Data Curious (2019.08.05): Designing better dashboards and interfaces
data / curious
2019.08.05
I'm popping in early this week. Trying to get on a Monday schedule.
Last week I stumbled upon some really thought-provoking pieces on how to create better, more helpful visual interfaces for analyzing data. From over-designed health apps to cluttered public health dashboards, each field can suffer from a lack of direction when it comes to building data visualization platforms.
This edition of Data Curious includes a few anecdotes to counter this issue. So much of data visualization happens before the "visualization" part. In fact, understanding what people need from the data is often the biggest hill to climb.
It's not about the data; it's about the people using the data.
Hope the links are useful to you. Have a great week!
Read_
Why are visualizations in most health apps so ineffective?
Health apps should answer a fundamental question: is my health getting better or worse? But sadly, most focus too much on sleek / trendy UI elements and not enough on the UX of data discovery. Lena Dorogenskaya offers a beautifully thoughtful redesign of a more helpful health app.
How can we design better dashboards for public health data tracking?
The public health field is suffering from an epidemic of its own: dashboard fatigue. Drowning in data, nearly every major organization has created their own dashboard. But as Tricia Aung writes in this very insightful blog, "dashboards should not be considered default magical solutions for visualizing global health data". Let's do better. Consider the user, the creative process, the most appropriate indicators and how to make your design accessible.
Which Javascript library should I use for adding data visualization to my website?
Start with browsing this list of six JS data viz libraries to help you decide. If you're looking for my two cents, I'm partial to Chart.js. It's easy to get into the docs, responsive by default and looks great with a little code-tweaking.
Explore_
How can I create a visual summary of text data?
Words are data too. This piece from Bloomberg illustrates a great way of placing quotes in their given context through the speech annotator widget on the right-hand side.
How can we think beyond the "normal" chart type?
Stare into the wonder that is this rotating, spinning globe with real satellite paths to witness some truly "out-of-the-box" design thinking in data visualization (credit: Nadieh Bremer).
When did the phrase "mass shooting" become part of public discourse?
Mose definitely, the 21st century. The phrase is a modern phenomenon. FiveThirtyEight dives into the recent rise in its frequency in this visual analysis.
Analyse_
Who has won the Man Booker Prize?
Ok, not a dataset in itself. But after stumbling upon this article on every Man Booker prize winner I had an interesting idea: what can we learn from this list of authors, if anything? I'd be inclined to scrape the list and then cross-reference it with open Wikipedia data. Any other ideas?
Learn_
How can we use machine learning and data viz to make music scores more accessible and inclusive to all?
Read through this amazing walkthrough on how to turn music scores into cluster visualizations through machine learning (you'll also need a tad bit of knowledge in Adobe Illustrator and/or your preferred image editing software...but it's very approachable, so don't be shy!).
How can I update charts in D3 using the update pattern? How does it work?
D3 is great at adding reactive interactivity to charts. But understanding how the general update pattern works can be a bit of a headache. Try out this explainer article with code samples.
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