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Bringing Data to Life: Combining machine learning and art to tell a data story
- 1. Bringing data to life: Combining machine learning and art to tell a data story Nancy Rausch | 28 March, 2019
- 3. Jan Miense Molenaer, The Dentist, 1629
- 9. “art is a means of communication that goes far beyond language.” - Zehra Dogan “art is a means of communication that goes far beyond language.” - Zehra Dogan
- 13. Photo courtesy of MORE TH>N
- 16. Do we have a budget? nope! What would the art form be? digital art What data set would we use? Art – Data Story
- 21. Initial Sketches in Illustrator
- 22. 4’ x 33’ MicroTile wall
- 23. Oil, acrylic, pan pastel, charcoal, and pencil on primed paper. Same proportions to the MicroTile wall.
- 24. “.. to promote software literacy within the visual arts, and visual literacy within technology-related fields.“ - Processing Foundation
- 27. First digital sketch translating the concept into generative code.
- 28. Added transparency and a time temp orb
- 29. Total energy Time of day Temperature Four color schemes transition throughout the day as well. How the data is represented
- 30. Selected color schemes to represent the time of day
- 36. Steps 1. Tokenization 2. Sentiment Analysis 3. Normalization 4. Entity analysis 5. Dependency parsing 6. NLG response
- 37. Demonstration
- 38. Lesson Learned 1. Its takes a team 2. Don’t let the art get too abstract. Stick to representing the data 3. Engage more than just visually. It makes the art more compelling 4. This idea resonates…
- 39. THANK YOU Email: Nancy.Rausch@sas.com Twitter: @nrvelo1, @JessicaPeter
Notas do Editor
- This presentation describes how a group of us that work at SAS combined Machine Learning with Art to tell a data story.
- The setup: Have you ever had to convince someone to go to the dentist? I have adult children. I recently tried to convince them to go to a dentist without mom prompting them or setting up their appointments. I even showed them this data where they can see how they will lose their teeth if they don’t. Those teeth cost me a lot of money for braces and I don’t want them to lose them! But, the data did not convince them. Graphs just doesn’t do it.
- But, show them a picture and they change their mind.
- We are surrounded by data. It permeates most aspects of our lives.
- This plethora of data is teaching us amazing things, like where we have come from.
- And where we can go….
- We are crafting beautiful visualizations to try to explain what the data is trying to tell us.
- But there are people that are getting left behind in this data universe. Especially if the findings are difficult to understand or complex, such as in the output of complex machine learning algorithms.
- Could we use Art to help tell the story behind data?
- Art engages us.
- It inspires us.
- It teaches us and is approachable for all ages.
- And art even reaches across species boundaries. Here we are seeing a real art show for dogs! How many of you have pets that like to look out the window at the world around them?
- This is an example of marrying data with Art. This is the London eye on the eve of the original Brexit vote. The leavers are on the right and the remainers on the left. This art mesmerized a country, and the entire world. It was understandable and approachable.
- So, a few of us set out a couple of years ago to see if we could use art to tell a data story. That is Riley on the left, an amazingly talented graphics programmer. Jessica next to him. This was her original idea. She is our artist and our fearless leader. Then Susan, another incredibly talented artist, recently graduated from NC State University School of Design. And me on the right, as the data scientist. My job was to collect the data, analyze it, and identify an interesting analytical story to tell.
- Here is where we started. We didn’t have a budget to work with so that limited our art form to a digital piece. Digital art is easy because its just a matter of our programming time.
- For our data we turned to the SAS Solar Array, which is part of our company’s green initiative. Here you can see it with the sheep in the foreground. Remember the sheep, they are important!
- The data is fascinating, at least for me! Lots of interesting time series, a few data quality problems, temperature, weather. Very cool data!
- I showed this to Jessica and she immediately focused in on the sinusoidal aspects of this data. Her creativity was sparked!
- For inspiration we turned to other patterns in nature where you could see that shape, and other forms of energy. Water flowing over pebbles in the stream, wind flowing and moving clouds, wind energy powered through that element.
- Here are some of the initial sketches that Jessica came up with.
- Here is the medium we decided to present the final art piece on. This is in one of our campus buildings, and was showing at the time a static image. We were sure we could do better.
- Once we had a format for the piece, we could get to work. Jessica came up with designs in the right aspect ratio for the piece. Here are some of her sketches.
- Next we had to digitize the piece. For this we turned to an open source tool that is frequently used by animators and designers. Processing made it easy to digitize the designs into the shapes and patterns we wanted to display.
- Next Riley got to work. He is an experienced digital artist and noticed that the designs resembled a Voronoi diagram. A Voronoi diagram is a mathematical construct for clustering data. Points close together are clustered into one shape, and the entire set of points could be divided into different segments in a diagram.
- Next we needed to create some space between the points. Riley implemented a random walk algorithm, and then removed shapes centered around the mean. This had the effect of opening up the space between shapes to make the image appear more organic.
- Here is the first digital implementation in Processing.
- Next we added elements to tie in the analytics. The image was enhanced by more transparency in the background, and we added an orb to show time and temperature changes from the forecast data.
- We added a legend to make it easier for people to understand and relate to the piece.
- Susan came up with an interesting color scheme to add interest and relatability to the picture.
- Here is a snapshot of the piece presented on the screen.
- This short video shows some of the design detail.
- We wanted to add a bit more interactivity to the piece to help people better relate to what they are seeing. So we added a chatbot.
- You can ask questions of the bot and it will tell you what the image is showing you. It will also tell you about the sheep. The sheep eat the grass around the array to keep it down so that the grass and weeds don’t block the sun. They are efficient little lawn mowers.
- Here is the final architecture showing the analytics that I did, and the input to the art piece. I decided to create a 12 hour forecast using a Recurrent Neural Network with an LSTM hidden layer, which gets fairly accurate results for solar array forecasting. I used our SAS Cloud Analytic Server to create the Forecast, and saved the results to a file. We then used the data from that file to project on the display. The piece represents a 12 hour forecast of a cloudy day in March from the output of a deep learning RNN network.
- Here is the final architecture of the bot. This is using SAS NLP technology to create a natural language response to questions. You can ask the bot questions about specific time periods, about the solar array output and about the sheep!
- The demonstration is in a separate video file available on my linked in page. You will want to play it on your computer so that you can hear the pretty music that I set it to. I want to acknowledge and thank https://www.bensound.com for the give of music that accompanies the piece.
- What did we learn from this project? It takes a team. Each of us brought different skills to this project, and we had a lot of fun putting it together. Don’t let the art get too abstract. Stick to representing the data. Engage more than just visually. It makes the art more compelling (and approachable) This idea resonates with people. I often go over to our building where this is displayed and watch people as they walk by the piece and stop to view it. It engages all sorts of people in the experience. Finally, visualizations like this help make complex analytical algorithms understandable and approachable for ordinary people. It demystifies the analytical findings in a way that people can relate to. It is our sincere hope that this has inspired you to go out and create your own beautiful visualizations based on data. Help us spread the message of using Art to bring Analytics to life!
- You can find me on LinkedIn as Nancy Rausch and on Twitter. Jessica Peter is also on Twitter and has many more of her beautiful visualizations shown there.