Wednesday, November 28, 2007

the usability of YouTube

I just came across this short paper on the usability of YouTube that I thought was interesting given the recent discussion here and on Stephen Few's blog. The authors point out that YouTube is a hugely successful site despite sporting an interface design that apparently doesn't respect many conventional usability heuristics. By considering what users enjoy about the site, and what keeps them coming back, they suggest that these traditional evaluation methods may need to be redefined; among other things, "engagement" and "playfulness," two terms we've been throwing around here lately, are becoming increasingly important.

While I won't argue that YouTube serves the same purpose as information visualization (particularly if its "apparently bad design" is intentional, as the paper suggests), what I find most poignant about this article is how it identifies the "new" Web 2.0-enabled user, a digital native that grew up with the web, as having a heightened literacy for the internet and its technologies. This new user interacts with information differently and more fluently than users of the past, so the design of interfaces for them should reflect this -- a sentiment that certainly applies to information visualization design as well.

Sunday, November 25, 2007

continuing the discussion with Stephen Few - my response

Before responding to Steve’s points, I want to take a step back and clarify that my original intent in critiquing his InfoVis capstone presentation was not to attack him personally, but rather his position on the topic of “infovis for the masses.” Unfortunately, it may have come off that way, and Steve’s responses to my issues, phrased as responses to “Few does X,” may further personalize the criticism, so I want to emphasize that this is ultimately a discussion about approaches to understanding infovis “for the masses,” and not some kind of flame war. As Steve suggested, I think it is clear that we both care a great deal about the “state of information visualization” today, so I apologize, particularly to Steve, if any part of this conversation has seemed or seems personal. It most certainly isn’t intended to be. I also want to point out that I completely agree with a good deal of the “low level” design issues Steve rails against (problematic use of color, charts designed so poorly that it is actually impossible to read values off of them, etc.); That’s not really what I’m taking issue with in this conversation. Again, I’m more interested in conceptualizing infovis design “for the masses.” So, that said: onwards and upwards!

Rather than responding point-by-point to Steve’s post, I will try to address what I see as the underlying disconnect in our positions. This disconnect, I think, revolves around our differing conceptions of the scope of information visualization, as well as our differing definitions of certain key terms. I’ll elaborate from some of the statements he makes in his response:

What is perhaps not obvious, based on my capstone presentation alone, is
the fact that I spend a fair amount of time trying to understand what draws
people to ineffective visualizations—those that fail to serve the needs of the
audience while managing to appeal to that audience on some level.


Many-Eyes has managed to make the process of data exploration and analysis interesting and fun, without resorting to features that undermine the effectiveness of the activity.


I hope that I’m never guilty of writing off meaningful aspects of visualization as useless, simply because they don’t match my own preferences—aesthetic or otherwise. If you ever catch me doing so, I want you to call me on it. Just make sure that what you point out as useful in a
visualization is actually useful and not just appealing to your own preferences.


When a great deal of evidence indicates that certain visualization practices work better than others, I believe that it’s helpful to teach people to follow the best practices and avoid those that fail.


I define the “right way” as the way that best satisfies the needs of people—the way that works. I’m a pragmatist. What I don’t do is define the “right way” as the way that people desire things to be done. Our desires, our notions of how things should be done, often conflict with the way that really works.


The real “disservice to the goal of popularizing information visualization” is the existence of (1) ineffective or irrelevant infovis projects and products that represent our work poorly, and (2) the unfortunate inability of many experts in the field to present their work to those who need it in a way that they can relate to, care about, and understand.

What makes these statements problematic to me, and what was part of what I was trying to get at in my original critique, are Steve’s definitions of terms like “useful,” “(in)effective,” and “[user] needs,” with regard to information visualization. If I were to try to identify, right off the bat, the fundamental disconnect between the two “camps” that Steve and I represent, it would be that we don’t necessarily agree on what these terms mean.

