Inspiration in the World of Data Viz

Learn two key concepts for ethical inspiration and acknowledging the source of your data viz ideas. By crediting original creators, you uphold respect and maintain originality in your work.

One of the great things about Tableau Public is that you can download other people’s vizzes to see how they were created or to create your own version. This feature has helped community members advance their understanding of Tableau, inspiring them to create new data visualizations. But how do you know when you’ve crossed the line from being “inspired” by someone’s work to “plagiarizing” their work?

Have you ever come across the phrase 'Steal Like an Artist'? It means drawing inspiration from peers to enrich one’s work, driving creativity through remixing and combining ideas. This concept is essential for artists, musicians, and data visualization professionals as it forms the basis of ethical creative practices. Similarly, 'Standing on the shoulders of giants,' a metaphor attributed to Sir Isaac Newton, highlights how our achievements are built upon the knowledge of those before us. Both ideas underscore the importance of learning from and acknowledging predecessors in the creative process. When you’re inspired by someone else’s work, you should always credit the original artist – and there’s a way to do that on Tableau Public!

Now, let's explore how to maintain these principles and ensure our visual storytelling remains original and respectful of others' work.

The difference between viz inspiration and plagiarism

“Plagiarism” is using someone else’s work and presenting it as your own. It can involve text, ideas, images, or other content. Not only is plagiarism unethical and dishonest, but it also hinders creativity and intellectual growth by stifling the development of original ideas. For example, if you download someone else’s viz and then publish it as your own without making many changes or crediting the original author, you may be viewed as plagiarizing.

“People often ask my advice about advancing their skills in Tableau and my answer is always to engage in the community. Following people on Tableau Public is a critical piece of this. There are now over 10 million vizzes on Tableau Public related to pretty much any topic you can imagine. There are thousands of people creating and sharing innovative techniques and designs. Tableau Public is an incredible place to learn and be inspired. But just like writing a college essay, it's important that what you build is yours and not someone else's. You have your own set of incredible skills and talents; show off YOUR talents, not someone else's, so that YOU are an inspiration to others.

“Inspiration”, on the other hand, is leveraging elements of an item or idea to create something new and unique. In data visualization, this could be taking specific ideas, styles, or methods and integrating them into your work with significant changes and personal touches. The end result should reflect creativity and originality while showing respect for the original source.

The critical difference is whether you’re building upon the original work and creating something new or simply copying it. If ever in doubt, the safest bet is to credit the original author. You can do this by listing the original author in the “Inspiration” field describing your viz. 

“When you give credit (via the inspiration field or other text or links on your viz), you’re not only doing the right thing—you're paying it forward to future learners by leaving a learning trail for others to follow.

Inspiration on Tableau Public

How did they create that viz on Tableau Public?

Have you tried reverse engineering or as Steve Wexler calls it “looking under the hood” of a  data visualization? This refers to the process of downloading, deconstructing, and analyzing someone else's work to understand its structure and principles. It’s a great way to learn Tableau or other tools. However, if you publish the work, you should credit the original author, as this is a crucial aspect of ethical creative practices.

Examples of vizzes on Tableau Public inspired by others

Below are several examples of visualizations published on Tableau Public inspired by other Tableau Public Authors.

RegionalSalesScorecard

Superstore Regional Sales Scorecard with Targets by Kevin Flerlage

The above Regional Sales Scorecard by Kevin Flerlage was inspired by Ellen Blackburn’s Consumer Duty Scorecard (below).

ConsumerDutyScorecard

Consumer Duty Scorecard by Ellen Blackburn

Another great example is Brittany Rosenau’s viz. She wanted to try out a new map projection for the #30DayChartChallenge and created the visualization below:

Fuel Prices by Brittany Rosenau

Fuel Prices April 4 2024 by Brittany Rosenau

Brittany had seen Agata Ketterick’s Cost of Childcare in the U.S. visualization (below), which was in turn inspired by Ademola Lapido’s County Median Home Prices visualization. Ademola learned the alternative map projection thanks to Kevin Flerlage, who wrote a detailed blog post on the topic with a shout-out to Sarah Battersy, the creator of the original shape files for these projections. This trail of citing sources demonstrates the immense power of building upon the work of others, and how beneficial leaving citations can be for others to learn and discover new techniques. It's a testament to the collaborative and innovative spirit of our community.

Child Care Costs Agata Ketterick

The Cost of Child Care in the US by Agata Ketterick


How to properly give credit for inspiration on Tableau Public

One of the Tableau Community Code of Conduct’s principles is to "Give credit where credit is due".

  • If your visualization is directly inspired by someone else’s, use the inspiration field on Tableau Public. You can add attribution to any visualizations you've published
  • If you share links to your visualization on social media—make sure you give a shoutout to those who inspired you. It’s all about recognizing and appreciating fellow community members.

“I always encourage people to give credit where it’s due, but being an empathetic person has given me the opportunity to understand and address instances where this doesn’t happen. It’s important to welcome, support, and encourage people to learn from each other. However, DataFam is not only about welcoming new members and spotlighting exceptional visualizations and creators but also about embodying compassion in our interactions.

Reviewing the above concepts shows how inspiration and originality can coexist. Ethical data visualization balances these, ensuring your work is unique while contributing to a thriving, innovative community. Join the Tableau Public community, learn from others, and always give proper credit. This keeps your work ethical, and also pays it forward by leaving a learning trail for future innovators.