessions, panel discussions, and closing remarks. Invited speakers will engage with the audience in discussions on the current status, achievements, lessons learned, unmet needs, challenges, potentials, and perspectives of spatiotemporal analytics in the context of Data Science, particularly as it relates to academic research and learning.
Keynote Speakers
Francesca Dominici, Co-Director of the Harvard Data Science Initiative, Professor of Biostatistics, Harvard T.H. Chan School of Public Health
Michael F. Goodchild, Emeritus Professor of Geography, University of California at Santa Barbara
Organizing Committee: David DiBiase (Esri); Wendy Guan (CGA); Elizabeth Langdon-Gray (HDSI); Matt Wilson (CGA)
SPONSORED by:
Day 1 -- Workshops -- Thursday, April 26th, 2017
Introduction - Jason Ur (CGA) AUDIO
Thu 1 Interacting with National Water Model Predictions, Devika Kakkar (CGA), Josh Lieberman (CGA) AUDIO SLIDES
Thu 2 Spatiotemporal Methodologies and Analytics for Extreme Weather Study – Using Dust Storm Event as an Example, Manzhu Yu (STC and GMU) AUDIO SLIDES
Thu 3 GeoAI: Machine Learning Meets GIS, Omar Maher (ESRI) AUDIO
Thu 4 Big Flow Data Visual Analytics through TrajAnalytics, Xinyue Ye (KSU and CGA) AUDIO SLIDES
Day 2 -- Conference -- April 27th, 2017
Introduction - Elizabeth Hess (IQSS) AUDIO
Fri AM Keynote: DATA SCIENCE AND OUR ENVIRONMENT, Francesca Dominici (Chan HSPH) AUDIO SLIDES
Fri AM Session 1: Sensors, Smart Objects and Infrastructure for Data Science
Fri (AM 1) 2 Senseable Cities, Carlo Ratti (MIT) AUDIO SLIDES
Fri (AM 1) 3 The University of Things (UoT), Peter Fox (Rensselaer) AUDIO SLIDES
Fri (AM 1) 4 Sensing in Space and Time, Mike Goodchild (UCSB) AUDIO SLIDES
Fri (AM 1) 5 Scientific Discovery in the Age of AI, Brendan Meade (Harvard EPS) AUDIO
Fri (AM 1) 6 Big Spatiotemporal Data Challenges and Opportunities, Phil Yang (GMU) AUDIO
Fri AM Session 2: Crowdsourcing, Geocomputation, and Spatiotemporal Analysis
Fri (AM 2) 1 Growing Trust and Transparency in Communities Where Predictive Algorithms are Deployed, Amen Ra Mashariki (NYU) AUDIO SLIDES
Fri (AM 2) 2 Making Spatial Aggregation More Transparent, Amelia McNamara (Smith) AUDIO SLIDES
Fri (AM 2) 3 Transdisciplinary Foundations of Geo-spatial Data Science, Shashi Shekhar (Smith) AUDIO SLIDES
Fri (AM 2) 4 Challenges and Solutions for the Analysis of New Forms of Data, Alex Singleton (Liverpool) AUDIO SLIDES
Fri (AM 2) 5 Progress in the Pipeline: Curating, Analyzing, and Conveying New Insights from Space-time Data, Robert Stewart (ORNL) AUDIO SLIDES
Fri PM Keynote: THE LANDSCAPE OF GISCIENCE , Michael Goodchild (UCSB) AUDIO SLIDES
Fri PM Session 1: Data Science for Cities, Health, and Environment
Fri (PM 1) 2 Empowering Local Communities through Data Analytics and AI, Emad Khazraee (Harvard Berkman/Kent State) AUDIO SLIDES
Fri (PM 1) 3 A Moral Compass for Data Science and AI in the City, Renee Sieber (McGill) AUDIO SLIDES
Fri (PM 1) 4 Putting Clinical (image) Data on a Map, Bjoern Menze (TU Munich) AUDIO
Fri (PM 1) 5 Estimating Pedestrian Flows on Street Networks: Revisiting the betweenness Index, Andres Sevtsuk (Harvard GSD) AUDIO SLIDES
Fri (PM 1) 6 A Convergence of Spatial Access, Amy Lobben (U Oregon) AUDIO
Fri PM Session 2: Geography, Civic Engagement, and the Future of Data Science
Fri (PM 2) 1 SocioEcological Applications of Remote Sensing Analysis at Scale, Jessica Block (UCSD) AUDIO SLIDES
Fri (PM 2) 2 Giving Relevance to Spatial Analytics and Spatial Data, Chris Cappelli (ESRI) AUDIO SLIDES
Fri (PM 2) 3 Why We Need Both Geography and Data Science to Achieve Sustainable Development, Robert Chen (Columbia/CIESIN) AUDIO SLIDES
Fri (PM 2) 4 Opening and Maintaining Lines of Communication between Data Science and Geographic Information Science, Diana Sinton (UCGIS) AUDIO SLIDES
Fri (PM 2) 5 Top-Down and Bottom-Up, Krzysztof Janowicz (UCSB) AUDIO SLIDES