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

Data deluge

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: http://en.wikipedia.org/wiki/Big_data

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): 149-174.

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

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

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

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