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
Please note that EnviroData Collaborative workshops are designed for Appalachian State faculty and staff attendees.
Upcoming Workshops
Web Mapping – Wednesday, September 16, 2026, 12 to 2 p.m.
Instructor: Dr. Johnathan Sugg, Associate Professor, Cartography & GIS; Web Mapping; Climatology; Environmental Communication & Perception in the Department of Geography and Planning
Location: Anne Belk Hall, Room 222 (CETLSS Classroom)
Description:
Web mapping technology has evolved faster than the communication theory needed to understand it. Today’s cartographers, researchers, or anyone making a map must balance traditional cartographic workflows with user interface/user experience design and modern web development. In this workshop, we will demystify this process by exploring the design and development of interactive, user-focused maps on the open web. Participants will use Leaflet, HTML, CSS, and JS to build a web-based mapping application, concluding with a published project on GitHub that serves as a foundation for your own environmental, energy, or economic data visualizations.
Through this workshop, you will:
- Understand map communication theory and user-centered design as it relates to interactive web map technologies.
- Work with spatial data in the open web format.
- Get familiar with Leaflet, HTML, CSS, JS, and GitHub for developing web maps.
- Build and publish a shareable web map with custom symbology and interactions.
The Web Mapping workshop is designed for faculty and staff. Participants should bring their own laptops with Visual Studio Code for Windows or Mac pre-installed and also signup for a free GitHub account.
Data Insights for Everyone: Sharing your findings with broad audiences – Tuesday, November 3, 2026, 12 to 2 p.m.
Instructor: Dr. Chris Quattro, Assistant Professor, Regulatory Law; City & Regional Planning; Environmental Planning, Department of Geography and Planning
Location: Anne Belk Hall, Room 222 (CETLSS Classroom)
Additional details and a registration link for the Data Insights workshop will be shared soon.
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
