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CyberGIS Summer School on Big Data Landscapes

Ready to supercharge your geospatial research? The CyberGIS Center is pleased to announce its Summer School on Big Data Landscapes. These workshops provide hands-on training with cutting-edge CyberGIS applications. Students, staff, and faculty are all welcome to attend, and light refreshments will be provided.

All workshops are held in NCSA room 1040.

CyberGIS-enabled Digital and Spatial Studies
An introduction to CyberGIS with hands-on experience with applications in the CyberGIS Gateway. This introduction places the rest of summer workshops into context, and includes time for participants to discuss how CyberGIS can enable their research projects.
Date: Thursday, July 16th
Time: 2:30 pm – 5:00 pm
Register by Wednesday, July 15th


Digital Terrain Analysis for Large, High-Resolution Landscapes
This course presents the theory of terrain analysis and introduces scalable capabilities to perform morphometric analysis on natural landscapes. The workshop focuses on cases where the input elevation data is detailed (e.g., LIDAR data) and the analysis is extended over a large area, which makes it impossible to perform on a conventional desktop GIS. This workshop is held over two afternoons.
Date: Thursday and Friday, July 23rd and 24th
Time: 2:30 pm – 5:00 pm
Register by Wednesday, July 22nd


Data Parallelism for Raster-Based Land Cover Analysis
This course is designed for researchers and practitioners interested in large scale landscape studies. With increased availability of fine-resolution regional and national land cover raster datasets, there comes the opportunity to study local land change dynamics across large regions. In this training, we introduce big-data-appropriate methods for conducting typical land cover analyses and simulations in a high performance computing environment. This course uses Python, but concepts can be applied using other programming languages.
Date: Thursday, July 30th
Time: 2:30 pm – 5:00 pm
Register by Wednesday, July 29th


Data Science with Python on Hadoop
This course is primarily designed for researchers who need to understand how to apply data science to large datasets with Hadoop. Data scientists commonly use various Python libraries to perform data analysis. However, Python algorithms that run perfectly fine in a single-machine environment cannot simply use Hadoop to scale on a cluster. We will learn how to run Python on a Hadoop cluster using two techniques: Pig user defined functions, and Pig stream command. In particular, this unit will demonstrate how to run a machine learning algorithm (e.g., K-means clustering) on a Hadoop cluster.
Date: Thursday, August 6th
Time: 2:30 pm – 5:00 pm
Register by Wednesday, August 5th


Interactive geo-visualization of large-scale movement data using Apache Spark
This course is designed for audiences interested in processing, analyzing and visualizing large-scale movement data using high performance computing platforms. In particular, we introduce Apache Spark to enable rapid and efficient data processing in an advanced computing cluster environment. Participants will learn programming with Apache Spark using Python for processing large-volume of geo-referenced movement datasets, and interactive visualization techniques for representing the results using D3.js, which is a JavaScript library for producing dynamic, interactive data visualizations in web browsers. This workshop is held over two afternoons.
Date: Thursday and Friday, August 13th and 14th
Time: 2:30 pm – 5:00 pm
Register by Wednesday, August 12th


To be notified of upcoming training and other events at the CyberGIS Center, sign up on our mailing list. These and other events are all on our calendar.


If the workshop you are interested in is already at capacity, please contact:
Johnathan Rush
Education, Outreach, and Training Coordinator
CyberGIS Center for Advanced Digital and Spatial Studies