Mind the gap: Advocacy journalism fills a void

By now, it’s safe to say that the digital ecosystem is shaking things up for journalists. Traditional journalists are turning into brands (Ezra Klein, Vox and Nate Silver, 538, to name a few). Journalists are getting paid for clicks. Social media tools are creating a new breed of reporting through conflict journalism and citizen journalists—coverage that bleeds into news reporting and advocacy. And mission-driven social media sites (like Upworthy) are partnering with advocacy organizations to create serious, in-depth original content, as the Nieman Journalism Lab reported last month. Phew.

Mind the gap: Advocacy journalism fills a void

And now advocacy organizations are getting into the mix. They’re taking the reins by exposing, researching and writing about the issues they care about in a genre of journalism known as advocacy journalism. Advocacy journalism has been around for a while (remember muckraking?). But today’s digital landscape seems ripe for innovation by those that want to take the genre further.

A recent article by Dan Gillmor in Slate’s Future tense project provides a thought-provoking and current look at the nexus of advocacy and journalism today, one that made me want to dig a little deeper into the subject to see where the field is at and what hurdles it faces.

Advocacy journalism is an interesting genre. On the one hand, it seems like a big deal—by injecting a point of view, it appears, at first blush, to upend the sacrosanct “objective reporting” model that is the foundation of traditional journalism. But in fact, today’s so-called traditional journalism is itself rife with points of view (reporters are human, after all, and routinely bring their personal perspectives to the questions they ask and the subjects they cover).

It’s no coincidence that, at the same time as advocacy journalism is getting more attention, investigative reporting in traditional media—the bread and butter of deep, immersive journalism—is diminishing due to shrinking newsroom budgets, capacity, and interest. (The American Journalism Review wrote about it in 2010, and things don’t look that much rosier if you read about revenues and ad dollars in Pew Research Center’s State of the News Media, 2014 report or the internet marketing firm Vocus’s 2014 State of the Media.)

So, resources for investigative reporting in traditional media may be diminishing, but the need itself certainly hasn’t. The immediacy of the internet and social media reporting make the gaps left by traditional news organizations more transparent than ever before. It has opened up the playing field for those who want, and need, to write about social change, and see advocacy journalism as yet another tool for driving that change. It is here that advocacy organizations are stepping in.

Gillmor mentions the Upworthy partnership with Human Rights Watch, Climate Nexus and ProPublica, but he also reminds us of the work of the libertarian Cato Institute, and the ACLU, noting that these organizations are not just writing about their issues—they have invested in hiring talented, investigative journalists to do the work.

One of my earlier posts this year discusses how advocacy organizations are harnessing social media to effect social change on their own terms (I wrote about the MIT Center for Civic Media’s study of the media coverage of the Travyon Martin tragedy, and of how it was framed and defined in part by digital-savvy advocacy organizations). In the same way, advocacy organizations are equipping themselves with investigative journalists to define the things that need fixing in our society, again, on their own terms.

Transparency and bias concerns apply to all reporting, not just advocacy journalism

As with any form of journalism (see a post that I wrote about the importance of trusted messengers correctly reporting the facts), there are always legitimate concerns around the ability of the “reporter” to be transparent about the perspective and bias that he or she brings to a story, especially when money comes into the picture (for example, a journalist embedded in an advocacy organization writing about an issue that is driven by a funder). But one can easily make the argument that journalism has never been immune to this predicament. Media brands are, after all, owned by corporations—remember Michael Bloomberg’s takeover of his newsroom and Murdoch’s editorial biases? The issue is not so much that money is paying for journalism (it always has). Rather, the issue is one of transparency and fairness (something Gillmor acknowledges in his online book, Mediactive).

Most recently, advocacy journalism was roundly dismissed by Buzzfeed’s Editor-in-Chief Ben Smith. When Eric Hippeau, a venture capitalist (and early investor in Buzzfeed), sat on a panel at the Columbia School of Journalism and asked Smith about the fine line between different forms of journalism and advocacy, Smith responded, “Um, yeah, I hate advocacy. Partly because I think, you know, telling people to be outraged about something is the least useful thing in the world.” (The video is here and and a good article with more on Buzzfeed is here.)

