Replicability and reproducibility of data-intensive design research using workflows - example in facial expression synchrony as a measure of empathy

Workflows are a standard and a crucial part of data-intensive research. They are iterative processes that support replicability and reproducibility by organising problem-solving tasks into well-documented sequential steps. Given the emergence of data-intensive design research, there is a need to adapt these practices in design research to help increase the transparency and, thus, quality of research. We present a step-by-step guide to applying a data analysis workflow in design research using an example of measuring empathic understanding via facial expression analysis. This note demonstrates the importance of a systematic workflow in data-intensive design research and how it adds the necessary transparency and detail to the method section. It shows how various research outcomes emerge throughout the process. Standardised data analysis, emphasising data preprocessing and exploration, and thorough reporting form the basis for research replicability, reproducibility, and transparency in data-intensive design research.