A CyberGIS Environment for Near-Real-Time Spatial Analysis of Social Media Data

Shaowen WangCyberInfrastructure and Geospatial Information Laboratory (CIGI)Department of Geography and Geographic Information Science

Department of Computer ScienceDepartment 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, CAAugust 7, 2013

Cyberinfrastructure – A Simplified View

Data / Information

Computing Communication

People Integration

Collaboration

Advanced Cyberinfrastructure Examples

www.opensciencegrid.org www.xsede.org http://lakjeewa.blogspot.com/

2011/09/what-is-cloud-computing.html

CyberGIS – A Tetrahedron View

Data / Information

Computing Communication

Geo Spatial

CyberGIS

What is special about “G” in CyberGIS?

• Location• Place• Space • Spatiotemporal

o Integration o Synthesis

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. “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

o Collects, processes and stores streaming data from Twitter in near real time

o Scalable services to query raw and derived data• Spatiotemporal data model

o Provides aggregated data and statistics at multiple scales for efficient information retrieval

o At the finest scale, the conterminous United States is represented as a field of 30-arc second resolution

• Exploratory data analysiso Kernel density estimation (KDE)o Monte-Carlo simulations

• Flow mapping o Single-source flow mapping is applied to depict movement patterns

(May 23 ~ June 5, 2013)

Spatiotemporal Data Cube

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

studentsIndustrial Partner: Esri

– Steve Kopp

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

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

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Long Tail – CyberGIS for Whom?

CyberGIS Gateway

CyberGIS Toolkit

GISolve

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GISolve Middleware

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Integration Framework

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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

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CyberGIS Toolkit – Deep Approach

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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

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Cyber + GIS > Cyber | GIS

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Cyber

GIS

Education and Workforce

• Curriculum and pedagogy• Open ecosystems

o CyberGIS Gateway o CyberGIS Toolkit

• Partnerships

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Vision

Spatial

ThinkingCom

putat

ional

Thinking

Cyberinfrastructure

Data-Intensive Sciences and Applications

CyberGIS Gateway

CyberGIS Toolkit

Space-Time Integration & Synthesis

GISolve Middleware

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

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Acknowledgments Federal Agencies

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)

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Acknowledgments – CIGI

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Thanks!

• Comments/Questions?

• shaowen@illinois.edu