  We propose a new way of thinking about one parameter persistence. We believe
topological persistence is fundamentally not about decomposition theorems but a
central role is played by a choice of metrics. Choosing a pseudometric between
persistent vector spaces leads to stabilization of discrete invariants. We
develop theory behind this stabilization and stable rank invariant. We give
evidence of the usefulness of this approach in concrete data analysis.