Steve, coming from the area of business intelligence, presumably values the clarity of the data above all else, which I think is a perfectly reasonable position given the “needs” of that field. I’m not totally familiar with the world of business intelligence, but the use of information graphics and visualization in that area is undoubtedly motivated by a need to understand the meaning of quantitative data and make critical decisions based on that understanding. So, for him, having the data presented as plainly, directly, and efficiently as possible is the prime consideration in the design of their visualizations. Anything that distracts from that is considered ineffective or not useful.

My contention is that this sort of traditional, “scientific” understanding of information visualization, while certainly valuable in some domains (such as business intelligence), is too restrictive when considering its broader, more popular uses. For one thing, there is the obvious point that “popular visualization” does not necessarily share the same critical goals. Many of the infovis examples that Steve criticized from the Smashing Magazine article exemplify this, in that they present information that is not necessarily “mission critical” in the same way BI information might be – people are not necessarily viewing these visualizations because they need to make critical decisions based on the meaning of the data they present. Rather, they are perhaps more “casual” forms of information visualization in which directness and efficiency of transmission are not the primary goal, which then complicates our conception of “usefulness” or “effectiveness.”

Now, I am the first to admit that, at this moment, I don’t have formal definitions of these terms that stand in opposition to the ones applied in Steve’s conception of infovis, but work to define them is starting to emerge: at InfoVis, we saw Zack Pousman’s (et al.) presentation and paper on “casual infovis,” Martin Wattenberg’s discussion of “vernacular visualization,” Fernanda Viegas’ description of the many expected uses of Many Eyes, Ola Rosling’s emphasis on visualization as storytelling, Brent Fitzgerald on Swivel as “big (social) database in the sky,” and Robert Kosara suggesting new uses for infovis (I’m sure I’m leaving someone out, but these are some I just blogged about). Across the internet, the discussion continues: Andrew Vande Moere, Andrea Lau, and Nick Cawthon ponder information aesthetics, the guys at Stamen Design discuss “useless” visualization, as does Matthew Hurst of Microsoft Live Labs… the list goes on!

What bothers me about Steve’s position, which I sensed mirrored in a lot of the discussion at InfoVis, is the suggestion that this new research, or the type of visualization that it describes, is somehow “not infovis.” While it’s true that infovis, as a field, grew out of a “strict” scientific tradition (ie. computer science) that informs its theories and methodologies, it is going to have to broaden its understanding of the ways in which “normal” people interact with information if it wants to present itself as accessible to the masses. I think the field will need to start thinking more in terms of “engagement design” rather than the highly quantified metrics of efficiency, time on task, etc., that have traditionally characterized user studies in HCI and interface design. Those metrics may make sense (and I think give rise to, at least in part, the “great deal of evidence” supporting best practices that Steve refers to) when describing visualization usage by users who spend their lives (and make their livelihoods by) working with charts, graphs, and other visualizations, but almost certainly don’t capture what is important about the way “the masses,” as I define them, use information visualization. For their purposes, engagement (another ambiguous term) should perhaps trump efficiency; for instance, maybe a particular design should sacrifice some of the “directness” of the data for other elements, such as “playfulness,” that encourage continued use. I can understand why Steve and others might be skeptical of this sort of approach to infovis, as there doesn’t yet exist a large body of research support it, but I would argue that this is because we haven’t really starting thinking about visualization in these terms yet, rather than because there is something fundamentally wrong with it. I’m concerned that the traditional infovis field believes too strongly that their understanding of their domain is the final word on information visualization. This is a problem.

