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Chapter 3: Weaving Data — Making Data Visible and Tangible

YongHong Chen

3.1 Collecting and Preparing the Data for Weaving

Recording the Data

Start by preparing a spreadsheet to record the relationship between your daily mood levels and key lifestyle indicators such as sleep duration, time spent in sunlight, and exercise (see Figure 3.1 for example). This practice embraces the concept of embodied cognition data—a tactile, aesthetically engaging method of interpreting and experiencing data through the body (Gaviria, 2008).

Spend the next week (or longer) recording your chosen parameters. As shown in the file Sample data for demonstration.xlsx, each row records the date, a self-rated mood score (0–10), hours of sleep, sunlight exposure, and time spent exercising. The mood scores are self-assessed as follows:

  • 0–2.5: very poor mood
  • 2.5–5: low mood
  • 5–7.5: decent mood
  • 7.5–10: excellent mood

The data below represents a fictional week for demonstration purposes only:

Screenshot of spreadsheet used to record daily mood rating (scale 1-10), hours slept, hours spent in the sun, and hours spent exercising.
Figure 3.1: Sample data for demonstration.xlsx

You will also need the following materials:

  • A pair of scissors
  • The 3D-printed Knitting Needles and Weaving Comb
  • The Mini Weaving Tools
  • Four colours of yarn:
    • Red for mood score
    • Dark green for sleep duration
    • Yellow for sun exposure
    • Light green for exercise duration
Image of white 3D printed loom, pink 3D printed weaving comb and knitting needles, orang handled scissors, and 4 bundles of yarn in light green, dark green, red, and yellow.
Figure 3.2: Needed materials.

Translating the Data into Weaving

In this method, yarn is wrapped around the loom to physically represent the values from the data table.
Each full loop around the loom represents one unit (e.g. 1 point or 1 hour). A value of 0.5 is represented by half a loop.

For example, if the mood score on 1st March 2025 is 5, wrap the red yarn around the loom five full times.
If sleep duration is 6.5 hours, use dark green yarn to wrap six full loops and one half-loop.
Use yellow yarn to represent two full loops for 2 hours of sunlight, and light green yarn to show one loop for one hour of exercise.

Repeat this process for each day of recorded data, encoding the data visually and physically onto the weaving frame.

3.2 Weaving Data in Practice

The next portion of the project can be done by watching the video (linked below) and following the written instructions.

Video 3.2: Weaving with Data – A Step-by-Step Demonstration

Step 1

Using the 3D-printed Mini Weaving Tools, begin by wrapping any colour yarn (this base layer forms the structural grid and will not be visible later) diagonally across each peg.

Image of white plastic loom with about half of the pegs looped with green yarn to form the base structure.
Figure 3.2.1: Start of woven base structure.

Step 2

Thread the red yarn (which represents mood scores) through the knitting needle. Tie one end securely to the centre of the base yarn to fix it in place.

Image of white plastic loom, now fully looped with a green yarn base structure. A pink needle is being used to loop red yarn through the strands of the base structure.
Figure 3.2.2: Beginning of weaving red thread into base structure with needle.

Step 3

Weave the red yarn through the warp structure in alternating intervals. Follow the data table numbers and wrap the number of full loops that match the mood score. The diagram below can be referenced for looping the yarn in and out of the base structure.

Diagram of steps for weaving a pattern of coloured threads into the loom's base structure.
Figure 3.2.3: Weaving technique and pattern.
Image of a white plastic loom with a green woven base structure and several rows of red and dark green woven through.
Figure 3.2.4: Loom with a few rows now fully woven.
Image of white plastic loom being used with a pink needle to weave dark green thread through the base structure.
Figure 3.2.5: Dark green yarn being woven through base structure.

Step 4

To change yarn colours—for example, when switching from dark green (sleep) to yellow (sunlight)— simply tie the new yarn to the previous one at the point of transition.

Image of the white plastic loom with a woven green structure and several rows started. Yellow yarn is being tied to the dark green yarn.
Figure 3.2.6: Tie the yellow yarn into the previous dark green strand.
Image of white plastic loom with the beginning of a woven structure. A pink needle is being used to thread yellow thread through the base structure.
Figure 3.2.7: Yellow yarn being woven through the structure.

Step 5

Once a day’s data is fully woven, use the comb to gently press down and shape the pattern into a regular circular form.

Image of a white plastic loom with a woven base structure. A pink weaving comb is being used to push yarn towards center of the structure.
Figure 3.2.8: Weaving comb being used to push yarn towards the centre of the structure.
Image of a white plastic loom with a half-finished striped woven circle. Bundles of coloured yarn, scissors, and pink weaving accessories sit to the side.
Figure 3.2.9: Woven piece with several days woven in.

Step 6

As more rows are added, the woven pattern begins to emerge clearly, visualising the rhythms in your data.

Image of a white plastic loom with a half-finished striped woven circle. Bundles of coloured yarn and pink weaving accessories sit to the side.
Figure 3.2.10: Woven piece with several days woven in.
Close-up image of a white plastic loom with a nearly finished, colorful woven circle. A pink needle is being used to weave in another row.
Figure 3.2.11: Close-up of the nearly finished woven piece.

Step 7

After completing the weaving of the full dataset, flip the entire loom over. Use a pair of scissors to cut the threads on the back and tie the neighbouring ends together securely along the edges of the weaving.

Image of a white plastic loom with a woven structure. Scissors are being used to cut off the backside of the base structure.
Figure 3.2.12: Cutting off strings on the back of the base structure.
Image of the woven piece separated from the white loom, which can be seen in the background.
Figure 3.2.13: The woven piece, now separated from the loom, with all ends tied off.

The result is a circular woven pattern that represents your mood and lifestyle data you’ve recorded for at least a week. This method can be adapted to any dataset—simply assign colours and units accordingly. For example, dark green stands for sleep: one full loop equals one hour, while half a loop equals thirty minutes.

Image of a circular, patterned woven piece, alongside the tools used – including a 3D-printed white miniature loom.
Figure 3.2.13: Output of dataset woven into a pattern, alongside the tools used.

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Chapter 3: Weaving Data — Making Data Visible and Tangible Copyright © 2025 by YongHong Chen is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License, except where otherwise noted.

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