ShiftHappens; Weatherline [Data]Wrapped; QuickHit: APC

We decided to stay an extra day in Boothbay Harbor since the forecast was literally for the perfect Maine coast summer day, so no extended Mavo example, but the Drops must go on. We’ll try to keep this one light.

Likely no Drop on Monday due to the extended personal holiday.

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ShiftHappens

This typewritere simulator was created by Marcin Wichary as part of his larger project, Shift Happens, a comprehensive history of keyboards and typing technology. The simulator is designed to authentically replicate the soothingly tactile and auditory experience of using a traditional typewriter, offering users a glimpse into what writing was like before the advent of modern computers and word processors.

When you visit the simulator, you can type as if you were on a real typewriter, complete with realistic mechanical sounds, the ability to use correction tools like Wite-Out, and even the option to change the ink ribbon. The simulator intentionally mimics the quirks and limitations of actual typewriters: for example, you cannot simply erase text as you would on a computer; instead, you must use simulated correction paper or Wite-Out, and the keys produce the characteristic unevenness and “wobble” of typewritten letters.

This digital recreation is both novelty and an educational tool, helping folks understand the physicality and constraints of historical writing technology. AS someone who learned how to type (fast) on a non-electronic typewriter, I can attest to how well this simulation works.

It is also a companion to Wichary’s book, which explores 150 years of keyboard history, from the earliest typewriters to the modern devices we use today. The simulator and the book both emphasize the human stories and cultural impact behind the evolution of typing, rather than focusing solely on technical details.

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Weatherline [Data]Wrapped

Sometimes the most profound lessons in design come from what we’ve lost. Jonathan from Datawrapper recently attempted to recreate the visualization style of Weatherline, a beloved weather app that vanished after acquisition in 2021. The exercise reveals as much about thoughtful design as it does about the tools we use to rebuild it.

This app wasn’t revolutionary because of its data. It used the same forecasts as everyone else. The magic was in its restraint. While competitors cluttered interfaces with radar maps and hourly breakdowns, Weatherline distilled weather into elegant trend lines showing daily highs and lows, simple color coding for precipitation, and just enough iconography to make forecasts instantly glanceable.

Their tagline captured it perfectly: “Your weather forecast in a simple infographic.”

Jonathan’s attempt to rebuild this visualization style using Datawrapper reveals the sophisticated thinking hidden beneath apparent simplicity. Here’s what worked easily and what required creative problem-solving:

Straightforward Elements:

• Daily temperature trend lines connected smoothly using Datawrapper’s “Connect all points” feature
• Area fills effectively showed temperature ranges and precipitation changes over time
• Emoji text annotations provided clean weather iconography

The Technical Challenges:

The real ingenuity emerged in handling mixed data types. Precipitation forecasts (0-100% chance of rain) needed integration with temperature data measured in degrees. Jonathan’s solution? Rescale precipitation percentages as if they were temperature values, then disable tooltips to hide the meaningless rescaled numbers.

Time spans presented another puzzle. The chart ran noon-to-noon, but low temperature data didn’t span the full timeframe. Solution: auxiliary lines with disabled symbols to maintain visual continuity across the entire chart width.

What Jonathan discovered through this recreation exercise illuminates a fundamental truth about effective data visualization: the most powerful charts aren’t about showing everything—they’re about showing just enough.

Weatherline succeeded because it prioritized human decision-making over data completeness. Users didn’t need meteorological precision; they needed pattern recognition to answer simple questions: What should I wear? Do I need an umbrella?

This constraint-as-feature approach represents sophisticated information architecture. Every element earned its place. Every interaction required justification. The result felt effortless because enormous effort went into making it appear effortless.

The Weatherline story—and Jonathan’s reconstruction of it—demonstrates something crucial about the relationship between tools and craft. Modern visualization platforms like Datawrapper provide the technical foundation, but recreating truly elegant design requires understanding the underlying principles that made the original work.

It’s not about pixel-perfect reproduction. It’s about capturing the spirit of thoughtful information design and adapting it to available tools. Sometimes the constraints of your platform (like Datawrapper’s mixed data handling) force creative solutions that might actually improve on the original concept.

I’m a huge fan of Datawrapper as they are doing amazing work democratizing the creation and publishing of data visualizations (not everyone can craft a 200-line ggplot2 chart or build up a D3 datavis). This was a wonderful showcase of how to work with this platform and plan out a datavis strategy.

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QuickHit: APC

Literally just three (short) main paragraphs on this page with two appropro modern neologisms.

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FIN

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