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.