Grottel, S.Heinrich, J.Weiskopf, D.Gumhold, S.Oliver Deussen and Hao (Richard) Zhang2015-03-032015-03-0320141467-8659https://doi.org/10.1111/cgf.12352Multi-dimensional data originate from many different sources and are relevant for many applications. One specific sub-type of such data is continuous trajectory data in multi-dimensional state spaces of complex systems. We adapt the concept of spatially continuous scatterplots and spatially continuous parallel coordinate plots to such trajectory data, leading to continuous-time scatterplots and continuous-time parallel coordinates. Together with a temporal heat map representation, we design coordinated views for visual analysis and interactive exploration. We demonstrate the usefulness of our visualization approach for three case studies that cover examples of complex dynamic systems: cyber-physical systems consisting of heterogeneous sensors and actuators networks (the collection of time-dependent sensor network data of an exemplary smart home environment), the dynamics of robot arm movement and motion characteristics of humanoids.Multi-dimensional data originate from many different sources and are relevant for many applications. One specific sub-type of such data is continuous trajectory data in multi-dimensional state spaces of complex systems. We adapt the concept of spatially continuous scatterplots and spatially continuous parallel coordinate plots to such trajectory data, leading to continuous-time scatterplots and continuous-time parallel coordinates. Together with a temporal heat map representation, we design coordinated views for visual analysis and interactive exploration.