  Hierarchical clustering is one of the standard methods taught for identifying
and exploring the underlying structures that may be present within a data set.
Students are shown examples in which the dendrogram, a visual representation of
the hierarchical clustering, reveals a clear clustering structure. However, in
practice, data analysts today frequently encounter data sets whose large scale
undermines the usefulness of the dendrogram as a visualization tool. Densely
packed branches obscure structure, and overlapping labels are impossible to
read. In this paper we present a new workflow for performing hierarchical
clustering via the R package called protoshiny that aims to restore
hierarchical clustering to its former role of being an effective and versatile
visualization tool. Our proposal leverages interactivity combined with the
ability to label internal nodes in a dendrogram with a representative data
point (called a prototype). After presenting the workflow, we provide three
case studies to demonstrate its utility.
