Colleen Rosales (Strategic Partnerships Director at OpenAQ and postdoc at UC Davis) describes using the Wolfram Language to organize, visualize, and model heterogeneous air quality data from instruments with differing sampling frequencies. She explains that rewriting a slow, previous analysis program in Wolfram improved processing and produced a shared GUI still used by her former lab.
Chapters
With Wolfram, the natural language is easier to bridge that gap between reprogramming language and the natural way of thinking. And so it allowed me to kind of combine my way of thinking into how a computer would think. I'm Colleen Rosales. I'm the Strategic partnerships director at OpenAQ. We are a nonprofit aimed to fight air inequality by open data. And I'm also a postdoctoral researcher at the Air Quality Research center at the University of California in Davis. For me, the Wolfram language is the way of thinking. And I learned programming through Wolfram, and it has allowed me to visualize data. It has allowed me to organize this disparate sources of data. So, for example, in my previous lab, we have different sources of data that come at different frequencies. For example, some are per second, some are per minute, and some come from instruments that are made within the lab. Some are manufactured by bigger labs. But the data that comes to us come in different forms. And so I needed a tool to have these data aligned and be able to be visualized and look for me to be able to look at the trends that these data have and for me to be able to do some modeling with them and whatnot. And so I think that is where Wolfram and the Wolfram language has really helped me, you know, organize this data, visualize, and also do some modeling with this data. So in my PhD, we did instrumentation. We built our own instruments to measure pollutants in the air. And in that sense, we didn't have a program built for us and for what it was previously, it was enough. But as I mentioned, the frequency of data that comes to us is increasing. And so the analysis time that it takes for us to be able to process that data becomes longer and longer. And so the previous program took about 30 minutes for one analysis, and so that was kind of long. And so I decided to rewrite the program in the Wolfram language and have a GUI for the program to be able to share that within the lab. And so until now, even if I left the lab already, they still use that to be able to process the data that the lab generates. I think for someone who doesn't know what the Wolfram language is, I'll say that this is a tool that allows you to think in many ways on how to approach your data or how to analyze your data in a way that is closer to how you would normally think about it in your head, if that makes sense. To me, it's not just a tool, but it's also a way of thinking.