Steve himself admitted that, if given a choice of visualization design, most users would always pick the “flashier” one. I’ll just reiterate that instead of assuming that “flashier” equals “less effective,” we should try hard to understand the value of “flashiness” (or “novelty,” or “aesthetics,” or whatever we want to call it) against the expanded definitions of “useful” and “effective” I’ve referenced here. At his tutorial session at InfoVis, I made the (admittedly somewhat outlandish) comparison to Jim Cramer and his highly-rated CNBC program, Mad Money. Cramer uses an almost ridiculous amount of (literally) bells-and-whistles to “decorate” his presentation of financial information, and yet the information gets across. Is it presented as thoroughly as it might be by a more Spartan “talking head” presentation? Probably not, but the show’s popularity says something about what engages non-experts. Coming back to the realm of infovis, there is something undeniably important and valuable about the fact that visualization examples such as Jonathan Harris’ “We Feel Fine,” or Stamen Design’s visualizations of, or, yes, the Ambient Orb, are popular and engaging. What’s interesting about Many Eyes, an example Steve does like, is that it supports many types of representation, from traditional analytic uses to the more unusual ones that Fernanda described in her presentation at InfoVis. Arguing that the mere existence of these sorts of projects undermines information visualization is a real problem. It implicitly assumes a very narrow definition of what “information visualization” is, which in turn rejects the type of understanding that I think is absolutely necessary to promoting the field as a medium that anyone can use. This kind of work should be taken seriously when considering information visualization design “for the masses.” I’m not arguing that its design principles should replace the ones that Steve talks about, but I’m completely certain that the two perspectives are not mutually exclusive; the reality, I think, is that both could benefit from a more robust understanding of one another.

So, in the end, Steve and I may be talking about two different things. As I stated at the beginning of this post, I certainly agree with most of the principles he employs to promote more effective design of business-related information visualization. What troubled me about his capstone at InfoVis, and a lot of the other discussions there, was perhaps that this was as far as his conception of “infovis for the masses” seemed to go. I applaud him for a lot of what he tried to convey to the audience there (they needed to hear it!), but I would suggest that “the masses,” to me and many others, includes a much wider population of users – most of whom are not “data analysts” of any sort.

Tuesday, November 20, 2007

continuing the discussion with stephen few

Yesterday I received an email from Stephen Few indicating that he had responded to my previous post criticizing his capstone presentation at InfoVis. You can read it here.

I really appreciate Steve's interest in continuing the discussion (and frankly I'm flattered that he even read what I've been writing), so this is just a quick note to indicate that I fully intend to respond to his post, either in the comments on his blog or here (or both). I'm in crunch-mode on a couple of projects now that the semester is winding down, but I will have something up as soon as possible in the next couple of days.

Thursday, November 15, 2007

InfoVis impressions, part 4: "Infovis as Seen by the World Out There"

This is the fourth (and final) part of my impressions of InfoVis 2007. Click here for part 3.

UPDATE: Stephen Few has made a written version (PDF) of his capstone presentation available on his website.

The final “for the masses” presentation at InfoVis was Stephen Few’s capstone, “InfoVis as Seen by the World Out There.” In it he discussed his observations on “the big picture view of what’s going on in infovis,” and how the lay-public, who “desperately need what we have to offer,” perceives (or misperceives) the field of information visualization. He argued that the outsider’s perspective is based on poor, primitive examples of visualization, and tried to motivate the audience to address the situation.

Rather than going in to too much more detail, I wanted to defer to Joe Parry’s impression of the talk, because it matches my own almost exactly:

On a separate topic I found Stephen Few's capstone talk rather unsettling - I understand why he is so passionate about designing clear visuals, but sometimes that passion can err on the abrasive side. And that style won't endear the visualization community to the world out there. I also think he underestimates the power of playfulness and fun in reaching out to an audience - come on - Swivel's option to 'bling your graph' is just funny! Another worry is that the very Spartan style of visuals he favours actually imposes an aesthetic in its own right, for all of its good intentions and intelligent rationale. We should accept some people just won't like that aesthetic.

Over the course of his talk, Few showed many “bad” examples of infovis from the web. Some of them I agreed were pretty terrible (including some of the new charting features in Excel), but most I felt he was dismissing without trying to understand what is useful about them (in addition to his criticism of Swivel, he wrote off the Ambient Orb, and the list of infovis examples recently published by Smashing Magazine). What was clear, as Parry alludes to, is that Few’s conception of popular infovis design is particularly hard-line -- more about telling the masses how to display information the “right” way, rather than thinking about how non-experts might interact with information differently and with different needs. This is understandable given his usual focus on design for the business intelligence community, but I think that attitude does a disservice to the goal of popularizing information visualization. I’m not arguing that something like the Ambient Orb is a fantastic example of visualizing information, but the fact that (some) people find it compelling suggests that there is something engaging about its presentation. Rather than writing it off as useless, why not try to figure out how to incorporate its engaging qualities in to more “sophisticated” visualization systems?

I wholeheartedly agree with Few’s assertion that the infovis community would do well to consider the scope of impact their work has, and I obviously believe that the field of information visualization can help “the world out there,” but I didn’t find the rhetoric of his talk particularly encouraging. On the one hand, he promotes bringing infovis “to the masses,” but on the other his conception of that process feels a bit too evangelical. Everything about his presentation revolved around showing “outsiders” why their intuition about infovis is wrong. If our goal is to produce infovis that makes sense to these non-experts, I don’t think this mentality is constructive.

Monday, November 12, 2007

InfoVis impressions, part 3: "The Impact of Social Data Visualization"

This is part 3 of my impressions of InfoVis 2007. Click here for part 2.

This panel essentially continued the discussion from the “Infovis for the Masses Panel” the previous day, and, to me, was the best of the conference. The presenters were Brent Fitzgerald from Swivel, Ola Rosling (son of Hans Rosling) from Google/Gapminder, Fernanda Viegas from Many Eyes, and Martin Wattenberg (subbing for Warren Sack) talking about examples of social visualization on the web. The panel was chaired by Robert Kosara from the University of North Carolina at Charlotte.

Kosara kicked off the discussion by motivating the idea of focusing on the visualization needs of “everybody.” He pointed out several important functions for popular visualization, including using it to address data that is public but not readily available to most people (census data, federal spending data, the type of information visualized by They Rule, etc.). He also emphasized the value of visualizations as political statements and as storytelling (referencing Hans Rosling and Al Gore’s recent uses of infovis). Finally, and appropriately, he asked the audience whether we can use visualization to change the world, and whether anyone wants to use visualization for anything beyond presenting at InfoVis every year. Slightly rhetorical, but poignant!

Next, Fernanda Viegas spoke about the various different ways people are using visualizations on and around Many Eyes, including as political commentary, art (“lit-mash” with tag clouds, etc.), as focal points for conversation, and as educational tools. She pointed out that these are all “new” ways of using visualization that see it as a medium for communication rather than scientific tool. This, I think, is one of the most significant points you can make about what visualization “for the masses” is about.

Following Fernanda, Brent Fitzgerald talked about Swivel, contrasting its more private data model to Many Eyes’ open one. He described their goal as creating the “big database in the sky,” where anyone can find the information they’re looking for, emphasizing Swivel’s support for collaborative data editing and analysis. Swivel aims to produce a “data marketplace” based on a social network of contributors.

Ola Rosling presented next, starting with a characteristically “Rosling-esque” demo of child mortality data from across the world using the Trendalyzer/Google visualization tools. He stressed the importance of animation in information visualization (particularly with regard to time-based data), arguing that “static representations are lying” by only showing a single snapshot of a changing data set. He also suggested that visualization literacy should be motivated by democratizing access to data, as well as simply creating visualizations of compelling data. Finally, he ended with a fantastic analogy that compared the information visualization community to the photography community; he asked us to imagine a photography conference where the photographers were all horrified by how their field was being devalued by the ubiquity of photographs taken by average folks with their cellphone cameras. It’s not a perfect analogy, but certainly an apt one, and one that I think touched on a real “fear” within the community. As Stephen Few pointed out in his capstone the next day, there was a lot of laughter after Ola’s analogy, but it was nervous laughter.

Finally, Martin Wattenberg presented on the popular use of visualization on the web by introducing the concept of “vernacular visualization,” the use of “unsophisticated” visualizations by non-(visualization)-experts to “get things done.” I really liked this framework for understanding non-expert use, as it relates closely to Thomas McLaughlin’s concept of “vernacular theory” from cultural/media studies, and the idea that non-experts (or non-academics) engaged in the production and consumption of (in this case) information visualization make use of a rich set of “theories” whose basis is not necessarily in traditional ivory-tower academic theory (and which may in fact break from it), but which are nonetheless very effective and meaningful for “getting things done.” Martin argued that in order to conceptualize “infovis for the masses,” we need to understand this vernacular. As an example, he pointed to the impact of xkcd’s “Map of the Internet,” a “vernacular” (literally a cartoon) visualization, and its influence on more traditional IP-space visualization within the infovis community (hint: evidently it quickly became one of the most cited examples of IP-space visualization in academic infovis papers!). He closed by identifying three directives essential to promoting social data analysis: 1) Love your data! 2) Enable conversation, 3) Visualizations can be very simple or very complex, and emphasized that “Anything can be successful [in popular visualization], so let’s try a lot of things!”

The discussion that followed in the Q&A session was varied and at times tense. The initial questions again reflected a lot of concern about the misappropriation of data on sites like Many Eyes, as well as a concern that visualization could be used in “unexpected (read: “negative”) ways. This culminated in what I perceived as bizarrely derogatory question from Ben Schneiderman, who asked the panel how we can move beyond the “modest” successes of their work, and increase the credibility and reliability of their data by “removing the garbage from view.” Aside from ignoring what these sites are actually about, this, again, struck me as characteristic of the dominant conception of information visualization at the conference as a truth-telling tool. It reflects a lack of awareness of visualization as a medium, with all the subtleties such awareness entails. As Martin pointed out, people misrepresent information in any medium, and several members of the panel reiterated that part of understanding visualization as a medium is gain a literacy that allows you detect the “lies.”

There was an interesting question about how to motivate an analytic approach (in visualizations) to understanding for non-experts, and how you might use elements of “artistic” infovis to bring people in to analytic infovis. This is something I’m interested in myself. Fernanda Viegas responded by suggesting that non-experts are not necessarily trying to do “analysis,” but rather trying to tell stories, or trying to see themselves in the data, and this is a type of use that should be taken in to consideration (and supported). Robert Kosara suggested that designers should look at “playfulness” as a means to capture attention, and that giving users the “means of production” with regard to visualization will help engage them beyond what happens when they are merely presented with a finished product. Ola Rosling emphasized the need to keep things simple, as non-experts will quickly turn away from a tool that seems too complex.

In a related question, Zach Pousman asked how we might evaluate the effectiveness of social visualization tools, or even identify the measure of effectiveness. Martin favored the “ethnographic” approach, arguing that since visualization is a medium, we need to look at how it’s being used and written about, rather than relying on traditional HCI metrics. The line of questioning ended there, but I think this an area in need of much more exploration; it is fairly obvious that the “small-N” evaluations attached to most infovis research cannot accurately capture real-world usage patterns, particularly when talking about social or mass-audience systems. Coming from media studies, I always think of this as analogous to the situation the television industry is facing, where the networks are only just now realizing that Nielson ratings don’t account for the myriad of new ways (YouTube, etc.) that viewers encounter and interact with television content. The same could be said about visualization.

The rest of the questions continued to revolve around issues of data provenance, and whether or not it was “wise” to empower non-experts with the “means of production” of information visualization. On the whole, I couldn’t help but find the conversation discouraging. I felt that, at best, most of the questions ignored what was significant about the popularization of infovis, and at worst, their rhetoric was actually quite demeaning to the concept. Even the perspectives that favored empowering non-experts were based on an undercurrent of intellectual superiority – there were many repeated metaphors of non-experts being “illiterate” or having a “child-like” ignorance of how to do proper visual analysis. The idea that they could be using visualization in meaningful ways that did not necessarily adhere to the traditional “values” of infovis remained largely unaddressed.

InfoVis impressions, part 2: "Infovis for the Masses"

This is part 2 of my impressions of InfoVis 2007. Click here for part 1.

On Sunday afternoon was the panel I was most excited about coming in to the conference, “Infovis for the Masses.” It featured Fernanda Viegas, Martin Wattenberg, and Frank van Ham from the IBM Visual Communication Lab presenting on Many Eyes, Wesley Willet representing a group from UC Berkeley presenting their paper “Scented Widgets: Improving Navigational Cues with Embedded Visualizations,” Jock Mackinlay from Tableau Software presenting “Show Me: Automatic Presentation for Visual Analysis,” and Zach Pousman representing a group from Georgia Tech presenting a paper called “Casual Information Visualization: Depictions of Data in Everyday Life” (I blogged about this one a couple of weeks ago). Ben Schneiderman chaired the panel.

However, while each of the panelists made interesting presentations, the direction of the panel as a whole came off as largely incoherent. It was clear that we were looking at several different conceptions of “infovis for the masses,” none of which were really able to interface with one another. To me, the presentations on Many Eyes and “casual visualization” were most related to the conception of popular visualization (“for the masses”) that I write about on this blog. They were also the most controversial, based on audience response. Many Eyes is about democratizing and socializing visualization, empowering anyone to become a producer and consumer of visualization, and encouraging the benefits that come from social interaction around the visualization of data. The paper on “casual visualization” suggests that there are valuable ways to use visualization that don’t have to do with solving specific problems in an analytic way, and that traditional design principles don’t necessarily support this type of interaction.

The other two presentations seemed less “masses”-focused to me. The “scented widgets” presentation was certainly interesting, but maybe too technique-specific for the scope of the discussion (or what I hoped the discussion would be). Mackinlay’s presentation was a demo of the charting features in Tableau. To him, “the masses” referred to corporate data analysts needing to produce charts and graphs with software like his. While I think Tableau is an impressive piece of work, its cost alone guarantees that it isn’t “for the masses.”

Finally, following the panelist presentations, Ben Schneiderman, one of the forefathers of information visualization field, closed the discussion with a few statements related to this slide (this was taken from a presentation of his in 1998, but the slide he showed was the same) that hammered home the incoherence of the panel. He argued the need for “scientific studies” and “whole product solutions” to bridge the gap between “visionaries” and “pragmatists, conservatives, and skeptics.” I may not have motivated it well enough here, but this, in my mind, had almost nothing to do with what was discussed in the previous two hours. Perhaps it spoke to what Mackinlay was talking about, but it utterly ignored the presentations about Many Eyes and “casual infovis.” Discussion on “infovis for the masses” should be about how non-experts consume and produce information visualization, not about how brilliant “visionaries” can sell product to them.

The questions from the audience at this panel mostly revolved around Many Eyes, but in my opinion also missed the point. There was a lot of concern over the validity of the data being uploaded to the Many Eyes site, and the possibility of “poor” visualizations being produced by people who don’t understand how to “best” use the visualization templates offered. These questions certainly reflected the characterization of the community described in part 1 of my impressions: overly focused on the scientific validity and usefulness of the content on Many Eyes. Such a focus ignores what Many Eyes is actually about; what’s interesting about the site is not really the data being uploaded, but the type of use and interaction that is happening around the visualization of that data.

InfoVis impressions, part 1

I got back from InfoVis 2007 a week and a half ago, and after catching up on the week I missed back home, I am just getting around to putting my impressions in order. Since I have a lot of stuff to post, I decided to serialize it. This is part 1.

Overall, it was a fantastic experience, and really gave me some much-needed insight in to what’s going on in the visualization community. There were many compelling presentations, panels, and posters there, but I’m mostly going to focus on the “for the masses” elements of the conference, since that is what is most related to my work. As the unofficial theme of InfoVis this year, the focus on the popularization of information visualization provided a fascinating and extended look in to not only what work is being done in this nascent “genre” of infovis, but also how the information visualization community as a whole is responding to its ideas and incorporating them in to the existing infovis domain.

