Data visualization with textiles as laid out in this handbook comes out of the interdisciplinary academic field of digital humanities. Digital humanities looks like a lot of things, but one area involves taking a critical look at ideas of “data” that we often take for granted.
Johanna Drucker’s 2011 article Humanities Approaches to Graphical Display takes common “simple” examples of data and data visualization asks questions about the data that went into those visualizations, offering possible models for what an alternate visualization might look like that is more thoughtful about the nuances behind the data.
Drucker argues that even subconsciously, we treat “data” (etymologically “a fact given or granted,” classical plural of datum, from Latin datum “(thing) given”) as something that can be objectively observed, that it’s something given that exists on its own. In reality, the “data” we interact with is more honestly “capta” (something taken, rather than given, also reflective of the subjectivity of the person doing the recording, or making choices for the system doing the recording). If we acknowledge that we’re actually working with capta rather than data, then we can look at “data visualization” not as a neutral, factual representation of information, but as a way to create a visual representation of an interpretation.
“Capta” never caught on more broadly, so using it instead of “data” would be confusing. But the approach to data visualization with textiles in this handbook takes seriously the idea of data fundamentally being “capta”, that it exists in a relationship with its recorder — as well as its visualizer.
Not every textile data visualization project has to spiral off into the thousand possible directions you could go in, depending on what kinds of nuances you want to represent. But it’s worth keeping this aspect of “data” in mind when you’re trying to map your data to textiles. Your textile project can be more capacious and flexible than your standard software data visualization tools support; outliers or pieces of data that “don’t feel right” being represented in a standardized way can be the most interesting parts of your textile.
Next steps with data
Do you have data you want to work with already? If not, explore different options for Acquired Data and Created Data.
Once you have your data, you can start thinking about what part(s) of the data you want the textile to capture, and then how to map that onto different textile properties.
Readings
- Data Feminism by Catherine D’Ignazio and Lauren F. Klein.
- “Humanities Approaches to Graphical Display” by Johanna Drucker, DH Quarterly 5.1, 2011.