A CyberGIS Environment for Near-Real-Time Spatial - PowerPoint Presentation

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A CyberGIS Environment for Near-Real-Time Spatial - PPT Presentation

Analysis of Social Media Data Shaowen Wang CyberInfrastructure and Geospatial Information Laboratory CIGI Department of Geography and Geographic Information Science Department of Computer Science ID: 810953

data cybergis integration spatial cybergis data spatial integration information analysis science cyberinfrastructure spatiotemporal computing gis applications advanced department gateway

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Slide1

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

Slide2

Cyberinfrastructure – A Simplified View

Data / Information

Computing

Communication

People

Integration

Collaboration

Slide3

Advanced Cyberinfrastructure Examples

www.opensciencegrid.org

www.xsede.org

http://lakjeewa.blogspot.com/2011/09/what-is-cloud-computing.html

Slide4

CyberGIS – A Tetrahedron View

Data / Information

Computing

Communication

Geo

Spatial CyberGIS

Slide5

What is special about “G” in CyberGIS? LocationPlaceSpace SpatiotemporalIntegration Synthesis

Slide6

Slide7

CyberGIS FluMapperPurpose: Early and fine- spatiotemporal-scale detection of flu outbreakHypothesis: Is such detection feasible based on social media data?

Slide8

Demo

Slide9

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

Slide10

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

Slide11

FluMapper ComponentsData collection and processingCollects, 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 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 simulationsFlow mapping Single-source flow mapping is applied to depict movement patterns

Slide12

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

Slide13

A 2D Illustrative Example

Slide14

Questions – 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?

Slide15

NSF CyberGIS Project$4.43 million, Year: 2010-1015

Principal Investigator

Shaowen Wang

Project Staff

ASU

: Wenwen Li and Rob Pahle

ORNL: Ranga Raju VatsavaiSDSC: Choonhan YounUIUC: Yan Liu and Anand PadmanabhanGraduate and undergraduate students

Industrial 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

Slide16

Overarching 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

Slide17

Long Tail – CyberGIS for Whom?

CyberGIS Gateway

CyberGIS Toolkit

GISolve

Slide18

GISolve Middleware

Slide19

Integration Framework19

Slide20

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.

Slide21

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

Slide22

CyberGIS Toolkit – Deep Approach22

Integrated with

advanced cyberinfrastructure

Plug and play

Geo/spatial as an integration axis

Open

Access

Community

Source

Service

Slide23

Science Drivers and ApplicationsClimate scienceEmergency managementGeographic information scienceGeography and spatial sciencesHydrologyHumanities Political sciencePublic healthSustainability science

Slide24

Cyber + GIS > Cyber | GIS24

Cyber

GIS

Slide25

Education and WorkforceCurriculum and pedagogyOpen ecosystemsCyberGIS Gateway CyberGIS ToolkitPartnerships

Slide26

Vision

Spatial

Thinking

Computational

Thinking