For the past several years, a collaborative effort has been underway to further understand Seneca Lake through the use of measuring instruments placed in the lake. The instruments measure a significant amount and variety of forms of data, such as meteorological conditions, water profiles, sedimentary data, and even data on zooplankton. Researchers found themselves awash in new data, but given the extent of that data, an effective means of organizing it was critical to their ability to analyze it. Max Beckett ’11, a senior computer science major, spent the summer developing a new visual modeling program that would efficiently present numerous variables simultaneously – in a manner easy to understand.
Three years ago, Assistant Professor of Biology Meghan Brown, Associate Professor of Geoscience Neil Laird, and Assistant Professor of Geoscience Tara Curtin began conceiving of the collaborative interdisciplinary project. A National Science Foundation grant helped secure the research instruments and the team gained the help of Associate Professor of Mathematics and Computer Science Stina Bridgeman to create www.fli-data.hws.edu, so researchers could access data on the conditions of Seneca Lake and compare variables.
Bridgeman recruited Beckett after he took her Data Visualization seminar. He spent the majority of the summer in Geneva creating and coding the visual modeling program in Java. The finished product essentially turns dozens of variables and their respective values from pages of jumbled numbers on an Excel worksheet to a cohesive system of graphing and data visualization.
Bridgeman allowed Beckett a large amount of leeway in his creative and programming decisions, granting him not only a sense of control and flexibility, but of responsibility.
“It was an interesting challenge being in charge of my own project-even frightening at times,” explains Beckett.
He notes Bridgeman’s knowledge and experience were crucial in conversations and for inspiration as to how to proceed with the project, the difficulty level of which was quite high. The data being retrieved from Seneca Lake has an amount of variables so extensive that it is impossible for someone to comprehend the number of dimensions were it to be put in a simple graph. Beckett, then, had to develop a way in which he could visually depict such a large amount of variables so they would be comprehensible.
The program is now complete, for the time being, as Bridgeman and Beckett await feedback from the other participants in the project.