  Engaging in interdisciplinary projects on the intersection between
visualization and humanities research can be a challenging endeavor. Challenges
can be finding valuable outcomes for both domains, or how to apply
state-of-the-art visual analytics methods like supervised machine learning
algorithms. We discuss these challenges when working with cultural heritage
data. Further, there is a gap in applying these methods to intangible heritage.
To give a reflection on some interdisciplinary projects, we present three case
studies focusing on the labeling of cultural heritage collections, the problems
and challenges with the data, the participatory design process, and takeaways
for the visualization scholars from these collaborations.
