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The Top 5 Data Visualization Trends in 2024
Video Visualization
This study found that 67% of users preferred to learn about a new product or service through a video rather than pictures or text.
Data Democratization
With advanced no-code data analysis platforms that automatically process and unlock data.
Real-Time Visualization
For user feedback and retention, real-time visualization is incredibly effective.
Mobile and Social Data Visualization
Adapting data visualization to mobile users has grown significantly in recent years as people use their mobile devices more frequently.
Artificial Intelligence and Machine Learning Datavis
By using AI in data visualization the possibilities for analyzing vast amounts of data and being able to streamline the processing, patterns will be discovered more readily.
An Incredible TedTalk-
Stunning Data Visualization in the Allosphere
The AlloSphere, created by JoAnn Kuchera-Morin is an example of when data visualization is taken to the next level. Created by artists, scientists, and engineers, this physical space is used to push the limits of patterns in data and of how data can be experienced.
This ted talk takes you through five research projects they are working on "from biological macroscopic data all the way down to electron spin".
- the "allobrain" to quantify beauty and fly through the brain
- Bio-generative algorithms for self-generation and growth
- Atomic world and fly into a lattice of atoms with multi-center hydrogen bonds with emission spectrums so you hear them singing to you
- Explore one single hydrogen atom and the electron flow (hear and see the electron flow
- Explore one single electron spin and decoherence in the model (helps with quantum computers)
From walking through colleagues' brains to hearing the hum of an electron spin, innovations such as this one will continue to push the bounds of data visualization.
An Amazing AI Image Generator-
Limitless Possibilities for Data Representation
Example of Data Visualization Using an AI Image Generator
Everyone has preferences as to the type of art they like.
When we gather individual preferences together, we get a picture of what a group as a whole prefers.
That’s what we did with the ETEC 522 65A class to better understand their collective taste in art.
Our method was inspired by artists Vitaly Komar and Alex Melamid, (Figure 1) who worked with the research firm Martilla & Kiley to survey 1,001 Americans about what they liked in art.
They then made a painting that represented the most popular choices from the survey. (Figure 2)
Similarly, we reached out to members of the ETEC 522 65A community to poll them on their preferences in art. (Figure 3) The survey ran through 18 questions, such as “serious or festive?” and “outdoor scenes or indoor?” We felt that the variety of information was appropriate for our purposes.
Figure 1
Figure 2
Figure 3
The Google Form we used not only collected the responses but also turned them into pie charts, making it easier to see what the majority preferred. The results can be seen below. (Figure 4)
Figure 4
For the parts of the survey where there was a clear favourite, we used those choices to tell Stable Diffusion XL, an AI that generates images, what to create. Based on the data gathered, the following prompt was used:
There was some dilemma in deciding whether to create a pure landscape or a portrait. Although people in the class expressed a majority preference to see people in their paintings, that was for the question of preferred type of indoor scene. Most people decided that they liked outdoor scenes over indoor scenes, so that should have cancelled out the preference to see people in paintings. However, there were two other questions that asked individuals to state the preferences for the type of people they liked to see in a painting, single or group, and ordinary or famous.
We felt we should try to honour those preferences. Therefore, one prompt was used to create an image with a single ordinary person (Figure 5), while another one was used to create an image of a landscape (Figure 6). Below is the prompt used for the image without a person:
The images that were created reflect the aggregate preferences of the ETEC 522 65A class:
A pie chart and a painting are both visual representations of data. Each pie chart clearly shows one data point - a preferred painting characteristic of the group. It is very clear with the pie charts what each group preference is. The image generator takes those clearly defined preferences and blends them to create a singular artistic piece.
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