Presentation on theme: "A CyberGIS Environment for Near-Real-Time Spatial Analysis of Social Media Data Shaowen Wang CyberInfrastructure and Geospatial Information Laboratory."— Presentation transcript:
1A 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 ScienceDepartment of Computer ScienceDepartment of Urban and Regional PlanningNational Center for Supercomputing Applications (NCSA)University of Illinois at Urbana-ChampaignNSF-CDI Specialist MeetingKnowledge Discovery in Cyberspace and Big DataSan Diego, CAAugust 7, 2013
2Cyberinfrastructure – A Simplified View Data / InformationPeopleIntegrationCollaborationComputingCommunication
7Hypothesis: Is such detection feasible based on social media data? CyberGIS FluMapperPurpose: Early and fine- spatiotemporal-scale detection of flu outbreakHypothesis: Is such detection feasible based on social media data?
9Questions – Scientific Problem Solving How to detect, represent, and communicate spatiotemporal patterns of flu risk?How to reveal spatial diffusion trajectories across various spatiotemporal scales?
10Wang, S. , Cao, G. , Zhang, Z. , Zhao, Y. , and Padmanabhan, A. 2012 Wang, S., Cao, G., Zhang, Z., Zhao, Y., and Padmanabhan, A “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:
11FluMapper Components Data collection and processing Collects, processes and stores streaming data from Twitter in near real timeScalable services to query raw and derived dataSpatiotemporal data modelProvides aggregated data and statistics at multiple scales for efficient information retrievalAt the finest scale, the conterminous United States is represented as a field of 30-arc second resolutionExploratory data analysisKernel density estimation (KDE)Monte-Carlo simulationsFlow mappingSingle-source flow mapping is applied to depict movement patterns
12Spatiotemporal Data Cube (May 23 ~ June 5, 2013)
14Questions – CyberGISHow 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?
15NSF CyberGIS Project $4.43 million, Year: 2010-1015 Principal InvestigatorShaowen WangProject StaffASU: Wenwen Li and Rob PahleORNL: Ranga Raju VatsavaiSDSC: Choonhan YounUIUC: Yan Liu and Anand PadmanabhanGraduate and undergraduate studentsCo-Principal InvestigatorsLuc AnselinBudhendra BhaduriTimothy NyergesNancy Wilkins-DiehrSenior PersonnelMichael GoodchildSergio ReyXuan ShiMarc SnirE. Lynn UseryIndustrial Partner: EsriSteve Kopp
16Overarching GoalEstablish 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
17Long Tail – CyberGIS for Whom? CyberGIS GatewayCyberGIS ToolkitGISolve
20Wang, 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: /
21CyberGIS Gateway – Broad Approach – Lowering Entry Door to CyberGIS Analytics
22CyberGIS Toolkit – Deep Approach Integrated with advanced cyberinfrastructurePlug and playGeo/spatial as an integration axisOpenAccessCommunitySourceService
23Science Drivers and Applications Climate scienceEmergency managementGeographic information scienceGeography and spatial sciencesHydrologyHumanitiesPolitical sciencePublic healthSustainability science
25Education and Workforce Curriculum and pedagogyOpen ecosystemsCyberGIS GatewayCyberGIS ToolkitPartnerships
26Data-Intensive Sciences and Applications VisionData-Intensive Sciences and ApplicationsComputationalThinkingSpatialThinkingCyberGIS GatewayCyberGIS ToolkitSpace-Time Integration & SynthesisGISolve MiddlewareCyberinfrastructure
27A collaborative software framework encompassing many research fieldsGeoSpatialEmpowering numerous applications and sciencesSeamless integration of advanced cyberinfrastructure, GIS, and spatial analysis and modelingCapable of handling huge volumes of data, complex analysis and visualization required for many challenging applicationsEmpower high-performance and collaborative geospatial problem solvingGain fundamental understanding of scalable and sustainable CyberGIS ecosystems27
28Acknowledgments Federal Agencies Industry Department of Energy’s Office of ScienceNational Science FoundationBCSEAROCIPHYPHYTeraGrid/XSEDE SES070004IndustryEnvironmental Systems Research Institute (Esri)Silicon Graphics, Inc. (SGI)28