The lab conducts many studies on the same population of monkeys and collects all of their data in Excel Worksheets. This works well for analyzing individual studies, but they needed a system for tracking subjects across multiple studies to compare their performance at different tasks. To help with this we created a database with a custom R library for adding and accessing census and study data. For lab members that are not familiar with R, or just want to quickly browse the data we created a website using R-Shiny.

The researchers had created a Qualtrics survey to probe the participant’s voting preferences. However, the way this information needed to be displayed and the data the researcher needed to collect was not possible in a standard survey. The Research Software Programming team was able to help create a custom information environment embedded in the Qualtrics survey using Javascript and custom HTML.

The lab needed a way to track color changes in a selected area, and was also interested in prototyping a wearable device that could handle the same task. They explored existing apps, and could not find anything that would meet their needs, so we created a small, custom iPhone app to handle their data collection.

The lab wanted to run experiments that involved taking spectroscopy measurements at a large number of intervals of movement of a delay line stage. This required running separate control programs for the spectroscope and the delay line, with a lab worker manually tending the experiment the entire time to trigger each delay line stage move and subsequent spectroscope measurement, an extremely tedious and time-consuming process. The Research Software Programming team developed a program to control both pieces of equipment, automating this experimental process. The program allows extensive configuration of the experiment parameters, as well as the analysis and display of the results, all in a single piece of software.

The lab needed data to refine and test their Circadian Rhythms Models, so our group created iPhone and Android apps that allowed users to donate their heart rate and step data and get an analysis back from the lab in return. The smartphone sends data to a server/database, and it is processed by multiple algorithms, some of which generate reports for the users.