Cyberinfrastructure and CyberGIS: Recent Advances and Key Themes
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1 Cyberinfrastructure and CyberGIS: Recent Advances and Key Themes Shaowen Wang CyberInfrastructure and Geospatial Information Laboratory (CIGI) Department of Geography Department of Computer Science National Center for Supercomputing Applications (NCSA) University of Illinois at Urbana-Champaign Geospatial Frontiers in Health and Social Environments Symposium on Enabling a National Geospatial Cyberinfrastructure for Health Research July 27,
2 Cyberinfrastructure (CI) Atkins et al. (2003) 2
3 3
4 CI A Simplified View Data / Information Computing Communication 4
5 CyberGIS A Tetrahedron View Data / Information Computing Communication 5
6 Cyber + GIS > Cyber GIS Cyber GIS 6
7 7
8 CyberGIS Challenges/Opportunities Spatiotemporal data Digital environments Computing Communication Information Application and user interfaces Geospatial sciences and technologies 8
9 Spatiotemporal Data Dynamic and continuous E.g. sensor networks Heterogeneous Interoperability Syntactic Semantic Large-scale and fine granularity Global coverage Individual-levellevel High-resolution Massive Produced by individuals Accessible to individuals Distributed access Interoperability Privacy Security 9
10 The Great Flood Cox et al. (2011) 10
11 Image source: 11
12 12
13 Empowering USGS Map Re-projection Services Raster size: 388,888 x 19,446 13
14 Desirable Application and User Interfaces Not have to be comprehensive User-centric Application-driven Intuitive Make spatial sense Customizable Adaptive 14
15 15
16 16
17 Digital Environments Heterogeneous architecture Parallel Used to be regarded as a way for speeding up GIS functions and spatial analysis Now becoming a must for GIS and spatial analysis to be built on Multi- and many-core GPU (graphics processing unit) Extreme-scale computing Distributed Service-oriented Clouds 17
18 Blue Waters Supercomputer Usable storage bandwidth: Aggregate system memory: Usable storage: Peak performance: >1 TB/s >1.5 PB >25 PB >11.5 PF Number of AMD x86 cores: >380,000 Number of NVIDIA GPUs: >3,000 External network bandwidth: 100 Gb/s scaling to 300 Gb/s 18
19 Geospatial Sciences and Technologies Patterns (maps) > processes (simulations) Spatial -> spatiotemporal 19
20 CyberGIS Analytics Driven by massive spatial data and informed by computational science Search and optimization Simulation Spatiotemporal analytics Visual analytics 20
21 21 NSF SI2: CyberGIS Project: 5-year, $4.4-million Principal Investigators Shaowen Wang PI Luc Anselin Co-PI Budhendra Bhaduri Co-PI Timothy Nyerges Co-PI Nancy Wilkins-Diehr Co-PI Industrial Partner: ESRI Steve Kopp Senior Personnel Michael Goodchild Sergio Rey Xuan Shi Marc Snir E. Lynn Usery Project Staff ASU: Rob Pahle ORNL: Ranga Raju Vatsavai SDSC: Christopher Crosby and Choonhan Youn UCGIS UIUC: Yan Liu and Anand Padmanabhan Graduate and undergraduate students 21
22 International Partners Australia Victorian Partnership for Advanced Computing (VPAC) China Computer Network Information Center of the Chinese Academy of Sciences United Kingdom UCL Centre for Advanced Spatial Analysis (CASA) 22
23 Current Research Foci Application interface and integration Spatial computational theories and methods Architecture and design Integration between information and computation systems Parallel and distributed computing methods and tools for scalable GIS and spatial analysis Balance between software engineering with fundamental research Access Individual user and scientist Community and organization Equality, privacy, security 23
24 Science Drivers and Applications Emergency management Forecasting large-scale human behavior Early detection of infectious diseases Political l redistricting i ti Spatiotemporal data analytics 24
25 GISolve Middleware 25
26 CyberGIS Processes (Wang 2010) Image source: 26
27 Experimentation CyberGIS GISolve p 2011/09/what-is-cloudcomputing.html 27
28 Cyber + GIS > Cyber GIS Cyber GIS 28
29 Spatial Computational Theories / Methods Synthesize spatial and computational thinking Computational Complexity vs. intensity Uncertainty vs. validity Performance vs. reliability Spatial Distribution Dependence Integration Representation Uncertainty SC ALE 29
30 Education and Workforce Curriculum & pedagogy Open ecosystems CyberGIS Gateway CyberGIS Toolkit Partnerships 30
31 Vision Applications Space-Time Analytics High-Performance, Distributed and Collaborative GIS Base Cyberinfrastructure Multidi sciplinary Interact tions Emergency Management, Energy, Health, Sustainability Spatial Computational Theories / Methods GISolve Extreme-scale Computing, Open Science Grid, XSEDE
32 32
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34 34
35 Computing is not about computers any more. It is about living. Nicholas Negroponte, Founding Director of MIT s Media Lab. Being Digital (1995), p. 6. CyberGIS are not about infrastructure and systems any more. They are about transforming research and education in humanities, engineering, and sciences. By helping gain better understanding about locations; and spatial contexts, relationships, and dynamics in a complex and rapidly changing world. 35
36 Acknowledgments National Science Foundation BCS OCI OCI PHY TeraGrid/XSEDE SES U.S.. Geological Survey 36
37 Thanks! Comments / Questions? 37
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