We explore the effects of data and design considerations through the example case of part-to-whole data relationships. Standard part-to-whole representations like pie charts and stacked bar charts make the relationships of parts to the whole explicit. Value estimation in these charts benefits from two perceptual mechanisms: anchoring, where the value is close to a reference value with an easily recognized shape, and alignment where the beginning or end of the shape is aligned with a marker. In an online study, we explore how data and design factors such as value, position, and encoding together impact these effects in making estimations in part-to-whole charts. The results show how salient values and alignment to positions on a scale affect task performance. This demonstrates the need for informed visualization design based around how data properties and design factors affect perceptual mechanisms.

@InProceedings{BG25,
  author       = "Bailey, Connor and Gleicher, Michael",
  title        = "Anchoring and Alignment: Data Factors in Part-to-Whole Visualization",
  booktitle    = "IEEE Vis '25 Short Papers",
  month        = "oct",
  year         = "2025",
  ee           = "https://arxiv.org/abs/2508.01881",
  url          = "http://graphics.cs.wisc.edu/Papers/2025/BG25"
}