When we think about data viz and textiles, the Tempestry Project—“personal and collaborative fiber art, environmental education, and climate activism through data representation”—often comes to mind. Representing climate data in an ancient textile medium reflects its gravity; the deliberate work of knitting or crocheting data mirrors how deliberate we must be in grasping this global problem and mitigating it. 

Just as textiles like a Tempestry are laborious to create, they are laborious to pick apart. Whether we are makers motivated by thrift and sustainability, crafters honing our technique, or artists driven by conceptual concerns, working with fibers often involves raveling finished cloth. A quilter salvages material from the clothing of someone who has passed for a memory quilt. A knitter ravels a sweater that no longer fits to reclaim the yarn. An artist unpicks her grandmother’s embroidered linens to ponder the baggage of inherited possessions. In ancient Greek myth, Penelope buys much-needed time as she weaves by day and unweaves by night. 

Other times, raveling is an intermediary step in creation. Some embroidery projects use waste canvas as a stitching guide, which must later be painstakingly removed. An especially precise way to cut a garment on grain is to select a single thread to unpick at the point you wish to cut. 

For this challenge, take time to ravel your data. Unpick a seam, fray a scrap of woven or knitted fabric, or remove stitches to illustrate data that is meaningful to you. You may wish to visualize data that points to absence or loss, for instance. Raveling can take time, so you may decide to focus on a single statistic or data point, rather than a dataset. Consider documenting the textile before and after your intervention. 

Practical tips

• Many professional seamstresses use razor blades in addition to seam rippers; they can be a speedy (but sharp) way to undo stitching. 
• Sewing pins are useful for selecting and unpicking a single thread. 
• Knitted textiles, like a sweater, will ravel much more easily than woven textiles, like a dress shirt. 
• There’s no need to buy fabric—reduce waste and reach first for scrap fabric or clothing beyond repair. 
• Need to count threads easily? Try an evenweave fabric such as Aida cloth or a scrap of coarsely-woven fabric like burlap. 
• Yard goods (like yarn and ribbon) are easily measured to a specific length; keep in mind that yarn can be separated into multiple plies. 
• Pick a spot with good window light for your project, or use a bright LED work lamp. Take breaks as needed—this work might strain eyes and hands. 

Need inspiration?

Here are some textile deconstruction projects that I find particularly interesting: 

• The WPA Milwaukee Handicraft Project unraveled military-surplus burlap bags to weave into textiles. 
• “Unraveling” (2015, by Sonya Clark) deconstructs the Confederate battle flag thread by thread. 
• “Unraveling” (2006-18, by Jean Shin) illustrates the network of relationships in the Asian American art community. 

Let’s see your raveled data! Send in one high-resolution image plus a 50-word description by AUGUST 4, 2023 (deadline extended!). 

The post Dear Nightingale: Raveling Data appeared first on Nightingale.

That day, I spent ten hours running a piece of cloth through my typewriter. I selected a few lines from the Book of Common Prayer to overtype 549 times, in all caps: “FROM PESTILENCE FAMINE BATTLE MURDER AND FROM SUDDEN DEATH GOOD LORD FROM LIGHTNING AND TEMPEST, FROM PLAGUE DELIVER US.” I’d recently learned that the Book of Common Prayer was compiled in the 16th century during the Black Death. That context may explain why the book’s many pleas for deliverance from plague still radiate urgency. 

Eventually, I began to document daily case counts in my region of Iowa on a larger textile. I recorded cases every day, each with a stamped prayer, “FROM PLAGUE DELIVER US.” Prayers tend to be said on behalf of those closest to us, and a county was the smallest geographic area for which case counts were available. Working with data from Johnson County, IA, I recorded just the new cases each day, excluding recovery data or deaths. My intention for the final product was to situate both the act of prayer and the practice of art making as nuanced methods for approaching uncertain situations. 

What happens when we can both see and touch data? I worked on DEMAND/PRAYER for about 20 hours a week over 18 weeks. I anticipated the project would be a sad one; I didn’t expect it to make me shake with anger while I sewed. It’s one thing to model cases digitally, and another to perform a small physical act of labor that acknowledges each person in a dataset. My anger was fueled by numbers from a relatively small area, compared to the pandemic’s global reach. I wondered if (and how) public policy outcomes might change if legislators, and the public, had a more embodied relationship to case data. As the writer Jenn Shapland claims, “I feel that there is a price we pay for disembodiment.” What might happen if those shaping public policy could touch and see the lives being impacted by this pandemic? 

There are important elements of the pandemic in Johnson County that this textile does not capture, such as which demographic groups bore disproportionately high caseloads. Additionally, the piece represents all new cases in the county over the course of a year with a reference to a Christian text, the Book of Common Prayer. But, perhaps only a third of Johnson County’s residents are religious, and the local religious groups include Jews, Muslims, Buddhists, Hindus, and Christians. Given these demographics, my work is an example of how data art differs from data visualization. As an artist, my work recycles canonical Christian texts to assert that mystical and spiritual experiences happen within, and sometimes despite, established social structures.

Cloth is a practical medium for my data physicalization projects: even durable paper can become worn out from repetitive stamping or typing. A second reason I use cloth is “computing’s historical dependency on textile design, its production methods, and its labor models.” Binary code was invented during the industrial revolution to automate weaving patterned cloth. Core memory, the first viable and widely adopted re-writable computer memory, was a conductive fabric which coded ones and zeros in magnetic beads as positive or negative charges. Core memory was woven by hand, and its fabrication resembled a combination of bead looming and pin loom weaving. A touchscreen technology often found in consumer electronics like tablets and smartphones relies on conductive grids that operate similarly to core memory planes. The anthropologist Stephen Monteiro draws parallels between needlework, touchscreen gaming, and image-based social media interfaces, arguing that “personal touchscreen device use resembles the actions, strategies, and conditions of craft production.”

Some data physicalizations are self-conscious of these connections, demonstrating integration between medium and message. Visualizing blockchain technology with yarn, knitting a blanket of sleep pattern data, and encoding the pace of global warming into winter wear—in these projects, yarn is a considered material choice. However, some textile data physicalizations leave me wondering why textiles were chosen as a medium for that data. To engage a certain demographic as makers or viewers of the data object? Because knitting, crochet, and embroidery are financially accessible techniques for making data physical? There’s nothing wrong with either motivation. However, many makers working at the intersection of textiles and data are still unaware of the degree to which information society depends on textile technology. When we choose textiles as a medium, we have an opportunity to highlight that connection.

Artistic data physicalizations are laborious, and they’re not immediate enough for many of the ways we use data. Still, I am drawn to the ways textiles can make associative leaps and humanize data: as if by giving data a body, we glimpse its soul. 

Learn more about gendered labor, textiles, and the 1969 moon landing:

1. Skilled seamstresses sewed Neil Armstrong’s space suit by hand, using techniques adapted from lingerie construction.
2. A workforce of unnamed women, some of whom were retired or laid-off textile workers, hand wove the space shuttle’s navigation program.
3. A workforce comprised mostly of Diné (Navajo) women fabricated the microchips for Apollo 11.

The post The Soul of Data: Data Physicalizations on Fabric appeared first on Nightingale.