That’s kind of ironic given Buzzfeed’s public missteps and its association with the Koch brothers on the issue of immigration reform. I’m not saying that the partnership is in and of itself a concern (Slate’s Dave Weigel described it as a “pro-immigration reform” panel that was very much in keeping with the Koch brothers’ longstanding interest in the issue). But the association is not one to be ignored, either, particularly from a man who claims to hate advocacy. I’m still coming around to the idea that “Buzzfeed” and “journalism” can be conjoined. I don’t say that to be snarky—I say that to mean that all lines are blurring, including newstainment sites like Buzzfeed that are reinventing themselves in the digital journalism mold, whatever that is.

Medialens has a good take on the back-and-forth skepticism around advocacy journalism (“All Journalism is ‘Advocacy Journalism’ ”) and offers some clear-eyed perspective by pointing to numerous examples of how ‘non’ advocacy journalism exhibits bias (ranging from uber-left Ira Glass’s omission of the U.S. role in Guatemalan genocide to Jeff Bezos’s 2013 purchase of the Washington Post alongside Amazon’s $600 million cloud-computing deal with the CIA—on the heels of its decision to stop hosting WikiLeaks in 2010).

Journalism is changing: traditional media gatekeepers are going away

As Gillmor points out (and as I’ve written written previously), back in the day, traditional media were largely gatekeepers to reporting. If you were an advocate or an organization with a story and a point of view, you had to get a reporter’s interest and rely on that person to pitch it to an editor. To stand the best chance of success, you had to do the research, get the facts straight, frame the narrative, and package it up so that a reporter could understand it, pick it up, and pitch it. Those days are disappearing, and in their place is a new frontier of blurry gray lines of people and perspectives, all vying for a chance to shape the news agenda of the next hour. Investigative reporting is what gives all of us perspective, makes us take a collective deep breath, and think beyond that next hour.

It’s unsettling, but also an opportunity to fill in the gaps left by the old guard, as long we do it right. So, what’s right?

Doing it right: some things should never change

I recall reading (and tweeting) about Upworthy’s announcement when I read Nieman Lab’s post last month. Given that I work in a policy and advocacy organization that has a keen interest in seeing its point of view accurately and widely expressed in the media, I myself wondered how we could inject ourselves into a similar partnership. And, if we could, what we would say, how we would separate our social passion from the hard and complicated truths that spell out complex political realities? For me, it raised more questions than I could answer. But it’s tremendously exciting to see where others are going.

I’ll be curious to see how (or if) these partnerships help fill the void left by the diminished investment in investigative reporting in traditional newsrooms. And I’m also eager to see what new best practices emerge as a result. But regardless of how things change, the responsibility of transparency has never been greater. And all of these changes add up to the same principles that should never, ever change in journalism—report the facts, be clear and transparent about your point of view, and tell people where your money is coming from.

Dataviz is not a one-way street: fostering critical thinkers

Last year, I wrote two posts about the important editorial role that the designer plays in visualizing data (you can read them here and here). This week, Moritz Stefaner did a much more eloquent (and concise) job of underscoring the sensibility and the responsibility of the designer in crafting a data visualization.

But what I found particularly insightful about Mr. Stefaner’s post is his different characterization of what many of us (including me) typically describe as “telling the story” through data. He challenges that oft-used paradigm and, instead, offers a more compelling mode–the participatory, audience-driven cognitive experience that is the true power of data visualization. To me, this is what I found the most compelling, the power that data visualizations have to create a community of critical thinkers.

The story-telling model, according to Mr. Stefaner, is a one-way street that invokes a limiting, linear “start here, end here” dynamic–one that ignores the true opportunities that data visualization presents. Mr. Stefaner’s more aspirational definition has the reader exploring and creating his/her own experiences through the visualization.

In hindsight, it makes so much sense, right? It’s the interactivity of data visualization beyond sorting, filtering, reading and reporting. Rather, it’s a way to respect and foster the intellectual curiosity of the reader, thus fostering a culture of critical thinkers who go behind the more passive consumption of being “told” a story.