To clarify that last point, I’ll start by saying that, as a first-time attendee of the InfoVis conference, I was quite surprised by the type of visualization discourse that dominated the event and, by extension, the infovis community that it represents. The outstanding impression I got from this conference is that the majority of research being done in the field of information visualization is focused on the technical details of designing visualizations (layout algorithms, data management, etc.), and is driven by a methodology that emphasizes a traditional scientific approach to this research. In other words, it presents itself (to this admittedly na├»ve observer) primarily as a branch of computer science, obviously reflecting and reinforcing its origins in that field.

That said, my exposure to the field originally came through my work developing interactive scientific visualizations for educational purposes (teaching principles of physics and biology to undergrads and high school students), the design of which focused primarily on supporting informal learning rather than, or in addition to, “focused episodes of work” (to borrow a term from Pousman, et al.). Though these educational tools were often used to help solve specific problems, we were more concerned with making them approachable to non-experts and promoting a casual exploratory usage model. As I began to study information visualization, most of my encounters with it have come through the internet, and though I’ve read most of the “bible” texts of the field that are clearly representative of the “computer science” approach, the “live,” publicly available, high-profile examples of infovis that you typically see on the net would generally be characterized as “casual infovis,” or “information aesthetics,” or “data art,” or whatever you want to call it. This would include systems and tools like Many Eyes, the Baby Name Voyager, the ubiquitous work of design firms like Stamen Design, the various visual web search tools like TouchGraph, art projects like, probably some business intelligence related visualizations like the Map of the Market, and even advertising-related infovis like the now defunct Coca-Cola WorldChill visualization (there are of course many more examples, these are just the ones I can think of off the top of my head). So, going in to the conference, my impression was that visualizations like these, regardless of the quality of their implementation, represented a legitimate area of study within the field of “information visualization.”

As it turns out, though, it appears that most of these examples probably wouldn’t be considered “information visualization” by the “information visualization” community represented by the InfoVis conference, presumably because, for the most part, they aren’t designed as tools with which you do rigorous analytic work. I saw a lot of evidence for this (which I’ll get to below), but it was most explicitly stated by Stephen Few in his capstone presentation: Stephen pointed to these kinds of examples on the web (in addition to some that I agreed were legitimately horrifying) as presenting a “primitive,” misleading view of what “information visualization” is, and suggested that it was the job of the conference attendees to be “model thinkers and communicators” that “take up residence in the real world” to show the “outsiders” what infovis is really all about. And this was framed as one of the more progressive viewpoints on visualization at InfoVis.

What was also surprising to me, based on the panels and presentations that explicitly addressed the idea of popular visualization, was that there didn’t seem to be much agreement on what “infovis for the masses” even referred to, or what its concerns should be. After the recap of the keynote below, the following posts are my observations on how this played out in the various related panels.

I already discussed Matthew Ericson’s Sunday morning keynote on info-graphics at the New York Times, so I won’t say much more about it other than reiterating how useful I thought it was. Matt described a design process that was very much “in the trenches,” emphasizing the special considerations that need to be made when designing for a mass, non-expert audience (i.e. readers of the New York Times). This included their development of a vernacular theory of visualization design that at times broke with what traditional infovis theory would suggest; examples included his observation that scatter-plots tend to confuse non-expert readers, because they are not familiar with graphs in which time is not on the x-axis. He also stressed the value of embedding of text annotations into their graphics to help guide a user through the data – something that a Tuftean purist might consider chartjunk. I was very impressed with his presentation and was happy to have a chance to speak with him afterwards.

InfoVis impressions, part 2: "Infovis for the Masses."
InfoVis impressions, part 3: "The Impact of Social Data Visualization."
InfoVis impressions, part 4: "Infovis as Seen by the World Out There."