This is not necessarily the sector you think of first when you talk about data, but it is one of the sectors where data is gaining more and more ground. 

Art in the data

Let's start with the importance of art in data. We are thinking here of data-visualization: how to represent data in the right way. Indeed, to make data accessible to the largest number of people, adding a part of art will make visualization more pleasant and not remain a discipline of insiders. 

Data visualization is a way to turn complex data into simple ideas. Data Art is the practice of using data to convey emotions to the public. We will therefore cross the artist's imagination and the objective truth brought by the data. In companies, data art allows to bring storytelling to data visualization by adding an aesthetic dimension. 

A good Data Analyst or Data Scientist doing visualization should have a basic artistic background: choice of appropriate colors, layout and data filtering. We also think of all the network representations that have an infinite number of ways to be represented but very few of which are easily understood. 

Data in art

The place of art in the data is more and more important in all categories of arts: Music, Drawing, Video, ... 

Image generation

Dall-E 2 released in the first half of 2022 allows to generate an image from a description and democratizes this method. Competitors such as Midjourney or Stable Diffusion have emerged very quickly. These artificial intelligences are so powerful that an American artist won a contest thanks to Midjourney. 

The question that we can ask ourselves when we see this one is a philosophical one: is the creator of such a work the man or the machine? Indeed, it is indeed the man who gives the right instructions which allowed this creation but it is the machine which creates this work thanks to all the knowledge which it accumulated by crossing tons of data during its training. 

In the 7th art

We presented it in a previous article, Netflix uses data to guide its creations and understand the appetites of its users. Finding and understanding what the public will like visually is one of the jobs of Netflix, which it masters to perfection. Netflix uses data to make series that appeal and this allows it to have many more series that do not stop: 80% of series have a second season where in the United States the average is 25%. 

‍

In the music 

Some contents can now be totally created by artificial intelligence as we presented in this article on data and music. The data allows to create assistants to the creation of music, by creating for example the continuation of a chord which will be musically coherent. 

Another example is the Data Driven DJ. This DJ creates music tracks from various data sources. For example, the position of the stars, the air pollution in China or the income inequality between subway passengers in New York are data sources he has used in the past. In the link earlier in this paragraph, he used the migration flows of refugees around the world as a data source. 

In the comic strip

The Datacomics.net site presents comics using data as the basis of their narratives. This site was created from the union of several researchers. And what they are trying to do is Data Storytelling: using data to tell a coherent story, in a comic book format. 

Conclusion 

Data and art are more closely intertwined than we think. Art adds an aesthetic dimension to data, while data adds an objective and factual dimension to art. 

‍