Infographics: A New Edition
A couple of weeks ago I purchased the latest edition of The Best American Infographics (2016) edited by Gareth Cook. Cook “is a Pulitzer Prize winning journalist and contributing writer to the New York Times Magazine.” In the past he worked for the Boston Globe and was their science editor from 2007 to 2011 [note: he graduated from Brown University with degrees in International Relations and Mathematical Physics, a bit of an odd combination]. This particular edition was released on Oct. 4 and is the fourth in the series. Like the other editions in the series, this one covers a range infographics “originally” published for a North American audience, online or in print, during 2015. If you follow this particular genre of data or info visualization, you may have seen some of them before.
Of course, this all begs the question of “what is an infographic?”, for which I have no really good answer. There is a long list of possibilities of which these are some:
- Wikipedia: Information graphics or infographics are graphic visual representations of information, data or knowledge intended to present information quickly and clearly.
- Customermagnetism.com: An infographic is a popular form of content marketing that can help you simplify a complicated subject or turn an otherwise boring subject into a captivating experience. Ideally, an infographic should be visually engaging and contain a subject matter and data that is appealing to your target audience …something that is truly ‘link worthy’ or ‘share worthy’.
- Visual.ly: Infographics are visualizations that: 1. present complex information quickly and clearly; 2. integrate words and graphics to reveal information, patterns or trends; 3. are easier to understand than words alone; 4. are beautiful and engaging.
- By Example: You’ll know one when you see one, which is sort of Cook’s approach (some examples of infographics about infographics are shown in Figure 2).
An Example: Dear Data
The introduction to this newest edition, which was written by Robert Krulwich of RadioLab and NPR fame, highlights one of the entries called Dear Data. Actually, it’s not a single infographic but a set of 104 (52 pairs of) infographic postcards exchanged between two artists, Giorgia Lupi and Stefanie Posavec, over the course of 2015. At the time, Lupi was living in Brooklyn and Posavec in London. Basically, they came up with a (personal) question for each the 52 weeks of 2015 which they each answered by collecting their own data, creating a graphic to visualize the data, putting it all on a postcard along with a brief explanation of the visualization, and then sending the card to the other. The questions covered a multitude of topics, some more personal than others including: How did you check the time? How often did you say ‘thank you?’ How often did you have intimate contact? How often did you complain? How often did you drink? How often did you walk through doors? And, so on.
This project is actually documented in a new book by the same name. The flavor of the book is reminiscent of some of the examples in a slightly earlier book (Oct. 2014) called Raw Data: Infographic Designers’ Sketchbooks by Heller and Landers. Some of the sketches by Posavec (see the cover in Figure 3) are also reminiscent of some of her earlier work (like her MA project Writing without Words) which I discussed in “Foundations of Analysis: Part 1.” Finally, the entire project exemplifies a larger movement known as the Quantified Self.
The Quantified Self
On a variety of occasions I’ve tried to keep an online diary of my dietary and exercise activities for an extended period of time. A couple of times in the past, I did at least 30 mins of running, cycling or swimming every day for a year, recording and analyzing the particulars as the year progressed. It’s hard to keep a streak like that going, especially when you’re flying all over the world on a frequent basis (75-100+K miles a year). Much of this effort was designed to track various training regimes for upcoming events (marathons, stage races, distance bike rides, and the like). Part of the time it was just to see if I could persevere for the year. A number of times I’ve tracked my diet in a similar fashion for extended periods (up to 6 months at a time) usually for medical reasons. Think about recording everything you eat and drink, determining the amount calories, salt, carbs, fats, you consume for the day. Also, think about trying to analyze the content of a meal eaten at a restaurant. With the exception of the occasional fast food restaurant, most restaurants don’t post this information. Again, this isn’t too daunting unless you’re traveling and eating out a lot (say 50-70% of the year like I used to do).
In the case of exercise, I’ve had a variety of activity trackers over the years (Garmin watches of various sorts). Until recently, these have worked well for running but not so well for cycling and swimming. Now, with a combination of my Garmin watch and iPhone, it’s easy to track all three and to have the data automatically upload to one of the fitness tracking sites for archiving and analysis. Some of these sites (like MyFitness) also make it possible to enter the food and drinks you consume and to have the various nutritional counts automatically computed. However, even with programs of this sort, I can attest that it’s still a royal pain in the backside to track your diet (unless you’re on a mono-diet).
The first time I tracked my info for any extended period of time, I viewed it as a major accomplishment. That is, until I came across some of the leading lights of the Quantified Self (QS) movement including Lifeloggers like Steve Mann and Gordon Bell. This movement focuses on “incorporating technology into the acquisition of data about various aspects of a person’s daily life.” When they say “various,” they aren’t kidding. It’s hard to think of an aspect of one’s life or self, that someone isn’t spending time recording and analyzing it (and in many cases an inordinate amount of time). This includes among other things data about “inputs (food consumed, quality of surrounding air), states (mood, arousal, blood oxygen levels), and work and performance, whether mental or physical.”
One of my favorites is Alberto Frigo‘s right hand (like “My Left Foot” but different). In his own words:
It has been more than 10 years since I have started that project, to be precise today the 11th of May 2014, is my 3.882nd day I have been photographing every object my right hand uses.
This project is briefly described in an article that appeared the Irish online news journal (the journal.ie) in 2015. As the article notes, the project is “documented on his (Frigo’s) frankly kind-of-impenetrable website” (see Figure 4). It is slated to run until 2040 when Frigo will reach 60. At the current rate of 76 pictures a day, that’s just under 1 million pictures.
On a slightly broader scale, and more in keeping with the infographic theme, Nicholas Feltron, who was one of the lead designers of the Facebook Timeline, produced an annual report for each of the ten years from 2005-2014 based on data about his personal activities and surrounding environs. Like an annual corporate financial report, Feltron’s report summarized his data for each of the four quarters, as well as for the total year. The totals for the last report in the series (2014) are shown below in Figure 5.
Life-Logging Before and After Apps: The Rise of Personal Visualization and Personal Visual Analytics
The shift to “commercially available applications and products” reflects a general trend away from PC-based solutions to mobile applications in large part because mobile devices are more frequently used to record the activities while they are on-going. This shift not only has simplified data collection, but it has also marked a major shift towards data 6visualizations revolving around personal dashboards. The visualizations in Figure 6 are typical of those produced a few years ago, while the visualization in Figure 7 is easily recognized as a recent mobile app.
Until recently, research in the use of these sorts of applications, services and tools has been spread across a variety of domains.” This means that many common lessons, findings, issues and gaps may be missed even though these research communities actually share many common goals.” Efforts to address these issues and gaps has given rise to an emerging research community focused on personal visualization (PV) and personal visual analytics (PVA). The former involves “the design of interactive visual representations for personal use in a personal context,” while the latter is the “science of analytical reasoning facilitated by visual representations used within a personal context” (Tory and Carpendale, 2015). Among those with an interest in PV and PVA, there is the belief “that integrating techniques from a variety of areas (among these visualization, analytics, ubiquitous computing, human-computer interaction, and personal informatics) will not only impact applications for formal data users but will also empowering individuals to make better use of their personal data that is relevant to their personal lives, interests, and needs” (Huang et al., 2015; also see Ryan, 2016 for a broader perspective).
Constructing Infographs: Left for a Later Date
In this note, I haven’t addressed any of the issues, techniques or tools revolving around the construction of infographs. This will be addressed at a later date.
Places (Virtual and Real)