Photos of Lauren Kuntz and Stuart Ian Graham

Reflections on the 2019 Winter Incubator program

April 24, 2019

With the results of our 2019 Winter Incubator program in, we offered participants the opportunity to weigh in on their experiences in this data science- intensive 10-week program. Two of them responded; here are their thoughts.


Stuart Ian Graham, UW Biology Department

A photo of Stuart Ian Graham
Stuart Ian Graham

I had the invaluable experience of working with Dr. Ariel Rokem in the 2019 Winter Incubator Program. I am a third year Ph.D. student in Biology and applied to the Incubator Program because I didn’t know where to begin on the data-intensive second chapter of my dissertation. Through Dr. Rokem’s patient and thoughtful mentoring, I was able to not only make considerable progress on this project but also develop data management skills that have already helped me with other ongoing projects.

The project I brought to the Winter Incubator aimed to build a model to predict tree growth from the species identities and sizes of neighboring trees. A number of research papers had already addressed this question using other datasets but I was struggling to understand and apply their methods to my own data. Over the course of the Incubator, I was reassured to learn that my confusion regarding these methods was warranted, as they were complex and their descriptions often left out some important details. In response to this, Dr. Rokem and I developed a new, more intuitive method to answer this question. I now intend to focus my dissertation chapter on this new approach to predicting tree growth, specifically by creating an R package that will allow other researchers to implement our new method.

An additional benefit of participating in the Incubator Program was the weekly meetings where all the Incubator project leads and e-Science liaisons gave progress updates. It was really interesting to view these projects from very different fields through the lens of data science, and thereby realize that they, in fact, had many commonalities. I am sure this experience will help me to see links between research questions that used to seem entirely unrelated and help me to envisage more interdisciplinary projects in the future. I am excited to continue building my data science skills and expect to visit the eScience studio regularly.


By Lauren Kuntz, UW Department of Oceanography

Lauren Kuntz, photo by Gulnara Niaz
Lauren Kuntz, photo by Gulnara Niaz

The amount of climate science data is truly overwhelming – from model simulations and reanalysis products to observations from satellites and ocean floats, we are dramatically expanding the volume of data to analyze, interpret, and understand. As a postdoctoral researcher in climate science, I have always been curious as to the best strategies to employ to help gain meaning out of all the data available.

The Incubator program increased my exposure not only to methodologies but also to resources to help handle the challenges of working with large datasets. For my project, I focused on satellite observations of latent heat profiles, trying to understand the main modes through which precipitation releases energy to the atmosphere. Before the Incubator, I would have been too daunted by the volume of data to take it on – with 16 years of satellite observations providing on the order of TB of data – but with the help of the eScience community, I developed the knowledge I needed to enable me to process it all.

The weekly meetings with the entire Incubator program also expanded my knowledge of the methods that exist in other fields of research. Having been exposed to new ways of working with data, I’ve expanded my own thinking of the questions within climate science I can ask. It’s amazing to realize all the research topics you can explore, once you have a deeper understanding of the tools available.


You can watch the presentations of our Winter Incubator projects on YouTube: