How to explain research findings in 2019
data / curious
2019.11.11
Greetings web friends,
Confession: I missed last week's Data Curious.
Reason: life gets crazy (also, I'm doing #codevember this year which is a huge time-suck).
Pledge: I'm still here and will write this newsletter (most weeks).
Addendum: I will most definitely miss a week again!
Now that we're all square, here are some cool links for the week. I highly recommend the UMAP one!
See ya next week,
Ben
Read_
What is the Mercator map projection good for?
Most of the time, not much. The Mercator projection is notorious for distorting the sizes of countries on a map. But web cartographer Kenneth Field explains a few examples of when this projection might be the right choice. Use with care.
What is UMAP?
If you've heard of or used t-SNE for dimensionality reduction in machine learning before, you should give this a read. If you haven't, you should still check it out because it's wicked cool!
UMAP is a clustering algorithm similar to t-SNE, but compared to t-SNE it has increased speed and better preservation of the data's global structure. The author's method of explaining this algorithm is what really shines here though: instead of a stodgy, boring research paper, they have chosen to publish their results online with interactive visualizations that explain how the parameters affect the UMAP output. This is how research should be explained in 2019.
Explore_
What should I bring to Thanksgiving dinner this year?
I love cooking. I also love data viz. This is the tool I've been hoping for to satisfy both. Select an ingredient, and a network graph appears linking it to the other ingredients that pair well with it for a certain dish. GAME CHANGER.
How can geography stack the deck for (or against) a person?
Woosh, look at those map transitions. A very tasteful report on the state of economic inequality around the globe using photography, charts and illustrations.
Analyze_
Where can I find open data on climate and weather research?
Did you know that Google Cloud has a host of open datasets ready to view/download/analyze in the cloud? They just released a new landing page specifically dedicated to open datasets in weather and climate change. You can find the rest of their open datasets here.
Learn_
How can I create scrollytelling maps?
I have written a lot about Mapbox in this newsletter, but I think rightfully so. They have published so many resources that makes mapping on the web easier than it has been before. This blog post explains how to create location-based stories with very little code, so you can get up and running with a fancy scroll-through story based on lat/long points.
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