The authors use data from Wikipedia to build a graph visualization of the evolution of artistic styles inspired by Alfred H. Barr's poster for the 1936 Cubism Abstract Art exhibition. Drawing from Wikipedia articles about persons and art styles, the authors construct a bi-partite network based on their mutual hyperlinks and assume relationships between styles if their respective articles are bridged by hyperlinks to and from person articles. The resulting visualization extends its model with respect to the number of covered styles, thus embedding it within a larger art-historical perspective as seen through the lens of Wikipedia.

The authors do digital research on the work of artist Mark Lombardi (1951–2000) as an experiment in methods for digital art history, manually generating GraphML representations of the networks depicted in his drawings and publishing them at http://www.lombardinetworks.net . Services on the data are implemented like textual search on labels of nodes or an index on what persons or institutions appear in which works. The networks are visualized with nodes linked to Wikipedia information about the actors. With calculations on the networks the authors generate synthetic drawings from multiple original works that overlap in actors.

This work provides a comparison of link structures present in a common subset of art history related biographic person records/articles from the Getty Union List of Artist Names and English Wikipedia.

Analysis of Wikipedia's inter-language links provides insight into a new mechanism of knowledge sharing and linking worldwide.

The author posits that the vast majority of people have little confidence about the “value” they should attribute to contemporary artworks. Many people are seduced into confusing worth with material production, with auction sales records, cult of celebrity, and endless gossip. People are unable to analyze the real activities of artists, their sales and exhibitions, from the unsubstantiated catchphrases of media speculation. This article aims to help clarify the basic mechanisms of the contemporary art market and to enhance understanding through the means of econometrics.

The SocioPatterns sensing platform uses wearable electronic badges to sense close-range proximity among individuals. It was used in an experiential exhibit that simulated a virtual epidemic among the visitors of the INFECTIOUS: STAY AWAY exhibition in the Science Gallery in Dublin, Ireland. The collected data was used to generate a high-resolution visualization that illustrates the variation in contact activity over the course of the exhibition.

In this article the authors highlight some of the issues surrounding the study of past urban connectivity and how archaeologists can deal with them by adopting a complex networks research perspective.

The author presents his interactive digital installations of the past decade, featured in museums, media arts festivals and galleries, that engage the audience to contribute data that is then transformed into content and visually projected large scale in the exhibition space. Collected over time, the data occasions further data-mining, algorithmic processing, with visualization of the results.

The authors analyze the network of Hispanic baroque paintings from 1550 to 1850. They divide the dataset of 11,443 works from Spain and Latin America into 25-year periods in order to study the evolution of the paintings' 211 descriptors. The analysis shows that most of the paintings are linked through genre and theme and that religious Christian themes make up the overwhelming majority of connections among the paintings.

Representing networks is a major interest of researchers in information visualization. In this article, The authors present novel visualization techniques based on Jacques Bertin's reorderable matrices .

Network science is a rapidly emerging analysis method for investigating complex systems, such as the brain, in terms of their components and the interactions among them. Within the brain, music affects an intricate set of complex neural processing systems. These include structural components as well as functional elements such as memory, motor planning and execution, cognition and mood fluctuation. Because music affects such diverse brain systems, it is an ideal candidate for applying network science methods. Using as naturalistic an approach as possible, the authors investigated whether listening to different genres of music affected brain connectivity. Here the authors show that varying levels of musical complexity affect brain connectivity. These results suggest that network science offers a promising new method to study the dynamic impact of music on the brain.

This paper discusses the role of models in the development of an interactive artwork made as the result of interdisciplinary collaboration. A variety of different types of model were used, each with different functions and status to the team.

This work aims to approach the phenomenon of culture through the development of new methods and more powerful tools to capture the content of digitally stored literary material. The authors chose as a test bed Dante's characters of al di là , a domain consisting in a set of data and relations complex enough to sharpen existing tools. The methods of investigation under development should help scholars of a literary text to concretize part of their interpretative intentions. For this purpose, the authors adopt advanced methodologies suitable to obtain a rich representation, expressing the multirelational network inherent in the text.

If whole communities of domain analysts are to be able to use interactive network visualization tools productively and efficiently, tool design needs to adequately support the metacognition implicit in complex visual analytic tasks. Metacognition for such exploratory network-mediated tasks applies across disciplines. This essay presents metacognitive demands inherent in complex tasks aimed at uncovering relevant relationships for hypothesizing purposes and proposes network visualization tool designs that can support these metacognitive demands.