Do data Center locations Correlate with regions of high energy prices?
Note: this project is currently ongoing. I’m tracking progress on this page, so stay tuned for updates.
As part of a wider effort to understand the energy costs of data centers, I’m creating a dashboard in R tracking energy usage and energy price trends. One key component of this project is data center location — namely, do data center locations correlate with regions that have higher energy usage and/or prices? I’m also exploring the media narrative around the topic, which will be woven into the final dashboard as a storytelling component.
01 Challenge: Visually capture the potential relationships between data centers, energy prices, and energy usage.
In the past year, data centers have become one of the latest hot-button topics entering the mainstream media sphere. They’re a top priority for Big Tech companies looking to support existing investments in artificial intelligence (AI), but they face pressure from advocacy groups, residents, and a growing number of politicians as they cite environmental impact issues and a growing concern over a lack of AI regulation. Data around data center locations in relation to energy usage and price is precarious, and I’m working to visually capture the potential relationships between them. This project is partly inspired by Business Insider’s extensive efforts to map US data centers.
02 Solution: a US Data Center and Energy Dashboard
The relationship between data centers and energy in the US is complex, so I proposed to capture various aspects of the relationship in a central dashboard. Using R and libraries including shiny, tidyverse, sf, tigris, dplyr, and leaflet, I’m currently building out a user-friendly, functional dashboard that enables viewers to interact with information and data related to data centers and energy in the US. Early iterations of the dashboard are below.
03 Process: Media audit, literature review, data exploration & analysis
Media audit of related key themes & topics
My initial research looking into key themes and topics discussed by the media has revealed the following as the most frequently covered aspects of data centers and energy in the US:
Artificial Intelligence (AI) literacy — programs, definitions, and fields of application
Data center energy use — proponents, concerns, regulation efforts
AI tools & applications — opponents, Big Tech promotion, lack of policy and regulation
Data center development — growth hot spots, resident opposition efforts, attempts to regulate
Literature review
My ongoing literature review includes a deeper dive into the above topics to better understand key players, trends, and regulations efforts. This section will be updated as I complete the review.
Data exploration & analysis
Primary sources of data include residential energy prices and industry energy usage from the US Energy Information Administration, as well as data center locations mapped by US state and county created by Business Insider. Exploratory analysis has included efforts to geocode the datasets in order to map them with the appropriate libraries and processes in R. Initial iterations of mapping in R are below.
04 Reflection & Findings
The relationship between data centers and energy in the US is complex, and I will continue to update this section as I continue my literature review and data analysis.
Library imports, summary of function sections, and documentation
INFO 696 Advanced Projects in Visualization
Professor Benjamin Zweig
Pratt Institute School of Information | Spring 2026