1. Eric Shook Department of Geography Kent State University
Spatial Big Data
Eric Shook
Department of Geography
Kent State University

2. Data deluge

3. Big Data: The V's
Big data is a huge buzz word in both academia and industry
Big data are described within the context of the "3 V's"
Volume – The size of data generally referring to large quantities
Variety – Lots of different kinds of data
Velocity – The speed at which data is generated, processed, or otherwise "consumed"
Others have added V's to the discussion
Veracity – Quality of data being captured can vary
Variability – Data inconsistencies and changes challenging analysis
Value – What do you get out of all the data
More information:

4. Spatial Big Data
Spatial big data are spatial data that challenge current computing systems in terms of management, processing, or analysis
Perhaps more specifically, spatial big data are spatial data that exhibit at least one of the 3 V's: volume, variety, or velocity
GIScience is increasingly challenged by spatial big data
Technological advances (Lidar and Satellite imagery)
Volunteered Geographic Information (VGI) (OpenStreetMap)
GPS
Geo-enabled Social Media (Twitter, Flickr, ...)
Evans, Michael R., et al. "Spatial Big Data." Big Data: Techniques and Technologies in Geoinformatics (2014):

5. Spatial Big Data: Volume
Lidar-based Hillshade of Kent, Ohio calculated using PCML

6. Spatial Big Data: Variety
The measurement is ...
Polyline
Trajectory or lifeline
Raster
Landscape feature values
Volunteered Geographic Information
Citizen Science
Point
Feature locations
Network
Roads or streams
Polygon
State or county
boundaries

7. Spatial Big Data: Velocity
1 Twitter user? No
Hundreds of Twitter users? No
Millions of Twitter users!
500 million
Tweets per day
20.8 million
Tweets per hour
5,787 Tweets
per second

8. Challenges of Spatial Big Data
Database design
to handle variety of data
as well as volume (storage)
and velocity (reading/writing speed)
Algorithms and Methods
3 V's challenge traditional algorithms and methods to help make sense of all the data
Spatial
Database
Computational
Components
GIS
Big Data Storage
Analysis
Web Portal
Middleware
Geovisualization
Visualizing all this variety data quickly is challenging
Web
...
Network limitations
to transfer data
with large volume
or rapid velocity
Devices
Web Services
Supercomputers
Computational Systems
Desktop PCs often cannot handle large volumes of data or data with rapid velocity
Spatial Data
Infrastructures
Social
Networking
Geo-enabled
Social Media
Web Mapping