Upcoming: Data Collection & Visualization in the Park

The best dataset is the one you gather yourself.

Join tcplot for a morning that starts with coffee and ends with a chart. We'll meet at The Coffee Shop NE, walk over to Audubon Park to collect data by hand, then come back and turn what we gathered into a visualization.

Data collection is usually invisible — by the time most of us see a dataset, someone else has already decided what counts. This is a chance to make those decisions yourself: what to measure, how to tally it, and what gets left out. The constraints of a clipboard and forty minutes turn out to be the whole lesson.

How the morning will flow

• ▸ Coffee & plan. Meet at The Coffee Shop NE for quick intros and to decide what each of us will count.
• ▸ Collect. Walk to Audubon Park and spend about forty minutes gathering data — tallies, timings, sketches, observations.
• ▸ Visualize. Head back and turn your raw tallies into something readable — on paper, in code, or in beads and thread.
• ▸ Share. Compare what we made — and how differently we each saw the same park.

Things you could count

Pick one and go deep, or track a few at once. A handful of ideas:

• ▸ Lay a loop of string on the ground and survey everything inside the circle — bugs, plants, blades of grass, clover, whatever you find
• ▸ Birds, squirrels, and dogs — by count, by type, by minute
• ▸ How people pass through: walking, running, biking, rolling, with strollers
• ▸ Trees by species, or the colors of the leaves
• ▸ Dandelions in the grass — where they cluster and where they don't
• ▸ Sounds — and how often each one interrupts the quiet
• ▸ Benches: how long anyone stays, and what brings them there

What to bring

Something to record with — a notebook or your phone — and shoes for a short walk. A laptop is welcome for the visualizing part but not required; we'll have paper and making supplies on hand. Dress for the weather.

Rain plan: light rain, we'll go anyway. Heavy rain, we'll collect our data right from The Coffee Shop NE.

Who this is for

Anyone curious about where data comes from — practitioners and first-timers alike. No tools or experience required, just a willingness to notice things.

Hope to see you there!