Category Archives: visual analytics

Playing With Data

Recent years have brought a steadily growing international interest in openly publishing government and other civic datasets online. Government efforts such as the United States’ data.gov, the United Kingdom’s data.gov.uk, and other European efforts such as in Norway immediately come to mind. There are commercial interests in this space as well, such as the newly launched Data Market, which goes a step beyond data curation to provide visualization tools as well.

So now that we have droves of data, what do we do with it?

One novel approach toward facilitating engagement with such datasets is to create playable experiences from that data. In particularly I have been exploring the design space of data-driven information graphics which include familiar aspects of games, such as goals, rules, rewards, competition, and advancement. The promise is that engagement and learning will be enabled by connecting game activities and goals together with interactions which facilitate visual analysis of the data. For instance, if in order to achieve a high score in the game, the player has to visually compare the values for a data attribute, then in the course of playing they may have an additional opportunity to engage with the data in a meaningful analytic capacity.

At Rutgers University we recently created a game called Salubrious Nation, which explores this idea of playable data. Salubrious Nation takes U.S. public health data, such as smoking, obesity, or diabetes rates, and creates a playable map-based game. The goal of the game is to guess the public health data value (e.g. binge drinking rate) for a randomly selected target county. The player can inform their guess by using other correlated demographic data such as poverty rate, or by looking at how the graphic changes colors when the player manipulates the slider to enter their guess. The player earns points based on how close their guess was to the actual. Each level is a different public health issue and at the end the player can compare their score to others who have played and finished. A screenshot is shown below, and the reader is invited to try the game online at http://www.salubriousnation.com

We ran an online study of Salubrious Nation with dozens of people in order to better understand how such a game-y (i.e. game-like) presentation of information impacts exploration of the data, insights and learning, and fun. What we found is that, when compared to a standard information graphic presentation of the same data, the game-y version was able to redistribute player’s attention in interesting ways. For instance, people’s interaction with counties was more uniformly distributed across the country due to the random nature of selecting target counties in the game. Also, players used the slider more in the game-y presentation, likely because that was both necessary to enter a guess as well as helpful in informing the guess since regional patterns could be see by tweaking it.
Considering the selective attention issue, where people are more likely to pay attention to things that they already agree with, this result suggests an opportunity to get players to look at aspects of the data that they might not otherwise be inclined to look at. While the game-y presentation wasn’t any more fun or engaging than a standard infographic, Salubrious Nation does demonstrate that the goals embedded in a game can successfully motivate interactions and bias both the exploration and the nature of the insights for players.

While Salubrious Nation is an initial foray into the design space of playable data and game-y information graphics, there still remains a huge array of possibilities for exploring this design space. Future designs might incorporate different player interaction pattern (e.g. player vs. player), game resources (e.g. lives, currency, power-ups) and goals or mechanics (e.g. collecting, building). Moreover, there are many other possibilities for game-y presentations of data depending on different data types (e.g. network, tree, temporal, etc.) and different non-map-based visual representations (e.g. node-link, timeline, etc.). Some game mechanics may be more general and adaptable to different data types whereas others may be more specific. More research needs to be done to better understand the generalizeability of these methods.

Opportunities for innovation abound here. The gamification of data does not have to be limited to simply presentation, but could be applied to all facets of a news information pipeline such as information gathering or dissemination. Imagine gamified mobile apps that motivate users to interact with the world in a news gathering capacity. This could enhance activities such as citizen science, or add to news organizations’ ability to gather more and diverse information.

Indeed there is a spectrum of artifacts that can be imagined within the realm of playable data. Some will look more like information graphics, others more like casual games, and still others like something we haven’t even conceived of. I hope that others will join in exploring this design space to make the continuing flood of online civic data more engaging, insightful, and fun for users to interact with.

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For more details on Salubrious Nation and the results of the study readers are invited to see a pre-print of the paper, which will be published at the 2011 Conference on Human Factors in Computing Systems in Vancouver, CA.

Wikileaks and Collaborative Sensemaking?

Thanks to the head start of the likes of the New York Times, the Guardian, and der Spiegel we now have some excellent written reporting on a few of the more important issues exposed in the wikileaks cablegate data. There have also been a number of visualizations of the dataset published in the last few days (e.g. Infothetics has a nice round-up), which help, to some extent, in browsing and making sense of all of the data there.

But what I want to suggest here is that, with all of the attention that this story is getting, that there may be some useful information to mine from social media about what is interesting, important, and noteworthy in the dataset. One of the most useful aspects of social media such as Twitter is that it provides a platform where interested individuals can make observations about what’s going on around them, including observations of large collections of documents.

At Rutgers, where I work, we’ve been developing a social media visual analytics tool call Vox Civitas and have collected a dataset of almost 60,000 (and growing) English language tweets marked with the hashtag “#cablegate” from Twapperkeeper. Vox provides the ability to visualize the collection over time, with sentiment, and includes capabilities for filtering according to many criteria. Without further ado, click here to see the cablegate dataset in Vox. Let us know what you find or if it inspires any follow-up work!