We present time-aligned edge plots: time- and edgescalable representations of dynamic graphs. Vertices are mapped to two vertical parallel axes. The left axis depicts the source vertices, whereas the right one depicts the destination vertices. The time axis is horizontally embedded in-between the two axes, resulting in a two-dimensional graph layout. Edges are added by drawing straight lines connecting the corresponding source and destination vertices through time, while the pixels along the lines are used to encode the time-varying information. In this way, the depiction of edges at the individual timepoints is reduced to only a few pixels, resulting in a less cluttered representation of dynamic graphs, while the alignment of edges over time reveals the temporal patterns in the data and preserves the users’ mental map. We evaluate our approach by comparing it theoretically and empirically against the state-of-the-art using dynamic graphs of varying complexities.