We present a hybrid visualization technique that integrates maps into network visualizations to reveal and analyze diverse topologies in geospatial movement data. With the rise of GPS tracking in various contexts such as smartphones and vehicles there has been a drastic increase in geospatial data being collect for personal reflection and organizational optimization. The generated movement datasets contain both geographical and temporal information, from which rich relational information can be derived. Common map visualizations perform especially well in revealing basic spatial patterns, but pay less attention to more nuanced relational properties. In contrast, network visualizations represent the specific topological structure of a dataset through the visual connections of nodes and their positioning. So far there has been relatively little research on combining these two approaches. Shifted Maps aims to bring maps and network visualizations together as equals. The visualization of places shown as circular map extracts and movements between places shown as edges, can be analyzed in different network arrangements, which reveal spatial and temporal topologies of movement data. We implemented a web-based prototype and report on challenges and opportunities about a novel network layout of places gathered during a qualitative evaluation.

Culturegraphy visualizes the exchange of cultural information over time. Treating cultural works as nodes and influences as directed edges the visualization of these cultural networks can provide new insights into the rich interconnections of cultural development such as movie references. All findings were made in a process that involved network scientists, a media theorist, and a sociologist. The role that visualization can play in bridging scientific communities was central to this work. In this sense, the resulting visualizations were process to bring researchers from different disciplines together. Traditionally using different methods, physicists increasingly ask similar questions as media theorists or sociologists as they study the dynamics in networks. Visualization can serve as a common language that brings fields together, shows differences, but also has its own idiosyncratic views.

We introduce a set of integrated interaction techniques to interpret and interrogate dimensionality-reduced data. Projection techniques generally aim to make a high-dimensional information space visible in form of a planar layout. However, the meaning of the resulting data projections can be hard to grasp. It is seldom clear why elements are placed far apart or close together and the inevitable approximation errors of any projection technique are not exposed to the viewer. Previous research on dimensionality reduction focuses on the efficient generation of data projections, interactive customisation of the model, and comparison of different projection techniques. There has been only little research on how the visualization resulting from data projection is interacted with. We propose a set of interactive visualization methods to examine the dimensionality-reduced data as well as the projection itself. The methods let viewers see approximation errors, question the positioning of elements, compare them to each other, and visualize the influence of data dimensions on the projection space. We created a web-based system implementing these methods, and report on findings from an evaluation with data analysts using the prototype to examine multidimensional datasets.

Culturegraphy visualizes cultural information exchange over time. Treating cultural works as nodes and influences as directed edges, the visualization of these cultural networks can provide new insights into the rich interconnections of cultural development. The graphics represent complex relationships of movie references by combining macro views summarizing 100 years of movie influences with micro views providing a close-up look at the embedding of individual movies. The macro view shows the rise of the self-referential character of postmodern cinema, while the micro level illustrates differences between individual movies, when they were referenced and by whom. The visualizations provide views that are closer to the real complexity of the relationships than aggregated views or rankings could do.