Juice Analytics

Freedom in the 50 States is a very nice site showing how states compare along a variety of measures of freedom. Included in the list are your freedom to gamble, smoke marijuana, drink alcohol, have bachelor parties, and shoot off fireworks and guns. Note: please do not exercise all your freedoms at once.

The colored map and detailed drill-down show 37 measures, yet they forgot to include one important freedom: your freedom to communicate data with ease and create interactive infographics in minutes. Don’t worry, we’ve got a heaping-helping of info-liberation. So before you send an angry e-mail to your congressman, take a look at what we put together with Slice in under an hour:

Like the Freedom site, we want users to be able to choose a metric and be able to see which states are freedom-loving and which are freedom-hating (I’m look at you, South Dakota, with your anti-bachelor party policies). That’s our new “map slice” in action, which can color states based on our data or overlay colored bubbles to visualize locations.

To add even more data exploring fun, we created a visualization to let you compare two states side by side.  Check out how North Dakota totally dominates California on freedoms.

Having flexed my information visualization freedom muscles, I’m off to ride my bike without a helmet while drinking a 32-ounce soda.

This week we are conducting a series of free (yes, free!) webinars to show how super easy it is to create an interactive, online report with Slice. You (yes, you!) are invited. If you don’t think you have enough time…that’s our very point. You probably don’t have time to keep building those giant PowerPoint decks full for charts or 15Mb Excel reports. Spend a  little time with us, save a bunch of time with Slice.

Choose a time below and sign up to watch our live webinar.

For the East-coast lunch-eating friends: May 1, 2013 12:00 PM EDT

For our West-coast lunch-eating friends: May 2, 2013 3:00 PM EDT

From Edward Tufte’s Visual Explanations, a diagram based on Salman Rushdie‘s description of the Indian epid Kathasaritsagara or Ocean of the Streams of Story.

The hot new concept in data visualization is “data storytelling”; some are calling it the next evolution of visualization (I’m one of them). However, we’re early in the discussion and there are more questions than answers:

• Is data storytelling more than a catchy phrase?
• Where does data storytelling fit into the broader landscape of data exploration, visualization, and presentation?
• How can the traditional tools of storytelling improve how we communicate with data?
• Is it more about story-telling or story-finding?

Many of the bright minds in the data visualization field have started to tackle these questions — and it is something that we’ve been exploring at Juice in our work. Below you’ll find a collection of some of the best blog posts, presentations, research papers, and other resources that take on this topic.

Note: I’ve excluded a lot of excellent sites and articles that use the phase data storytelling, but treat it as fresh way to talk about data visualization.

1. Blog Posts

Storytelling with Data: What Are the Impacts on the Audience? by Nick Diakopoulos
“I realize there’s a whole lot of inspiration out there, and some damn fine examples of great work, but I still find it hard to get a sense of direction…We need to know what makes a data story “work”. And what does a data story that “works” even mean?”

A Data Scientist’s Real Job: Storytelling by Jeff Bladt and Bob Filbin
“In short, we’re tasked with transforming data into directives. Good analysis parses numerical outputs into an understanding of the organization. We “humanize” the data by turning raw numbers into a story about our performance.”

Coffee & Empathy: Why data without a soul is meaningless by Om Malik
“The idea of combining data, emotion and empathy as part of a narrative is something every company — old, new, young and mature — has to internalize. If they don’t, they will find themselves on the wrong side of history.”

Look ma, no story! by Moritz Stefaner
“Tools have no stories to them. Tools can reveal stories, help us tell stories, but they are neither the story itself nor the storyteller. Portraits have no story to them either. Like a photo portrait of a person, a visualization portrait of a data set can allow you to capture many facets of a bigger whole, but there is not a single story there, either.”

Discussion: Storytelling and success stories by Andy Kirk
“I just wanted to share my view on the distinction I personally make between the two main types of visualisation function: exploratory and explanatory”

The secret to storytelling is in the editing by Garr Reynolds
“Although it is a film about the role of editing in filmmaking, the lessons and principles are applicable to other creative work such as writing, and storytelling of all kinds, including presentations.”

Visualising data: can you see stories? by Chris Twigg
“Narrative can on the one hand be broken down into a set of universal laws and principles that may transcend mediums. Stories have temporality in common (they deal with time) as well as causation (they deal with cause and effect of something). On the other hand there are the more media specific narrative affordances as for example in the way that film, opera, novel and data visualisation – because of their physicality and the dimensions open to them – would be able to give a different ‘staging’ of a story.”

Data Visualization as Storytelling: A Stretched Analogy by Zach Gemignani
“For practitioners of the craft, connecting our work to stories feels satisfying — it is a call to raise our standards and an opportunity to enhance the influence of our field. Stories evoke images of rapt audiences, dramatic arcs, and unexpected plot twists. Unfortunately this analogy is a stretch.”

