spatialComputing.html

TITLE:	From GPS, Google Maps & Uber to Spatial Computing 2020
PRESENTER:	Shashi Shekhar : Biography ( 100 words , 350 words ), Homepage , Picture
AFFILIATION:	Computer Science Department, University of Minnesota.
URL:	http://www.cs.umn.edu/~shekhar

VIDEOS:

Short (4-minute) overview for Spatial Computing , Communications of the ACM, 59(1), January, 2016 (With S. Feiner, and W. Aref).
youtube playlists for 2 current projects , spatial data mining , spatial querying , and spatial networks .
Coursera : This page provides a collection of videos organized into several modules. These videos are part of a Coursera course titled From GPS and Google Maps to Spatial Computing . Use a free Coursera account to access these videos.

SLIDES:

53-Slides (5Mb pdf) , Distinguished Lecture at The Information Science and Technology Center, Colorado State University, Fall 2015 ( news article ).
60-Slides (2.4Mb pdf) , Keynotes at Intl. Symposium on Spatiotemporal Computing (July 2015) , and IEEE Intl. Conference on Contemporary Computing (August 2015) .
43-Slides (2Mb pdf) , Keynote at Intl. Conf. on Geocomputation, 2015.
36-Slides (2Mb pdf) , NIST Data Science Symposium , March 2014.
( 40-Slides, 3Mb pdf ), USDOE Argonne National Laboratory Workshop on High Performance Computing and GeoSpatial Analytics, April 2014.
Spatial Computing Workshop Report Overview (with Spatial Big Data Issues) 39-Slides (pdf) (Nov. 2012),
Interdisciplinary Research and Spatial Computing: 1-slide (pdf) (March 2015), 26-Slides (pdf) (Jan. 2013),

ABSTRACT:

Since public availability of Global Positioning System in the 1990s, spatial computing has enriched billions of lives via pervasive services (e.g., Google Maps, Uber, geo-tagging, check-in), ubiquitous systems (e.g., geographical information system, spatial database management system), and pioneering scientific methods (e.g., spatial statistics). These accomplishment are just the tip of the iceberg and there is a strong potential for a compelling array of new breakthroughs such as Earth dashboards for continuous monitoring of environmental hazards, localization indoors and underground, accurate spatio-temporal predictive models, time-travel (and depth) in virtual globes, etc. For example, a McKinsey report projected an annual $600B saving from leveraging spatial big data (e.g., smart-phone trajectories) for novel eco-routing services to reduce wasted fuel, greenhouse gas emission and pollution exposure during unnecessary waits at traffic lights and in congestion.

However, many fundamental research questions need to be investigated to realize the transformative potential. For example, how may location-based services survive GPS-jamming (or spoofing)? How may spatial big data (e.g., smart-phone trajectories) be mined without violating privacy ? How can machine learning algorithms be generalized to address spatio-temporal challenges (e.g., auto-correlation, non-stationarity, heterogeneity, multi-scale), to scale up to spatial big data and to model geographic concepts (e.g., context, hot-spots, hot-features, doughnut-hole patterns)? How can eco-routing address the new challenges, e.g., waits at traffic-signals violate the sub-path optimality assumption in popular A* and Dijktra's algorithms?

This presentation shares a perspective on the societal accomplishments, opportunities, and research needs in spatial computing based on a recent community report following the Computing Community Consortium workshop titled From GPS and Virtual Globes to Spatial Computing -- 2020 held at the National Academies.

KEYWORDS: Spatial Computing, Geographic Information Systems, Spatial Databases, Spatial Data Mining.

ACKNOWLEDGMENTS: This work was supported in part by the National Science Foundation, the U.S. Department of Defense, and the University of Minnesota.

REFERENCES

Spatial Computing ( html , short video , tweet ), Comunications of the ACM, 59(1), January, 2016 (With S. Feinrer, and W. Aref).
From Google Earth and GPS to Spatial Computing - 2020: Community Report brochure and report ,2013.
National Academies Reports:
Identifying patterns in spatial information: a survey of methods ( pdf ), S. Shekhar, M. R. Evans, J. M. Kang and P. Mohan, Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery , 193-214, 1(3), May/June 2011. (DOI: 10.1002/widm.25).
S. Shekhar and H. Xiong (Co-EIC), Encyclopedia of GIS , Springer, 2008, isbn 978-0-387-30858-6.
S. Shekhar and J. Kang, Spatial Databases , Wiley Encyclopedia of Computer Science and Engineering (Ed. Benjamin Wah), John Wiley and Sons Inc, 2009, isbn 978-0471383932.
S. Shekhar and S. Chawla, Spatial Databases: A Tour , Prentice Hall 2003, ISBN 0-13-017480-7.
S Shekhar, S Chawla, S Ravada, A Fetterer, X Liu, and C Lu, Spatial Databases: Accomplishments and Research Needs ( pdf ), IEEE Transactions on Knowledge and Data Engineering, 11(1), Jan. 1999.
ACM Special Interest Group : SIGSPATIAL ,
GeoInformatica: An International Journal on Advances of Computer Science for Geographic Information Systems, Springer: Homepage .
Spatial Big-Data : A Perspective (abstract, slides, position papers).
Spatial Computing Perspective on Food Energy and Water Nexus , Journal of Environmental Sciences and Studies (Special Issue on FEW Nexus), ISSN: 2190-6483 (Print) 2190-6491 IOnline), Springer, 2016. (Note: It is a vision paper exploring possible roles for spatial computing in FEW Nexus).