Cartographic Modeling Language Approach for CyberGIS : A Demonstration with Flux Footprint Modeling
A CyberGIS Environment for Near-Real-Time Spatial Analysis of Social Media Data
description
Transcript of A CyberGIS Environment for Near-Real-Time Spatial Analysis of Social Media Data
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?
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
16
Long Tail – CyberGIS for Whom?
CyberGIS Gateway
CyberGIS Toolkit
GISolve
17
GISolve Middleware
18
Integration Framework
19
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
21
CyberGIS Toolkit – Deep Approach
22
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
23
Cyber + GIS > Cyber | GIS
24
Cyber
GIS
Education and Workforce
• Curriculum and pedagogy• Open ecosystems
o CyberGIS Gateway o CyberGIS Toolkit
• Partnerships
25
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
27
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)
28
Acknowledgments – CIGI
29