Why good storytelling helps you design great products by Braden Kowitz
“It’s not uncommon for designers to confuse a beautiful looking product with one that works beautifully. A great technique for creating smarter, better products is to approach them using story-centered design.”

How might rhetoric inform information design? (Quora) and related blog post by Stewart McCoy

2. Presentations

How to Tell Stories with Data (Really) by Edward Segal
PDF version

Visualising Workflow: Findings Stories and Telling Stories by Andy Kirk

Storytelling with data visualization: Questions and challenges by Albert Cairo

Storytelling with Data by Jonathan Corum

3. Research Papers

Visualization Rhetoric: Framing Effects in Narrative Visualization by Nick Diakopoulos (Summary, Research Paper)
“We carefully analyzed 51 narrative visualizations and constructed a taxonomy of rhetorical techniques we found being used. We observed rhetorical techniques being employed at four different editorial layers of a visualization: data, visual representation, annotations, and interactivity. The five main classes of rhetoric we found being used include: information access (e.g. how data is omitted or aggregated), provenance (e.g. how data sources are explained and how uncertainty is shown), mapping (e.g. the use of visual metaphor), linguistic techniques (e.g. irony or apostrophe), and procedural rhetoric (e.g. how default views anchor interpretation).”

Narrative Visualization: Telling Stories with Data by E. Segel and J. Heer
(Abstract, Research Paper)
“We systematically review the design space of this emerging class of visualizations. Drawing on case studies from news media to visualization research, we identify distinct genres of narrative visualization. We characterize these design differences, together with interactivity and messaging, in terms of the balance between the narrative flow intended by the author (imposed by graphical elements and the interface) and story discovery on the part of the reader (often through interactive exploration).”

Storytelling: The Next Step for Visualization by Robert Kosara and Jack Mackinlay
“Presentation and communication of data have so far played a minor role in visualization research, with most work focused on exploration and analysis. We propose that presentation, in particular using elements from storytelling, is the next logical step and should be a research focus of at least equal importance as each of the other two.”

What Storytelling Can Do for Information Visualization (PDF) by Nahum Gershon and Ward Page
“Effective presentations using the storytelling approach require skills like those familiar to movie directors, beyond a technical expert’s knowledge of computer engineering and science. Creating a presentation is not just a matter of being literate in visual media and storytelling but depends on a frame of mind that caters to other modes of human information processing and thinking.”

The Enchanted Imagination: Storytelling’s Power to Entrance Listeners
“While storytelling has flourished, there has not been a concomitant surge in research of the art form. One element of storytelling has remained nearly unconsidered, and it is, perhaps, the most profound and influential characteristic of storytelling: its power to entrance those who listen.”

4. Tools, Examples, and Other Resources

Hans Rosling’s TED Talks
“What sets Rosling apart isn’t just his apt observations of broad social and economic trends, but the stunning way he presents them. Guaranteed: You’ve never seen data presented like this. By any logic, a presentation that tracks global health and poverty trends should be, in a word: boring. But in Rosling’s hands, data sings. Trends come to life. And the big picture — usually hazy at best — snaps into sharp focus.”

Robert McKee, Godfather of Storytelling (Wikipedia)
Rather than simply handling “mechanical” aspects of fiction technique such as plot or dialogue taken individually, McKee examines the narrative structure of a work and what makes the story compelling or not. This could work equally as well as an analysis of any other genre or form of narrative, whether in screenplay or any other form, and could also encompass nonfiction works as long as they attempt to “tell a story”.

Stories Through Data
Exploring storytelling in data visualization. A collection of visualizations sorted by Chris Twigg’s narrative analysis framework.

13pt Information Graphics
Gallery of examples from the studio of Jonathan Corum, an information designer and science graphics editor at The New York Times.

A free and collaborative taxonomy of Data Storytelling tools by Philippe Nieuwbourg
“To summarize my investigations around data storytelling tools I created a mind map. This map will be an up-to-date taxonomy / ontology / typology, of software available on the market, to create stories around data.”

DataStorytelling.tv
“An independent website, dedicated to storytelling around data.”

Pixar’s 22 Rules of Storytelling
“Give your characters opinions. Passive/malleable might seem likable to you as you write, but it’s poison to the audience.”

Bob Beamon’s Long Olympic Shadow by Kevin Quealy and Graham Roberts (NYT)

Good data communication hinges on picking right chart. The patterns and insights almost magically emerge when you choose a chart or visualization that emphasizes the important elements in your data. Unfortunately, this is one of the biggest struggles for inexperienced presenters of data.

I don’t like to knock our own stuff, but a little healthy introspection is always a good thing. Consider our popular ChartChooser tool. In spite of it’s carefully crafted name (it was core of an ad campaign akin to peanut butter: Choosy chart choosers choose ChartChooser — no, not really), we’ve come to believe that ChartChooser isn’t so useful for the “Chooser” part; it is useful because the “Chart” part is nicely formatted, downloadable PowerPoint and Excel charts.

