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The Jump Plot is grounded in network graphing. Top influencers include the arc diagram and force directed network diagram. While it has many roots, it stands on its own in terms of ability to visualize and scale to graphing of event sequence data. This page provides you an example implementation of the Jump Plot in d3.js, adapted from Mike Bostock's hive plot page.
The layout of the Jump Plot maintains the integrity of the event sequence you are analyzing, keeping checkpoints (aka nodes) in sequence order. Ultimately this keeps the overall flow of the sequence (which occurs over time) on the horizontal axis, in line with the expectations of our reader. Hops (aka links/edges) are drawn connecting one checkpoint to another (usually drawn with Bezier curves). Hops visually represent the movement from one checkpoint to the next (e.g., moving to the next step in your process). The measure of time elapsed for the hop is utilized to plot the height of the Bezier curve. This design results in a scalable graph type for sequence of events with the ability to handle both contiguous and discontiguous hops (a main value add of the design).
While the Jump Plot examples on this page are leveraging mocked up data, they demonstrate the graph types capability to scale to high volume event sequences. There are additional examples of implementations at jumpplot.com.