Mr. Stefaner tells us that this is his motivation for creating rich, immersive projects, ones that turn his audiences into “fellow travelers,” as he calls them. I absolutely love this characterization, albeit to me, it is not without some challenges. For example, there are times when I find myself lost in a data visualization that is too complex. Rather than stimulate my intellectual curiosity and propel me deeper into that visualization, I find myself frustrated that I’m being left behind by the author/designer, that I’m missing something important. This isn’t what Mr. Stefaner is suggesting, but it’s worth noting nonetheless.

This is one of the best things that I’ve read in a while, and one I’ll remember.

Case study: creating a 50-state data visualization on elections administration

Ever wonder how well states are running their elections systems? Want to know which state rejects the highest number of absentee ballots? Or which state has the lowest voting time? And which state has the highest rate of disability- or illness-related voting problems?

A new interactive elections tool by The Pew Charitable Trusts (the Elections Performance Index) sheds some light on many of the issues that affect how well states administer the process of ensuring that their citizens have the ability to vote and to have those votes counted. Measuring these and other indicators (17 in all, count ‘em), Pew’s elections geeks (I was a part of the team) partnered with Pitch Interactive to develop a first-of-its-kind-tool to see how states fare. Today’s post is a quick take on how the project was created from a data visualization perspective.

Pew Election Performance Index interactive

Pew’s latest elections interactive: The Elections Performance Index

Lots of data here, folks. 50 states (and the District), two elections (2008 presidential and 2010 mid-term) and 17 ways to measure performance. Add to that the ability to allow viewers to make their own judgments–there is an overall score, for sure–but the beauty of this tool is that it allows users to slice and dice the data along some or all indicators, years and states to create custom views and rankings of the data.

You might already know about Pitch Interactive. They’re the developers who created the remarkably cool and techy interactive that tracks government-sponsored weapons/ammunition transactions for Google’s Chrome workshop (view this in Chrome) as well as static graphics like Popular Science’s Evolution of Innovation and Wired’s 24 hours of 311 calls in New York.

The data will dictate your approach to a good visualization

When we sat down with Pitch to kick around ideas for the elections interactive, we were initially inspired by Moritz Stefaner’s very elegant Your Better Life visualization, a tool that measures 11 indicators of quality of life in the 30-plus member countries of the Organization for Economic Cooperation and Development (OECD). Take a look–it’s a beautiful representation of data.

And though, initially, we thought that our interactive might go in the same direction, a deeper dive into the data proved otherwise. Comparing 30 countries along 11 indicators is very different than comparing 50 states plus DC, 17 indicators and 2 election cycles. Add to that the moving target of creating an algorithm to calculate indicators for different user-selected combinations, and you’ve got yourself a project.

After our interactive was live, I talked to Wesley Grubbs (founder and creative director at Pitch) about the project. I was interested in hearing about the hurdles that the data and design presented and how his creativity was challenged when working with the elections data. One of the first things that he recalled was the sheer quantity of data, and the complications of measuring indicators along very different election cycles. If this sounds too wonky, bear with me. Remember, one of the cool things about this interactive is that it allows you to see voter patterns (e.g., voter turnout) along two very different types of elections–mid-term elections (when many states elect their governors, their members of Congress and, in many cases, municipal elections) and the higher-profile presidential elections. Pitting these two against one another is a bit like comparing the proverbial apples and oranges. Voting patterns are dramatically different. (The highest rate of voter turnout in 2008–a presidential election–was 78.1 % in Minnesota. Compare that to the highest rate in the 2010 midterm election–56% for Maine, and you’ll see what I mean.)

Your audiences will influence your design

Another challenge early on was the tension between artistry and function. In an ideal world, the most beautiful thing is the most clear thing (an earlier post, “Should graphics be easy to understand?“, delves into this further). I remember reviewing the awesomeness behind Wes and his team’s early representations of the data. From my perspective as a designer, these were breathtakingly visual concepts that, to those who hung in there, served up beauty as well as clarity. But from a more pragmatic perspective, an analysis of our audience (policymakers and key influencers as well as members of the media and state election administration officials) revealed that the comfort-level with more abstract forms of visualizations was bound to be a mixed bag. Above all else, we needed to be clear and straightforward, getting to the data as quickly as possible.

Wes decided to do just that. “It’s funny,” he said. “We don’t often use bar graphs in our work. But in this case we asked, what’s the most basic way to do rankings? And we realized, it’s simple. You put things on top of one another. So what’s more basic than a bar chart?”