Here are the filtering choices for ChartChooser:

I’ve been at this a while and I still don’t always know how to connect what I’m trying to express with words as vague and broad as ‘Composition’ or ‘Relationship’.

It isn’t entirely ChartChooser’s fault. Basic chart types are by nature broad and flexible in their usage. How can we make it easier for someone to make that leap from their question to a visualization that best answers it?

We believe one part of the solution is to make visualizations more purposeful. That is, create re-usable ways of expressing data that are carefully designed to answer common questions that people pose about their data.

While it’s true that everyone’s data is unique, what we’ve learned is that in most cases, the things they want to know about their data aren’t so unique. The same sets of question patterns show up time after time. It’s almost like a game of Mad Libs:

• Which are my top performing _plural noun_?
• Which _plural noun_ are the most significant outliers when measured by _ measure_ and _ measure_?
• Which _plural noun_ have improved or declined the most over the last _time period_?
• How does _singular noun_ compare to _singular noun_ across my important performance measures?

Our goal is to draw straight, obvious lines between questions like these and a visualization that directly and simply expresses an answer.

If you consider the last data Mad Lib question above, our match-up visualization is a good example: compare two things side by side to see relative performance. The Match-up was inspired by the traditional tale-of-the-tape graphics that you used to see in boxing matches.

Like a lot of our visualizations in Slice, we’ve added a number of key features that really help the user quickly understand and explore the data. Here are a couple examples:

We’ve put together a whole collection of these purposeful visualizations, such as a funnel visualization for sales conversions and other processes; a leaderboard for ranking top items across a bunch of measures (try it free here), and a comments visualization for reviewing and exploring survey verbatims, tweets, and other descriptions. And we’ll be making more. What questions do you ask of your data?

Over the years you’ve seen a few blog posts from the Juice Team on football, the American variety. We thought it made sense to give the world’s most popular version of football a little love since the Major League Soccer (MLS) season just got underway.

As we started our journey to pay tribute to the beautiful game, we came to realize much like the recent Sloan Sports Analytics Conference that fútbol is just starting to get its data on. Check out this view of team performance created in Slice.

This data comes from the MLS Soccer Team Stats page.

The Tournament is upon us. And if you know about picking a brackets, you know it comes down to match-ups, strong guard play, and choosing at least one 12-seed to beat a 5-seed. You also know the winner of your office pool will inevitably be that one non-basketball fan who picks teams based on mascots.

Since we’re bound for disappointment, why not have some fun with data. Our resident Iona grad, Michel, put together this slick Sliceboard that ranks the tournament teams by offensive and defensive stats. Notice how his school pours in 81 points a game as the 2nd most prolific offense in the tournament. They also manage to have the 2nd worst defense. Sorry Michel, defense wins Championships.

Dashboards can be dull. Four or six charts laid out in a grid. All data, no explanation or logical flow. In our white paper on dashboard design (PDF), I got a little perturbed at this model because it offers so little guidance to the reader.

In hopes of sparking some new thinking, here are a half-dozen dashboards that demonstrate innovative designs and features.

1. ThinkUp: Dashboard as News Feed

This clever social media dashboard focuses on the changes and news-worth data updates. Each timeline element that flows down the page can be expanded to show details that supports the headlines.

2. SumAll: Trends, annotations, and goals

SumAll’s recently released tool for trended business data is beautiful in its execution. The interface puts multiple metrics on the same chart to make it easy to see how trends correlate to each other (even though they are on different scale). SumAll does a nice job with allowing user-created comments, setting goals, and anticipating how users will want to read the data. If you design dashboards, it is worth signing up to absorb some of the nice design touches.

3. AppFirst DevOps Dashboard: Key metric trends and thresholds

This dashboard is a more traditional real-time operations dashboard. It shows all the key metrics together along with trends relative to goals.  AppFirst has some nice features that you can see in the video including 1) dropping metrics one on top of another to see correlated trends and, 2) “smart thresholds” to highlight points in the historical trends when the metric fell out of an acceptable range.

4. Analysis-One: Creative layout for easy comprehension

Many stoplight-style dashboards can be jarring to look at. This radial approach provides the high-level performance warnings in a subtle and pleasing way.

5. Square: Filtering

Mike Bostock of D3.js fame is the brains behind this dashboard for Square’s retail sales. He used his Crossfilter approach for super simple and fluid filtering.

6. Tweetping and Tron, the Movie show us dashboards of the future.

If you want to build a dashboard with a style that will still work 20 years from now, check out the dark backgrounds, tiny fonts, and animation in these dashboards.

