Open Call - The Jewelry Code: Data as Wearable Art

Syldyr project invites you to create a wearable object – a piece of jewellery – that merges data and art. Let your piece tell a story through material, structure, form, size, geometry, texture, or color that push the boundaries of traditional jewellery design.

In anticipation of the upcoming exhibition at The National Museum of Kazakhstan (which is still open for submissions—see the Syldyr project page for open call details), the Syldyr team is launching a collaborative challenge. The goal is to create jewelry, share research and creative processes, support one another, and ultimately submit the resulting piece to the open call.

Participants are encouraged to decide how to visualize data on their wearable pieces. Will they use color (e.g., blue stones to represent days without coffee, red stones for days with double espresso), size (e.g., varying pendant sizes to reflect the gender pay gap across countries), references to graphs or charts (e.g., a bracelet shaped like a graph showing ocean pollution trends), or something entirely original? Creativity is highly encouraged.

They should document and share each step of the journey on social media, tagging @syldyr_project and using the hashtag #DataArtChallengeSyldyr. Whether in stories or posts, visibility is key—so profiles must be public in order for the Syldyr team to view the shared content. The team is eager to see everything: data selection or collection, material choices, and the assembly process.

Those who wish to join the Challenge’s WhatsApp group can send the Syldyr project a direct message to be added. Any questions can also be directed via DM.

This is a call to create Data Art jewelry. In today’s Post Truth era, reliable statistical data remains one of the last bastions of shared understanding. By turning data into wearable art, participants can help spread awareness through a beloved medium.

Participants should first decide what kind of data to use in their pieces. Will it be personal data, such as coffee consumption over the past year? Or will it draw from reliable statistical sources on global issues like climate change or gender inequality? All data types are welcome.