“We had to build trust–you can’t show sparkle balls flying across the screen to impress [your users]–you have to impress them with the data.”–Wesley Grubbs, Pitch Interactive

When I asked Wes how, at the time, he had felt about possibly letting go of some of the crazy creativity that led him to create the Google weapons/ammunitions graphic, he simply responded, “Well, yes, we do lots of cutting edge, wild and crazy stuff. In this case, however, a good developer is going to go where the data leads them. In addition, the audiences for this tool are journalists, academics, media–the range of tech-saavyness is very broad. We had to build trust–you can’t show sparkle balls flying across the screen to impress them–you have to impress them with the data.”

Turn your challenges into an asset

When we brought up the oft-cited concern around vertical space (“How long do you expect people to scroll for 50 states, Wes?”, I remember asking) his approach was straightforward: “Let’s blow up the bar chart and make it an intentional use of vertical space. Let’s make the user scroll–build that into the design instead of trying to cram everything above the fold.”

I think it worked. This is a terrific example of visualization experts who, responsibly, put the data and the end users above all else. “We could have wound up with a beautiful visualization that only some of our audiences understood,” says Wes. “We opted to design something accessible to everyone.”

How did Pitch build the Elections Performance Index tool?

Primarily using D3, a javascript library that many developers are now using for visualizations. It was not without its drawbacks, however. When I asked Wes about lessons learned, the first thing that he mentioned was the importance of understanding the impact of end-user technology on different programming languages. “D3 isn’t for everyone,” he notes. “Take a look at your users. What browsers are they using? The older stuff simply won’t work with many of the best tools of today. You have to scale back expectations at the beginning. The hardest part can be convincing organizations that the cutting-edge stuff requires modern technology and their users may not be in line with that. It’s all about the end user.”

Well, as an end user and a participant in the process I’m pleased. I hope you’ll agree to take the tool for a spin.

Building good infographics part 3: Design and execute

In the first article of this series, we discussed how good planning and team dynamics can make or break even the best design ideas for an info graphic.

In the second article, you learned how to bring together your data and your story into a solid sketch.

In this final part, I’ll cover presenting the concept to your team effectively, managing expectations, and executing the rest of the design process so that your designer doesn’t fire you.

Part 4: Pitch the concept sketch to your team.

Schedule another meeting. Buy more donuts. Bring your designer. Keep it low-key if you can.

Get buy-in and set expectations. Now is the time to present to the team. The nice thing about sketches is that they appear to be so informal that you can share them with people quickly–they allow you to reach out individually to take the temperature of the team if needed and make adjustments as you see fit. This iteration helps because, when you get down to the formal presentation of the sketch, you’ve already established a bit of buy-in (team dynamics permitting, of course).

Before you launch into the sketch, start with a step back to cover the major points from the kick-off meeting.

It may seem repetitive, especially if you just met a few days ago, but it helps ensure that everyone’s on the same page and, if not, identifies those issues quickly. There is nothing worse than launching into a presentation only to find out later that not everyone shares the same goals for the graphic.

Reiterate what you’re creating, who it’s for, how you expect they’ll use it, what they’ll likely want to hear, and how the graphic will support that. Sometimes, this is where things can really get bogged down. The meeting that you had a few days or weeks ago (you remember the one–everyone nodded and seemed to be in happy agreement) suddenly becomes a distant memory as stakeholders, faced with a concrete presentation and decision point, decide to begin reevaluating the goals, objectives and purpose of the graphic. Well, better now than later. When this happens to me, I’m grateful for it, to be frank. It’s pretty much a hallmark of busy teams (you can’t get them to focus until you have something in front of them) or new teams (those who haven’t worked together before, or who haven’t created data viz products before).

Sometimes the difficult conversations tell you more about the team than anything else. At any rate, it’s valuable.

If this happens to you, try to relax and take it in. Sometimes the difficult conversations tell you more about the team than anything else. At any rate, it’s valuable. It’ll give you a sense of the red flags to watch for later in the process. If the team is too indecisive, bring in senior managers, if you can, or summarize the issues they raise and simply state that decisions need to be made before moving further. Don’t be discouraged if you’re suddenly back to the drawing board. These things happen. A lot.

