Data Visualization: The Stolen Art

Data Visualization: The Stolen Art

Data Visualization The Stolen Art FeatureMake no mistake about it, data visualization is an art form. I always enjoy sharing the anecdote that I have created literally hundreds of data visualizations, and to this day, not a single one of them has been perfect to everyone that saw it. There is always feedback, criticisms, and ideas about how to do it better.

That’s perfectly okay with me. It tells me the audience is engaged and that my work has the opportunity to start a conversation around data. When the feedback is constructive, sometimes I get a better idea about how to do something; other times there were explicit reasons for my choices and I politely deflect. I don’t take any of it personally because art is in the eye of the beholder, and data visualization is an art.

I imagine that’s what makes so many of us passionate about honing our craft. After all, not every job or practice makes you willingly want to practice on weekends and share your work with the world. For many of us, data visualization is our calling because it is the perfect balance between the left and right sides of our brain. With the proliferation of tools that are making the work of data visualization practitioners public, combined with those practitioners pushing to evolve their work, there is one trend I’ve seen that we need to collectively consider…

 

Be Respectful Using Others Art to Enhance Your Own

The aspect of data visualization that I’ve been thinking about a lot lately is how much third party art has been integrated into public data visualizations. The topic has been on my mind for quite some time, but came to a head for me last week for two reasons.

First, there was a Makeover Monday about Donald Trump that featured many caricatures of his likeness. I’m not going to call out any specific pieces because I do not know the back story behind each one. Perhaps the art was purchased, the original artist provided permission to use their work in the data visualizations, or the data visualization author drew the cartoons themselves. However, I couldn’t help but wonder that unless the data visualization designer was resident Tableau cartoonist, Philip Riggs, that the art wasn’t original.

Makeover Monday is a phenomenal project started by Andy Cotgreave and Andy Kriebel (and now supported by Eva Murray) where one data visualization in the public domain is made over by a crowd of Tableau Public users each week. The program has given voices to many users and provided countless innovative ideas to learn from. I bring the topic of using others art to enhance your own up now in hopes that by being respectful, we will collectively maintain our credibility and maximize the opportunity to tell our stories.

The second thing that finally pushed me to say something is a recent Tableau Public Viz of the Day by André Oliveira featuring the art of Banksy. My first instinct was that there was no way it was okay to just copy and paste these valuable works into a Tableau Public visualization. That prompted me to research the artist, and it turns out I was wrong. Banksy does not copyright their work and allows it to be used as long as the person using it does not imply it is their own. (not to mention that Banksy will not pursue legal action so they can protect their identity).

Here’s a look at the respectful and very-well done Tableau Public visualization.

[Click image to view interactive data visualization]Banksy Roadmap Tableau Public Viz of the Day

Ironically, it turned out in this unique case that the third-party art was being applied appropriately. Banksy has the spirit of most Tableau Public authors who allow their work to be downloaded and borrowed from. While many of us have good intentions, we can’t assume that every artist is as open about sharing their work as Banksy.

I want to be clear that I am only asking the data visualization community to be respectful and consider the hard work that went into creating the original art before incorporating it into your own. I am not an intellectual property lawyer, and I think there are very few who are completely innocent; I know I certainly am not. As hard as I try to be respectful, I have received requests to alter my work to accommodate intellectual property rights. I have always happily complied as quickly as possible, and usually was not aware I was in violation. I don’t think I would be writing this if I didn’t have personal experience accidentally crossing the line. Sometimes images that appear in Google image results require licensing to share. Certain sports websites, even if they have league partnerships, do not use team logos. Even names of some sporting events cannot be used for commercial gains.

 

5 Tips for Integrating Others Art into Your Own

You may be wondering if it’s so easy to violate somebody else’s intellectual property rights, is there anything you can do to enhance your own data visualizations. Here are just a few ideas:

1. Ask permission. I cannot express this one enough. A lot of artists will happily allow you to share their work and incorporate it into your own as long as you’re giving credit where credit is due.

2. Legally purchase images from istockphoto.com. Many of the images you see on this site and throughout my data visualizations were purchased from iStock, and there is no shame in that. Using illustrations is a great way to professionally enhance your data visualizations, and you can do it the right way for as little as $12 per image. The standard license allows you to use the image online and print up to 500,000 impressions.

3. Use icons from The Noun Project. The Noun Project provides thousands of icons that you can use for free as long as you credit the source. For just $1.99, you can use the icon royalty free or for a subscription of $9.99 per month, you can use any of the icons royalty free. Hat tip to Lindsey Poulter for introducing me to this source of images.

4. Use silhouettes of images. I admit that this tip is grayer than the others, but there is legal precedence that outlines are not in violation of copyright law. I say this one is grayer because sometimes the original art is already a silhouette and should not be used without permission. The use of silhouettes have the extra advantage of making the imagery on a data visualization more iconic, and I always prefer simpler imagery. Here’s one example in my Jackie Robinson baseball statistics data visualization. Nobody owns the outline of Jackie Robinson sliding into a base because beyond being challenging to prove the outline is Jackie Robinson, it’s nearly impossible to prove which photograph was used to create the silhouette.

5. If you’re a Tableau Public user, leverage the licensing they already provide. There are 11 different shape palettes that come with every download of Tableau. These icons can be used for marks or navigation throughout your data visualizations. Tableau also comes with three different mapping styles, and you can use 14 custom Tableau map styles when integrating Mapbox.

Finally, if you are okay with people using and learning from your data visualizations, make it clear and easy for them to do so. Every single one of my Tableau data visualizations can be downloaded so you can reverse engineer them. I’m also happy for you to embed the visualizations in your own website or own examples. Links are appreciated, but I also embed credit within the visualizations.

Thanks for reading,
– Ryan


By | 2017-04-21T21:48:43+00:00 January 24th, 2017|Thoughts|