Data Memes for Personal Visualization Darius Coelho, Ayush Kumar, and Klaus Mueller Visual Analytics and Imaging Lab, Computer Science Department, Stony Brook University, NY, USA and SUNY Korea, Songdo, Korea ABSTRACT We introduce the concept of Data Memes as artistic visuals of data in which users can merge data visualizations with an image such that the structure of the image supports the user’s intended meaning (or interpretation) of the data. Since Data Memes can represent very personal views, it is natural to employ them in the visualization of personal data. Hence, in this paper we focus on the use of Data Memes for this purpose and also explain how they can be constructed with relative ease. Data Memes as a general concept are meant to engage users with the visualization and persuade a viewer to look at the data. Communicating personal achievements is often the wish of posters in social networks, and although we have not tested this yet, we believe that Data Memes augmented with pertinent personal data have good potential to achieve higher levels of attention in these circles, and elsewhere. Keywords: Chart junk, infographics, personal visualization. 1 INTRODUCTION The information age is upon us and in recent years millions of terabytes of data have been generated every day. A growing chunk of this data is related to our personal lives – information about ourselves, our communities, and issues that have a personal relevance [9]. With the access to such data, people want to make sense of it, and to do so they turn to visualization. While there are a multitude of solutions available to visualize these data, they are rarely used in a personal context. Recently researchers have been exploring the area of Personal Visualization and Personal Visual Analytics. Personal visualization caters to the wide variety of requirements of people who are not necessarily visualization experts or analysts. These people bring personal interpretations to their data and wish to design visualizations that can represent these personal views [20]. In our paper we describe a design framework that allows users to express their opinion about the data by framing them as charts into a self-selected and self-designed visual context. This has good potential for fostering their own engagement with the data as well as that of others with whom these design products are shared. Fig. 1 shows some examples of the personal visualizations of personal data our system can assist users in creating. Here we note that our system can also be used for other types of data, but the opportunity for users to frame these data into a personalized visual context always remains and is a hallmark of our system [5]. We have coined a new term for these types of visualizations – Data Meme. Wikipedia defines the notion of Meme "an idea, behavior, or style that spreads from person to person within a culture". A more recent phenomenon is that of Internet Meme. These are images augmented with text in which the creator’s choice of image puts forward his/her idea about the message the text conveys. They are often reused with the same core message, and as a result gain viral dissemination. Similarly, our Data Memes are images augmented with related data in which the designer’s choice of image puts forward his/her idea about the message the data convey. Our Data Memes appeal to the masses by embracing mainly basic charts, specifically pie, line, and bar charts. Following the definition put forward by Pousman et al. [15], they fall into the set casual information visualization techniques catering to a wide variety of users. The chosen and further enhanced image that becomes part of the visualization is itself a powerful element of the visualization as it can encode a multitude of information. The image is linked to the topic of the data being displayed, with the choice of image putting forth the designer’s point of view about the data. At the same time it is also capable of enhancing memorability and engaging viewers. We foresee that users may use the Data Memes to post their own data on social media or blogs in order to (1) engage viewers to consider the information or (2) put across their own point of view about the data. Figure 1. Personal visualizations (a) shows Joe's speed over multiple heats that he ran (b) shows Mike's workout routine for the week Emails: {dcoelho, ayush.kumar, mueller}@sunykorea.ac.kr (a) (b) Electronic proceedings of the IEEE VIS 2015 workshop Personal Visualization: Exploring Data in Everyday Life The authors remain the holders of the copyright