A CyberGIS Environment for Near-Real-Time Spatial Analysis of Social Media Data Shaowen Wang CyberInfrastructure and Geospatial Information Laboratory (CIGI) Department of Geography and Geographic Information Science Department of Computer Science Department of Urban and Regional Planning National Center for Supercomputing Applications (NCSA) University of Illinois at Urbana-Champaign NSF-CDI Specialist Meeting Knowledge Discovery in Cyberspace and Big Data San Diego, CA August 7, 2013

Cyberinfrastructure – A Simplified View Data / Information People Integration Collaboration Computing Communication

Advanced Cyberinfrastructure Examples http://lakjeewa.blogspot.com/2011/09/what-is-cloud-computing.html www.opensciencegrid.org www.xsede.org

CyberGIS – A Tetrahedron View Data / Information Geo Spatial CyberGIS Computing Communication

What is special about “G” in CyberGIS? Location Place Space Spatiotemporal Integration Synthesis

Hypothesis: Is such detection feasible based on social media data? CyberGIS FluMapper Purpose: Early and fine- spatiotemporal-scale detection of flu outbreak Hypothesis: Is such detection feasible based on social media data?

Demo

Questions – Scientific Problem Solving How to detect, represent, and communicate spatiotemporal patterns of flu risk? How to reveal spatial diffusion trajectories across various spatiotemporal scales?

Wang, S. , Cao, G. , Zhang, Z. , Zhao, Y. , and Padmanabhan, A. 2012 Wang, S., Cao, G., Zhang, Z., Zhao, Y., and Padmanabhan, A. 2012. “A CyberGIS Environment for Analysis of Location-Based Social Media Data.” In: Location-Based Computing and Services, 2nd Edition, ed. A. K. Hassan and H. Amin, CRC Press, pages: 187-205

FluMapper Components Data collection and processing Collects, processes and stores streaming data from Twitter in near real time Scalable services to query raw and derived data Spatiotemporal data model Provides aggregated data and statistics at multiple scales for efficient information retrieval At the finest scale, the conterminous United States is represented as a field of 30-arc second resolution Exploratory data analysis Kernel density estimation (KDE) Monte-Carlo simulations Flow mapping Single-source flow mapping is applied to depict movement patterns

Spatiotemporal Data Cube (May 23 ~ June 5, 2013)

A 2D Illustrative Example

Questions – CyberGIS How to model and analyze big data that are not collected for the purpose of intended spatiotemporal analysis? How to integrate hybrid spatiotemporal analyses? How to replicate and validate such analyses? What are the key CyberGIS characteristics? What are the basic building blocks of CyberGIS?

NSF CyberGIS Project $4.43 million, Year: 2010-1015 Principal Investigator Shaowen Wang Project Staff ASU: Wenwen Li and Rob Pahle ORNL: Ranga Raju Vatsavai SDSC: Choonhan Youn UIUC: Yan Liu and Anand Padmanabhan Graduate and undergraduate students Co-Principal Investigators Luc Anselin Budhendra Bhaduri Timothy Nyerges Nancy Wilkins-Diehr Senior Personnel Michael Goodchild Sergio Rey Xuan Shi Marc Snir E. Lynn Usery Industrial Partner: Esri Steve Kopp

Overarching Goal Establish CyberGIS as a fundamentally new software framework comprising a seamless integration of advanced cyberinfrastructure, GIS, and spatial analysis and modeling capabilities and, thus, leads to widespread scientific breakthroughs and broad societal impacts

Long Tail – CyberGIS for Whom? CyberGIS Gateway CyberGIS Toolkit GISolve

GISolve Middleware

Integration Framework

Wang, S. , Anselin, L. , Bhaduri, B. , Crosby, C. , Goodchild, M. F Wang, S., Anselin, L., Bhaduri, B., Crosby, C., Goodchild, M. F., Liu, Y., and Nyerges, T. L. “CyberGIS Software: A Synthetic Review and Integration Roadmap.” International Journal of Geographical Information Science, DOI:10.1080/13658816.2013.776049.

CyberGIS Gateway – Broad Approach – Lowering Entry Door to CyberGIS Analytics

CyberGIS Toolkit – Deep Approach Integrated with advanced cyberinfrastructure Plug and play Geo/spatial as an integration axis Open Access Community Source Service

Science Drivers and Applications Climate science Emergency management Geographic information science Geography and spatial sciences Hydrology Humanities Political science Public health Sustainability science

Cyber + GIS > Cyber | GIS

Education and Workforce Curriculum and pedagogy Open ecosystems CyberGIS Gateway CyberGIS Toolkit Partnerships

Data-Intensive Sciences and Applications Vision Data-Intensive Sciences and Applications Computational Thinking Spatial Thinking CyberGIS Gateway CyberGIS Toolkit Space-Time Integration & Synthesis GISolve Middleware Cyberinfrastructure

www.cybergis.org A collaborative software framework encompassing many research fields Geo Spatial Empowering numerous applications and sciences Seamless integration of advanced cyberinfrastructure, GIS, and spatial analysis and modeling Capable of handling huge volumes of data, complex analysis and visualization required for many challenging applications Empower high-performance and collaborative geospatial problem solving Gain fundamental understanding of scalable and sustainable CyberGIS ecosystems 27

Acknowledgments Federal Agencies Industry Department of Energy’s Office of Science National Science Foundation BCS-0846655 EAR-1239603 OCI-1047916 PHY-0621704 PHY-1148698 TeraGrid/XSEDE SES070004 Industry Environmental Systems Research Institute (Esri) Silicon Graphics, Inc. (SGI) 28

Acknowledgments – CIGI 29

Thanks! Comments/Questions? shaowen@illinois.edu