Tweetping

Tron Dashboard

If you’re interested in more well-designed dashboards, Quora has a good discussion on the topic here.

For a famous person, Edward Tufte is adept at avoiding the papparazzi. You probably know this iconic Tufte teaching picture. But it is pretty hard to find another picture of him.

Until now. The clever folks at AdAgeStat were able to get a shot (undoubtably with a bowtie camera) of Tufte for an interview on their AdAgeStat blog.

Tufte in full color

The interview is worth a read. It covers some of the typical Tufte hobby-horses, like this rant about PowerPoint:

“PowerPoint benefits the bottom 10% of presenters by forcing them to have points, some points … any points at all. And the best 10% of presenters have such good content, style and self-awareness that PowerPoint does little damage. PowerPoint should be used solely as a projector operating system to show 100% content, without the bullet grunts, logos and the formatting nonsense from the Strategic Communications Department, and the $20 million Pentagram corporate format guidelines.”

That stuff aside, there were some great nuggets about data presentation. For example his take on presenters and credibility:

“Presenters need (1) to tell a coherent story and (2) to convince their audience of their credibility. A good way to gain credibility is not to have lied to the same audience last month. Another is to demonstrate that you are not a cherry picker, basing your case on evidence selection rather that on evidence. Another necessity is to demonstrate your mastery of detail.”

In my experience, providing your audience with some (limited) flexibility to interact with the data is a great mechanism for building credibility. Have the confidence to allow access to more than cherrypicked data and you won’t come across as manipulative.

Tufte pushes back on the notion of being “overwhelmed by data” by saying:

“Overload, clutter, and confusion are not attributes of information, they are failures of design. So if something is cluttered, fix your design, don’t throw out information. If something is confusing, don’t blame your victim — the audience — instead, fix the design.”

In the world of business intelligence and reporting software, there isn’t a lot of empathy with audiences. The focus is squarely on the user trying to create something, not the reader trying to understand the content.

Finally, he hits on a seldom-discussed gap in data analysis by noting that “good content reasoners and presenters are rare, designers are not.”

In conversations with people like Andrew Abela and Nancy Duarte, we’ve thought a lot about how tools can help people better present data. In the end, it is still a very human art form to synthesize understanding about a problem and construct a logical argument or story around it. Tools can only help facilitate and guide the process. That’s what we are trying to do with Slice.

This weekend is the start of the NFL Combine. It is where roughly 300 of the top college football players show off the physical prowess, strength, speed, agility to NFL teams to help their status in the upcoming April draft.

In case you end up catching a glance of the festivities and want to know a little bit more about the players, below you’ll find a few visualizations that might help you learn a little about that player from Lehigh or the guy who did 38 bench presses of 225 lbs.

Use the search capability on each of these to find the player, position, conference or grade that you want to learn more about. We grabbed the data from NFL.com and CBSsports.com. Enjoy!

Leaderboard: Ranks players across multiple measures.

Comment View: Read quick summaries of players

Table: Search, sort, and find player details

Ok, we’re gonna take an informal survey. Raise your hand if you’ve ever experienced this:

You’re sitting through yet another dull, data-heavy presentation packed full of repetitive charts. A question gets raised, and the presenter flips furiously to find a relevant chart on page 53. A colleague squints at a dense table of numbers, wondering what it all means.

We’ve all been there. And oh! how painful. Too many times we’ve seen the aftermath of the indiscriminate boardroom presentation bore-athons. Well, it’s time to make it stop!

As a result, we at Juice challenged ourselves to find a way for ordinary business folks to create engaging, interactive presentations that leave the dreary days of Death by PowerPoint behind and bring new life to the data-presentation experience. Our solution is called Slice.

Over the last year we’ve worked with dozens of organizations to refine and enhance how Slice works. Our customers come from a diverse array of industries, from research organizations to healthcare service providers to advertising agencies.

Here’s what we learned. There are many great data analysis tools out there like Tableau for ad hoc analysis, SAS and R for statisticians, and a myriad of others. However, we’ve heard repeatedly from real users that these tools fall flat on helping people become data presenters.

Slice solves that data presentation problem.

Once you’ve done the analysis and you know what to communicate, packaging the results in the proper way is critical. But, to do it right

• You want the design to be striking, but you’re not a designer;
• You want engaging interactivity, but you’re not a developer and the IT wait list is overflowing;
• You might cobble something together using Excel and PowerPoint, but mediocrity is not what you’re looking for.

Slice removes these constraints by focussing on the last mile of business intelligence: presenting data with the visual precision, interactivity and excellence in a way that sparks engagement.

We are really excited about how Slice makes a difference for people who have struggled too long with delivering data-rich presentations or reports. Interested in seeing the advantage Slice can give you? We’ve just released a new version and we’d be happy to set you up with a 30-day trial. Go to our Slice page, fill out the form, and we’ll be in touch.