In the digital humanities, variation in the data is both a blessing and a curse. On one hand, variation represents change that can provide us with broad-scale historical insight (e.g., "How is what people talked about in the 18th century different from what they talked about in the 17th century?"). On the other hand, some kinds of variation can actually obscure others (e.g., did people actually stop talking about a particular word in the 17th century, or did the spelling just change?). As DH research scales up to more and more documents covering ever longer spans of history, variation of both kinds is necessarily unavoidable and must be explicitly accounted for. In this paper, we discuss the challenges concerning variation that we have encountered in a multi-year, collaborative project focused on a collection of print documents from 1470-1800. We have addressed this variation through a combination of data standardization and task-driven visualization design.

@InProceedings{ASG16a,
  author       = "Alexander, Eric and Stuffer, Deidre and Gleicher, Michael",
  title        = "Addressing Variation at Scale in Historical Document Collections",
  booktitle    = "Proceedings of the 2016 Workshop on Visualization for the Digital Humanities",
  month        = "Oct",
  year         = "2016",
  url          = "http://graphics.cs.wisc.edu/Papers/2016/ASG16a"
}