Making data pipelines with R: How to automate downloading and processing data from web APIs

Hosted by: Shannon Albeke, WyGISC – University of Wyoming

Email: salbeke@uwyo.edu

Duration: 4 hours

Overview

Being a Spatial Data Scientist means needing many skills and tools to accomplish tasks accurately and efficiently in our brave new world of open data and digital data repositories. Obtaining data from various sources seamlessly, massaging it into needed formats and structures, processing it into derived metrics, and visualizing or modeling the data are essential skills. These skills, coupled with the integration of statistical approaches and spatial analyses, can be powerful tools for informing management decisions at broad spatial scales. In this workshop, I will present an opportunity to gain additional skills using open-source software, coupled with open data API’s, that I have found highly useful for our daily activities. Topics will include reading in geometry layers from web services, obtaining tabular data from an API (translating JSON to data.frame), downloading and processing raster datasets, and more! Software installation instructions and all data needed will be provided, with students expected to have the requisite software installed prior to the course. No prior experience with R is required, but if you do have experience using R, it will be quite useful!

About the speaker

Dr. Shannon Albeke is a Senior Research Scientist and GIST Faculty member. He holds a Bachelor of Arts degree in Environmental Sciences, with minors in Biology and Geography in 1997 from the University of Colorado – Boulder. After graduation, he began an 8-year career as an Aquatic Habitat Biologist for the Colorado Division of Wildlife and by necessity learned how to be a GeoSpatial Data Scientist. Dr. Albeke received his PhD from the University of Georgia – Warnell School of Forestry and Natural Resources in 2010 as well as becoming a member of WyGISC. Dr. Albeke’s general research interests center around applied GIS, programming, and statistics.

Additional information

Students will want to install R and R Studio, plus additional packages prior to the course.


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