If the conversation is moving smoothly, it’s helpful to talk about the data.

Talk about the things that you expected to find that you confirmed (likely they’ll expect those things also). For example, “I knew that widgets were gaining ground in G20 countries.” And talk about the findings that surprised you. ”We talked about widgets gaining ground in our report, but when we looked at more data we saw the lead as slight, which belied our key message. So, to soften this, we added data about projected use for the next 8 years and were able to keep the message of increased widget-use.”

Sell your stakeholders on the problems and solutions that you encountered before getting into the nitty gritty of a sketch.

In other words, ensure that you have shared expectations about the graphic, then sell your stakeholders on the problems and solutions that you encountered before getting into the nitty gritty of a sketch. It’ll inform them and give them good perspective as they review. This sounds like a lot, but it’s important. In my experience, it can take anywhere from a few minutes with an experienced team to more than an hour.

Now, show the sketch(es). Pitch your concepts. Listen. Get people excited. Be open-minded (or, hell, just fake it). Listen, listen, and listen. When you’re not listening, ask questions. Have your designer on hand to participate with you.

Weighing the impact of team recommendations on scope and timing. Once the show and tell is over, talk about the production and design cycles in a general sense and, if you’re able (you’ll have to think on your feet), how the group’s feedback might affect the schedule and scope of the graphic.

Don’t speak for the designer if the designer is not there.

Be careful here–particularly if the designer (for whatever reason) is not part of the conversation. Don’t make assumptions about how easy or difficult it will be to implement a particular suggestion. What looks easy to you may take a long time to illustrate. What seems like a no-brainer idea may not be supported by the data. What seems like a good suggestion may have cascading effects on the design that only the designer can spot. When in doubt, be noncommittal.

Part 5: Keep iterating.

Once you’ve had these conversations, you can keep iterating the sketch as needed. Easy peasy, right? Sure. I usually allow for about 2-3 iterations of a sketch. More than that, and I like to put in a hard stop to bring the team back together to ensure that we’re not going off track. Each iteration should be more refined and have fewer issues. If you find yourself or your team continually revising or revisiting the same things, this may not be a good idea to execute as a graphic.

Part 6: Start illustrating and designing. When do you move from paper and pencil to design?

For me, once the structure, content and data are mostly locked down (this is what we want to say, in this order, this is the data we want to show, and this is how we want to show it) it’s safe to move to design.

  • Before you start designing, confirm that the data is final. Really, really final. Your designer will love you, you’ll save time, and you’ll make fewer mistakes.
  • Once in design, keep your design cycles lean and tight.
  • Remember all the work you put into the initial presentation discussions? Keep referring to the commitments that your team and reviewers made in terms of who sees what, when and how they’re allowed to influence the graphic. (Good luck with that.)
  • Follow best practices. Don’t force your designer to unnecessarily embellish in order to add visual appeal.
  • Again, if you find yourself or the team going through too many edits, stop. Revisit whether this project is feasible.

Understand the nature of edits, who’s making them, and why. Too many edits can be a result of:

  • Too many writers involved (or the wrong people suggesting edits).
  • Team members brought in to give feedback who were not made aware of the original goals, audience and dynamics of the project.
  • People (including the designer or project lead) who lack the necessary skills or experience.
  • Not enough of an overall direction given to team about what the graphic needs to accomplish, for whom and why.
  • Decision-makers not focused appropriately enough to give careful feedback (I notice this a lot when working with people who are very, very busy. You might see a lot of edits and back-and-forth when these folks aren’t able to focus on the product as a whole, and consequently keep “catching” things with each iteration.
  • The data changes.
  • Rushed timing. Assumptions are made about how long an graphic will take to produce by the wrong people.
  • Wrong assumptions made about how “easy” it is to create a graphic from repurposed content.

Part 7: Lessons learned.

No matter how successful or unsuccessful your first efforts, you can learn from them. How you impart those lessons to your team is the subject of another post. But suffice it to say that you should keep a close eye on what worked and what didn’t, and get at least an informal sense from all team members involved in order to refine your process and your team for the next time.

Well, that’s it. Go forth, enjoy, and make things easy to understand for the rest of us. And be nice to your designers.

