After decades of digitization, large cultural heritage collections have emerged on the web, which contain massive stocks of content from galleries, libraries, archives, and museums. This increase in digital cultural heritage data promises new modes of analysis and increased levels of access for academic scholars and casual users alike. Going beyond the standard representations of search-centric and grid-based interfaces, a multitude of approaches has recently started to enable visual access to cultural collections, and to explore them as complex and comprehensive information spaces by the means of interactive visualizations. In contrast to conventional web interfaces, we witness a widening spectrum of innovative visualization types specially designed for rich collections from the cultural heritage sector. This new class of information visualizations gives rise to a notable diversity of interaction and representation techniques while lending currency and urgency to a discussion about principles such as serendipity, generosity, and criticality in connection with visualization design. With this survey, we review information visualization approaches to digital cultural heritage collections and reflect on the state of the art in techniques and design choices. We contextualize our survey with humanist perspectives on the field and point out opportunities for future research.

The visualization and analysis of dynamic networks have become increasingly important in several fields, for instance sociology or economics. The dynamic and multi-relational nature of this data poses the challenge of understanding both its topological structure and how it changes over time. In this paper we propose a visual analytics approach for analyzing dynamic networks that integrates: a dynamic layout with user-controlled trade-off between stability and consistency; three temporal views based on different combinations of node-link diagrams (layer superimposition, layer juxtaposition, and two-and-a-halfdimensional view); the visualization of social network analysis metrics; and specific interaction techniques for tracking node trajectories and node connectivity over time. This integration of visual, interactive, and automatic methods supports the multifaceted analysis of dynamically changing networks.

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Uncertainty is a standard condition under which large parts of art-historical and curatorial knowledge creation and communication are operating. In contrast to standard levels of data quality in non-historical research domains, historical object and knowledge collections contain substantial amounts of uncertain, ambiguous, contested, or plainly missing data. Visualization approaches and interfaces to cultural collections have started to represent data quality and uncertainty metrics, yet all existing work is limited to representations for isolated metadata dimensions only. With this article, we advocate for a more systematic, synoptic and self-conscious approach to uncertainty visualization for cultural collections. We introduce omnipresent types of data uncertainty and discuss reasons for their frequent omission by interfaces for galleries, libraries, archives and museums. On this basis we argue for a coordinated counter strategy for uncertainty visualization in this field, which will also raise the efforts going into complex interface design and conceptualization. Building on the PolyCube framework for collection visualization, we showcase how multiple uncertainty representation techniques can be assessed and coordinated in a multi-perspective environment. As for an outlook, we reflect on both the strengths and limitations of making the actual wealth of data quality questions transparent with regard to different target and user groups.

Stories are an essential mode, not only of human communication-but also of thinking. This paper reflects on the internalization of stories from a cognitive perspective and outlines a visualization framework for supporting the analysis of narrative geotemporal data. We discuss the strengths and limitations of standard techniques for representing spatiotemporal data (coordinated views, animation or slideshow, layer superimposition, juxtaposition, and space-time cube representation) and think about their effects on mental representations of a story. Many current visualization systems offer multiple views and allow the user to investigate different aspects of a story. From a cognitive point of view, it is important to assist users in reconnecting these multiple perspectives into a coherent picture-e.g., by utilizing coherence techniques like seamless transitions. A case study involving visualizing biographical narratives illustrates how the design of advanced visualization systems can be cognitively and conceptually grounded to support the construction of an integrated internal representation.

Information visualizations (InfoVis) in the context of political communication are designed to convey a broad understanding of socio-political data and their multitude of intricately connected variables to the public. A cognitive framework to explain and empirically study how users acquire and organize their internal representations gained from InfoVis systems with multiple perspectives is still missing. In this paper we discuss the theory of mental models and its consequences for the design and research of InfoVis interfaces. Especially for multidimensional data, it is a challenge to design accessible and conceptually consistent InfoVis interfaces to support the local and global coherence of the recipients’ mental models. In this paper we exemplarily show how specific design features, i.e. advance organizers, narrative visualizations, seamless transitions, and multiple coordinated views can accomplish this in the field of political communication and its complex data.

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