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RIEEE EnviroData Collaborative

Description

The RIEEE EnviroData Collaborative (EDC) is designed to meet a growing need at Appalachian State University: building environmental data science and modeling capacity through hands-on skill building, shared learning, and collaborative exchange. As the pace of innovation in areas like machine learning, remote sensing, and cloud computing accelerates, researchers across disciplines are seeking opportunities to update and expand their technical skill sets to continue learning beyond graduate training.

Through periodic, skill-focused workshops led by both campus experts and invited facilitators, this program creates space for faculty and research staff to gain practical experience with new tools, exchange knowledge, and grow their capacity to conduct cutting-edge, data-intensive research. Beyond individual skills, the EDC will foster a culture of collaboration and interdisciplinary connection.

Objectives

  • Create space for faculty and research staff—regardless of discipline or career stage—to gain practical experience with new tools, exchange knowledge, and grow their capacity to conduct cutting-edge, data-intensive research
  • Offer structured time, community support, and accountability to help participants finally engage with that tool or technique they’ve been meaning to learn “when they have time”
  • Cultivate a vibrant, interdisciplinary community of Appalachian State faculty and research staff advancing environmental data science and modeling capacity

Upcoming Workshops

Coming soon!

When available, courses can be registered for at: course registration


Past Workshops

Feb 20, 2026: Causal Inference in R: An introduction

Instructor: Dennis Guignet, Associate Professor of Economics

Description: We have all heard the maxim “correlation does not imply causation”, but causation is often what environmental researchers seek to find. In this workshop we will explore tools to infer causal relationships in real-world data, using an example of environmental pollution and home values. The two-hour workshop will feature a presentation on necessary background material and then segue into an applied R-based example.

Nov 12, 2025: Supervised Machine Learning with R

Instructors: Hasthika Rupasinghe, Associate Professor of Mathematical Sciences; and Lasanthi Watagoda, Assistant Professor of Mathematical Sciences

Description: This hands-on workshop introduces participants to R Markdown as a tool for conducting and documenting data analysis in a single, reproducible environment. Participants will use RMarkdown throughout the session to write code, view results, and generate their own workshop notebook. We will then explore the fundamentals of supervised machine learning using R, focusing on regression models for continuous outcomes. The session will progress from basic linear regression to modern machine learning methods, including shrinkage approaches (LASSO, Elastic Net, AHRLR) and tree-based ensembles (Bagging, Random Forest, Boosting). By the end of the workshop, participants will understand how different modeling strategies balance interpretability, flexibility, and predictive accuracy.

Sep 23, 2025: Getting Hands-On with Data: Interactive visualizations in R

Instructors: Michael Erb, Research Scientist, RIEEE and Research Associate Professor of Geological and Environmental Sciences; and William Armstrong, Associate Professor of Geological and Environmental Sciences

Description: Interactive visualizations provide an engaging way of exploring large datasets and browsing data with peers and students. In this workshop, you’ll learn to process data in R and produce interactive figures using several R packages: tidyverse, plotly, and leaflet. We’ll focus on two main examples: an interactive 3D scatterplot of penguin data—which can be zoomed, rotated, and filtered—and an interactive map of North Carolina population. Other visualizations will be included throughout.


Contact

Want to get in touch about past and upcoming workshops? Use the form below for:

  • Questions and comments
  • Suggestions for future workshops (i.e., what would you like to learn?)
  • Volunteering to teach a workshop
  • Request to be added to the mailing list
  • Request access to past workshop materials

Note that EnviroData Collaborative workshops are aimed at App State faculty members.

Data

Project Team Members

Associate Professor

Research Scientist, Research Associate Professor

Grace Marasco-Plummer

Managing Director

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