A little bit of visual awesomeness from Visual.ly

On a weekly basis (if I’m lucky) one of the things that I find myself most in need of is a common area to find real-life examples of the best practices that we all try to follow. But talk is cheap and a little bit of visual awesomeness goes a long way so…

When Visual.ly announced its launch of a new social media platform for data viz designers, I danced my happy dance (perhaps prematurely, time will tell).

visual.ly - new social media platform for data viz

Why? Well, I don’t know how many of you often find yourselves swimming upstream and in the dark when it comes to sweet-talking clients out of ideas that you know are, em, well, sometimes just a wee bit unusual, not realistic, not good practice, a few branches short of a tree etc., etc.. If you are, then you also know how, though these conversations can sometimes be rewarding, oftentimes they are not (all recipients of puzzled looks or polite silence followed by the inevitable request to “do it anyway” or “can’t you just…” raise your hands).

I’m hoping that this new platform will give us quick access to quality examples of information design–solutions that illustrate a specific direction or idea that we’re trying to pitch to our teams, stakeholders and clients. Often I find myself scrambling to create comps to better prove or show a point. Nothing wrong with that, but if there’s a place where I can follow knowledgeable designers and their work rather than wading through Google searches or sites that warehouse images, I’m all for it (though where would I be without my favorite beer graphic?).

The Visual.ly social media platform, coupled with the excellent blogs out there (ranging from good critiques on the visual.ly blog, to case studies and reality checks by chartsnthings, as well as the usual suspects like the Guardian and Flowing Data and many more) is a damn good thing, and I’m excited to see this take off.

If we use this tool wisely and well, does that mean no more animated 3D piecharts?

How to choose the right chart (part two)

How timely. Last week I wrote about choosing the right chart. Juice Analytics recently created an interactive Chart Chooser, based on Andrew Abela’s original Chart Chooser decision chart (via FlowingData). Both tools are excellent and offer a great start to choosing the right chart/graph format for data. The interactive chart offers little in terms of best practices (it wasn’t designed to do that) but helpfully separates out different chart types by the data that you have (quantity, comparison, distribution, etc.). And the best part of the interactive is that it provides you with downloadable templates for both Excel and Powerpoint. I’ll try this and might write about how well it works for me in a business setting.

I actually like Andrew’s original (static) chart a little better, as I find the flow diagram does a nicer job of providing context for the decision-making process.

Put both of these things together and you’re off to a good start.

[UPDATE]: Read Naomi Robbin’s (Forbes) excellent counterpoint to the chart-by-menu mentality.

Andrew Abela Choosing a Good Chart

Andrew Abela’s original chart chooser tool

The joys and sorrows of concentric circle graphics

There are not many good examples of concentric circle graphics out there. La Nacion produced one last year about subway strikes, and The Guardian produced an interactive graphic on gay rights in the U.S. Both of these intrigued me because, in my day job, I produce endless variations of graphics dealing with 50-state data. And most of the time, when we look at 50-state data, we draw… you guessed it: maps. Or bar graphs showing quantity or line graphs showing changes and trends over time but no matter what we do, it involves data for the 50 states, most often over time. 50 states multiplied by several years is a lot of lines to draw, bars to fill and state maps to create. So I’ve been thinking about ways to tell the story in different formats–going beyond the map, so to speak. Last Wednesday, we created this concentric circle interactive. Here’s how we did it, and the process we took to decide on the format.

Stateline PCS jobs screenshot

One of the most onerous dimensions to 50-state data is the sheer physical size and length of the data. Our website used to allow for a content well of 500 pixels. Try shoving 50 state labels across 500 pixels and you’ll quickly see why it’s a challenge.

But even with all the real estate in the world, long, horizontal displays are also taxing on the user if there is a comparative aspect to the data. There is simply too much bouncing back and forth from the left to the right. Go long and you lose the comparative advantages of a horizontal layout because users with small screens must scroll vertically and can’t see the entire landscape at once. Of course, layering the data into different views as an interactive can solve that. But sometimes you want to show the data all at once. And for that, a static graphic can work well.

Understandably, a map is often the solution. But maps have their limitations too. There’s only so much that you can infer from a map. If your data consist of more than 4-5 gradations it can be tough to create the at-a-glance, concise overview for which a map is best suited.

