Press Release

What is the overarching concept or idea behind this exhibit?

In this exhibition, we invited submissions from artists (professional or amateurs) and scientists alike that focused on the perception of data from an artistic lens. Both data scientists and artists have to attend to detail while being sensitive to the whole, and both have to navigate complexity and discover messages worth sharing. Considering these connections, it seemed natural to put data science and art into dialog.

What do you want the art to communicate through their artwork?

We wanted to emphasize artwork that elicit aesthetic or emotional responses through beautiful representations of data, or encourage reflection on the role of data in science, society and our daily lives. We also wanted to question some myths about data science and art. Data scientists are often portrayed as purely rational, only interested in things that can be quantified. But the reality is that data scientists are often most interested in ambiguity and uncertainty. Similarly, artists are sometimes dismissed as living “in their own world” when they have the sharpest eyes for patterns (social and natural) that many of us can vaguely sense but not precisely articulate.

In the submissions that you have, what artistic techniques or visual elements are used to convey data?

The artwork is quite varied: 3D representations of scatterplots, color grids of heatmaps of experimental data, weaving of DNA structures, pictures of google searches, 3D-printed tiles representing eigenfaces, and images projected on wall.

How did that artwork or idea make you feel?

We felt grateful to be a part of such a creative community that doesn’t draw artificial boundaries around itself.

How does a Data art exhibit challenge or change perspectives on the subject matter?

We hope that the exhibition will show that data can be artistically beautiful. We loved the sense of defamiliarization. So much of our lives have been spent deciphering scatterplots, eigenvectors, and sequence data on computer screens. But seeing a scatterplot in physical space (Bella Wu and Claudia Solis-Lemus), an eigenvector of a face (Ben Kizaric), or a DNA sequence woven from linen (Danielle Burke) — these were completely new experiences! On a related note, it made us realize how much data science practice is wrapped up in convention. It’s so easy to use software defaults that it’s hard to recognize all the choices that we could make if we dove a little deeper. We especially felt this idea seeing experimental colormaps on community-contributed data (Clementine Zimnicki), and more broadly, we are so used to data science being communicated through computer screens, but this is only one of many possible mediums. We appreciated that the exhibition became a way for the artists to question data science conventions.

How does the artwork involve the viewer in exploration of data?

Different artwork will show different facets of data.

Does the artwork raise any questions or concerns about data privacy, survelliance, or ethical implications?

All data has been anonymized, so there are no privacy concerns related to the artwork. After seeing the submissions, we did have the (somewhat disorienting) thought that almost anything could become data. Someone only has to care enough to represent it in a way that lasts longer than the initial impression.

How does this artwork contribute to the broader field of data art or the intersection of art and science?

Art is meant to inspire audience to view data in a different lens, and ideally, by showing the “beautiful” side of data, younger generations can be inspired to pursue a career in Data Science.