Research Like a Software Engineer - Organizing Your Projects Like Applications

Conducting research for data science research often involves handling a variety of data sources and analysis methods that can quickly become quite complex. The desire to easily share and reproduce this research adds to this complexity. This is where using the same tools and methodologies from software engineering can help.

In this workshop, Travis will share his experience of being both a software engineer and a social science researcher. By building an example project using Python and PostgreSQL, we'll go over the following items:

• Building a research application by creating our very own CLI tool
• Designing a PostgreSQL database to power our research application
• Using tools like QGIS and pgAdmin to read from our database for exploratory data analysis
• Enabling reproducibility by packaging and sharing our software

To illustrate how all of this comes together, we walk through an example project where we research travel times to parks within the city of Berlin. We'll use data from the 2022 German Census and OpenStreetMap as the basis for the study. The tutorial will focus on how to import and organize this data into our database as well as adding new tables for measuring travel times. At the end, we'll package everything up and share it with the world.

Prior to the tutorial, please ensure you have git (https://git-scm.com/) and the pixi package manager (https://prefix.dev/) installed on your computer.

Travis currently works as a software engineer where he works on the conda package manager. But before that, he completed two degrees in the field of social science which gives him a unique perspective on both fields. In this workshop, Travis wants to share these unique experiences with you and share how you can better organize your research applications.