And if there are no regional patterns discernible in your map, readers wind up staring at a jumble of color with only a legend to tie it all together.

Which brings me to concentric charts. They’re not pie charts (if you look up pie charts on wikipedia, you will see that there is a distant cousin to the pie chart called a “ring chart,” also known as a multi-level pie or a radial tree). These appear to be somewhat visually similar to concentric circle graphs but have a different use–they tend to show hierarchy in data–you might see these when your computer shows you how much disc space you have, for example.

Filelight disk usage graphic

This ring chart shows computer hard drive disk space

A concentric chart, on the other hand, can tell a different story altogether. In a recent post on La Nacion’s subway strike graphic, I mentioned how designer Florencia Abd manages to plot out a time across four nodes (year, month, day and time) as well as another variable–type of incident/strike. That’s a lot of ground to cover in a static graphic. Imagine doing it in other ways and I’m sure you’ll agree.

La Nacion Conflictos Bajo Tierra

Because a circle is, well, round, its shape lends itself quite well to a relationship-based approach. Not so much a pie-chart (where the user sees the parts in their physical relationship to the whole), but rather using the organic form of a circle to help the user more easily compare complex data. And if you add concentric circles, you take advantage of the hierarchy inherent to those circles to create layers–an intuitive way to order your data–perfect for showing levels or ratings where you use the inner and outer rings to denote the endpoints in a scale (e.g., one thing is stronger, larger or more intense on the outside than it is on the inside) or time, as the subway graphic above shows (the outer ring shows 5 a.m. and the inner ring shows 11 p.m.).

So, what does all this have to do with the U.S. map? As I mentioned, the strength of a map is to show geographic relationships in data. For example, southern states vote “red” (or conservative) in the U.S.; whereas a swath northeastern states might vote “blue” (progressive). For this, a map is helpful because regional differences tell the story and are easy to spot.

But the nice thing about concentric charts is that they, too, can show geography, or any groupings, for that matter. As the Guardian’s example shows, each “slice” of the concentric chart belongs to a state and groups of slices are regions. In the Guardian example, each ring (or level) of the chart denotes a particular right afforded to gay couples.

The Guardian gay rights in the US

My team took this in a different direction. We wanted to show states and regions as well. But we also wanted to show change over time, as well as intensity on a scale. So when the Bureau of Labor Statistics released its employment figures, we had a few choices. We needed to show how changes in employment have affected each state since the recession (from April, 2007 to April, 2012). Because the recession started in December, 2007, we wanted to show how employment looked in each state before the recession, during the recession and how (and which) states were pulling themselves out of the recession.

We could have created an interactive that showed how the same views above changed over time (presumably you’d see a pre-recession view showing states doing well, a recession view showing most states doing poorly, and post-recession years showing mixed results). The most valuable piece of this would be, of course, geographical patterns in the data, if they existed (how did the Rust Belt fare, or the East Coast, for example). You could overlay this with population or any other demographic data to tell an interesting story.

When we looked at the data, we saw that there were not very strong geographic patterns to show. So we decided to create a concentric chart. Why? Because we didn’t have geographic patterns, but we did have temporal patterns (most states did poorly during a particular period of time, which contrasted well with the mixed results that states showed as they were attempting to pull themselves out of the recession, at least in terms of their employment figures). And the fact that we used a circle meant that we didn’t have to create a very long or wide table or chart, and we could stray from the map approach.

We decided to make this a light interactive–by rolling your cursor over each state’s cell you can see a small bar graph showing change in employment over time. This worked for us because our goal wasn’t to show specific numbers (how much employment rose and fell in a particular state), but rather intensity and patterns over time.

The debate continues (check out the comments on Nathan Yau’s post on the Guardian graphic) on whether or not these concentric graphs are merely eye candy when a simple bar or line chart would do just as well. I would opine that, if used correctly, they work well. Let me know if you agree. Here’s a screenshot of our interactive, and you can view the live version here.

