We begin with the premise that data literacy is a fundamental facet of citizen education in this information age, and that an engaged citizenry in a democracy not only requires access to data, but also the capacity to manipulate and examine the data from multiple perspectives. The visualization of data elucidates trends and patterns in the phenomena that the data represents, and opens accessibility to understanding complicated human and natural processes represented by data sets. Research indicates that interacting with a visualization amplifies cognition and analysis. A single visualization may show only one facet of the data. To examine the data from multiple perspectives, engaged citizens need to be able to construct their own visualizations from a data set. Many tools for data visualization have responded to this need, allowing non-data experts to manipulate and gain insights into their data, but most of these tools are restricted to the computer screen, keyboard, and mouse. Cognition and analysis may be strengthened even more through embodied interaction with data. We present here the rationale for the design of a tool that allows users to probe a data set, through interactions with graspable (tangible) three-dimensional objects, rather than through a keyboard and mouse interaction. We argue that the use of tangibles facilitates understanding abstract concepts, and facilitates many concrete learning scenarios. Another advantage of using tangibles over screen-based tools is that they foster collaboration, which can promote a productive working and learning environment. We speculate that collaborative data exploration can be a productive educational activity for citizens in their communities and in the classroom, and we suggest our tool as a means to do this.

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We extracted 327,322 faces from an archive of Time magazine containing 3,389 issues dating from 1923 to 2014, classified the gender of each extracted face, and discovered that the proportion of female faces contained within this archive varied in interesting ways over time. The proportion of female faces first peaked in the mid-to-late 1940s. This was followed by a dip lasting from the mid-1950s to the early 1960s. The 1970s saw another peak followed by a dip over the course of the 1980s. Finally, we see a slow and steady rise in the proportion of female faces from the early 1990s onwards. In this paper, we seek to make sense of these variations through an interdisciplinary framework drawing on psychology, visual studies (in particular, photography theory), and history. Through a close reading of our Time archive from the 1940s through the 1990s, we conclude that the visual representation of women in Time magazine correlates with attitudes toward women in both the historical context of the era and the textual content of the magazine. Beginning with its inception in 1923, Time magazine, perhaps more than any other comparable publication, has both reflected and influenced American popular attitudes toward domestic and global politics. This includes the changing ideas about women since the mid-twentieth century, which is the subject of this paper. Our approach was twofold. We used supervised machine learning to extract visual images of faces from an archive of Time magazine, which contains 3,389 issues ranging from 1923 to 2014, and computationally classified the faces as male or female. We then closely read selected Time articles to make sense of this quantitative data against the background of postwar feminism and the history of the magazine itself. Our focus is on the period between the 1940s and the 1990s, which witnessed significant changes in attitudes toward women, and where our data of the proportion of female faces exhibits significant fluctuation.

Tangible user interfaces and physical representations of data are both promising approaches to improving insights derived from large data sets. Interactive tangible representations of data, which seamlessly combine those two approaches, potentially take advantage of cognitive processes, data representations, and interactions not supported by current approaches and may enhance collaboration. This paper describes user evaluations of two sets of prototypes comprised of physical blocks to represent data. One set uses six blocks of identical dimensions and another set uses six blocks with different dimensions. The objectives of this pilot study include (i) making general observations on how users interact with the two prototypes, (ii) making observations on the role these tangible interfaces play in collaboration, and (iii) comparing the two sets of tangible interfaces. We report on the results of the study and discuss future work.