Explaining outliers is a topic that attracts a lot of interest; however existing proposals focus on the identification of the relevant dimensions. We extend this rationale for unsupervised distance-based outlier detection. and through investigating subspaces. we propose a novel labeling of outliers in a manner that is intuitive for the user and does not require any training at runtime. https://www.roneverhart.com/Jacksonville-Lever-with-Round-Rose-Omnia-943-00/