Stateline PCS jobs interactive

 

Staying fit through data visualizations

Better living through data visualizations? A new web app called “Spark” claims to improve your body through data viz. And art. And a gizmo called a fitbit. Whatever you call it, it’s both interesting and scary. If you have the time to spare (and, presumably, the calories), you can purchase the fitbit gizmo to track your every physical movement to help you get a very, very detailed sense of your physical activity throughout the seconds and minutes of your life. Really. People do this.

Okay, enough of that. What’s interesting is the use of data visualization to emotionally inspire people to keep moving, walking, jogging, or whatever people do who don’t have enough sense to ride a bike.

Upload your fitbit data (remember that’s the gizmo you have to purchase and presumably wetwire into the back of your skull) to your computer or tablet, log into “Spark” and you’ll be rewarded with piles of visualizations reflecting your activity level. In real time (using the fitbit API, Raphael and HTML5 Canvas). Please ignore the fact that Spark is hosted on a website with a url that begins with “QuantifiedSelf.com.” Apparently data vis is headed for greener pastures.

Sarcasm aside, Spark provides an interesting example of how data visualization can extend into nontraditional paths. More power to ‘em, I say.

Spark

 

Data Journalism Awards – whodunits in Spain, business in Brazil and bus subsidies in Argentina

Three solid entries from Spain, Brazil and Argentina are among the 58 nominees featured in the first-ever international competition for data journalism, the Data Journalism awards. The awards, announced by the Global Editors Network, will be announced on May 31. In the meantime, keep your eye on these three nominees:

La trama de la SGAE,” from El Mundo’s Spanish designer David Alameda, covers last year’s “Operation Saga,” an undercover investigation of fraudulent financial activities conducted by the president and other members of Spain’s influential Society of Authors and Editors (SGAE). This piece boils down the complex network of who gave money to whom, how much and when into one of the best examples of interactive flowcharts that I’ve seen. As with the best data visualizations, this interactive avoids the many common mis-steps that could have occurred through the overuse of photos, text, talking heads, etc. Instead, Alameda keeps his focus–and ours–on a tightly scripted interactive that guides the user quickly and efficiently through the web of financial whodunits.

La trama de la SGAE interactive

2011 Brazil State-Level Business Environment Ranking ranks the country’s business environment along eight categories (ranging from the political climate to innovation) and a series of indicators specific to each category. The interface is clean and simple to understand. Navigation, categories and indicators are well-prioritized and intuitive. One of my favorite features is the linked rollover behaviour between all four elements on the screen: a regional map, a deeper state-specific map, a regional bar graph and an overall scoring graph. A lot of information packed into a clean, well-designed interactive.

Brazil State-level business environment ranking

Lastly, Argentina’s La Nación is doing great stuff with open data. By my calculations, given that the country ranks sixth of 12 South American countries (and 92nd out of 142 economies globally, according to the recent Global Information and Technology Report’s Networked Readiness Index), this is a telling example of how Argentina’s relatively advanced use of information and communication technologies seem to be paying off, even if its government doesn’t always play along.

La Nación’s Subsidies for the Bus Transportation System is not so much a data visualization as a series of efforts to use open data to report on how bus subsidies in Argentina are being conducted. Dig a little and you’ll find a few good infographicsinvestigative pieces that detail a government’s efforts to be less than transparent about dollar figures, and an encouraging collaboration between the newspaper and Junar’s open data platform to create a Tableau dashboard that is beginning to circumvent Argentina’s lack of open data infrastructure. Interestingly, the newspaper compares its early efforts to the U.S.’s Freedom of Information Act laws and the American government’s data.gov platform. The dashboard presents a snapshot of indicators key to Argentina  (ranging from crime and accident rates to political indicators and legislative data). It’s a promising approach that may help other countries (like Bolivia) with similar challenges (see related article on Bolivia’s recent technology rankings).

La Nación open data dashboard

 

 

Etymologically speaking: a world interactive map

This interactive world map, created by Spanish data journalist and developer Chiqui Esteban, is fun, beautiful and informative even if etymology is not your bent. I’m going to spend way, way too much time on this map. Roll your cursor over the map to see a customizable, magnified view of each country’s name, and it’s English translation, ranging from Equalizer, to Chief Smith, to Land of the Enjoyers of Beautiful Things. I’ll let you figure out which those are, and ponder the sad irony of good intentions gone wrong, in many instances.

The World in Plain English - Interactive Map