International Love Data Week 2026 is February 9-13, 2026. The theme this year is Where’s the Data? The U-M scholars who have shared their data publicly are enthusiastically answering this question.
Deep Blue Data is a repository offered by the University of Michigan Library that provides access and preservation services for digital research data that were developed or used in the support of research activities at U-M.
In honor of Love Data Week, we reached out to some recent Deep Blue Data depositors to ask about the history of their work, unique discoveries they made along the way, and how they see their data being useful to their research communities and beyond.
We hope you enjoy learning more about the scholars behind the data sets. As a reminder, all data sets in Deep Blue Data are openly accessible for anyone to download and use, because we love data.
Dr. Jenna Stolzman is a recent PhD graduate in The Wooldridge Combustion Laboratory in the Mechanical Engineering department. The laboratory focuses on high-temperature chemically reacting systems relevant to power and propulsion generation and chemical processing, with the goal of enabling advancements in materials, fuel chemistry, and combustion device design. Jenna and their collaborators deposited their dataset “Dataset for: Effects of crosswind and shroud geometry on performance of low-flow, non-assisted flares.” As the name implies, this data supports their 2025 journal article entitled "Effects of crosswind and shroud geometry on performance of low-flow, nonassisted flares."
What prompted you to conduct your research in this area?
Flares in the oil and gas industry emit significantly more methane than is currently inventoried by the US Environmental Protection Agency, highlighting a critical gap in emissions mitigation. This motivated a Department of Energy ARPA-E-funded effort to investigate advanced, cost-effective flare technologies. The current research focuses on the design, fabrication, and experimental testing of novel flare technologies aimed at reducing methane emissions.
For those not familiar with your field, what is the one thing you think is most important about your work or your findings?
A key finding of this work is that a simple, low-cost retrofit to existing pipe flares can reduce methane emissions by up to 50%. Given that thousands of flares are currently operating across the United States, even modest improvements can have substantial environmental impact.
How do you hope your data might be encountered or reused out in the world?
This dataset can be used to validate computational models, develop new scaling relations or machine learning approaches for predicting flare efficiency, and support the advancement of best practices for methane emissions mitigation. More broadly, it enables researchers and industry stakeholders to better understand and improve flare performance under realistic operating conditions.
What is one thing you learned during the process of preparing your data for deposit or sharing?
I learned that preparing data for public sharing requires significantly more time and intentionality than preparing data for my own use. This helped me understand the importance of organizing data early to support long-term usability.
Why do you think sharing data is important?
Sharing data is especially important in the field of flares, where publicly available datasets are limited. By making this dataset accessible, it can help advance understanding, support model development, and enable the broader research community to improve methane emissions mitigation strategies.