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Many of the state\u2010of\u2010the\u2010art techniques can show an overview of vertices and edges but lack a data\u2010scalable visual representation of the time aspect. In this paper, we address the problem of displaying dynamic graphs with a thousand or more time steps. Our proposed interleaved parallel edge splatting technique uses a time\u2010to\u2010space mapping and shows the complete dynamic graph in a static visualization. It provides an overview of all data dimensions, allowing for visually detecting time\u2010varying data patterns; hence, it serves as a starting point for further data exploration. By applying clustering and ordering techniques on the vertices, edge splatting on the links, and a dense time\u2010to\u2010space mapping, our approach becomes visually scalable in all three dynamic graph data dimensions. 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