If you have a few minutes to spare (or need some cheering up after one of your papers has been rejected), here’s a nice read:
Guillaume Cabanac (2015) Unconventional academic writing.
Cabanac wrote this as an addendum to Hartley’s Academic writing and publishing: A practical handbook (2008), and as a present for Hartley’s 75th birthday. It contains lots of unusual – and very funny – titles, papers, and figures, all of which have been published in academic journals. My favorite may be this one-page paper on writer’s block:
Hat tip to Viola Voß for the pointer.
In this great article, Lisa Charlotte Rost gives you a crash course to the use of color in data visualisation (and mapping, for that matter). It covers some theory, lots of useful links to classics such as ColorBrewer and less-known tools such as this awesome R library that provides color schemes based on Wes Anderson movies (yes, seriously).
This slide deck from FOSS4G 2016 originally only got my attention because of the truly awesome title, but it turns out Erik Escoffier has some tricks up his sleeve that I didn’t know. Worth a look if you’re frequently writing code that does geo stuff.
I just learned about Open Reblock from my students. Very cool project:
Reblocking is the process of physically transforming an informal settlement to provide an access path to all its structures. This project analyzes the spatial structure of informal city blocks, and uses an algorithm to suggest reblocking solutions that provide access to all structures within the block in a minimally disruptive way.
Interesting read about what can happen if you use a technology – IP addresses in this case – for something completely different than it was meant to:
For the last decade, Taylor and her renters have been visited by all kinds of mysterious trouble. They’ve been accused of being identity thieves, spammers, scammers and fraudsters. They’ve gotten visited by FBI agents, federal marshals, IRS collectors, ambulances searching for suicidal veterans, and police officers searching for runaway children. They’ve found people scrounging around in their barn. The renters have been doxxed, their names and addresses posted on the internet by vigilantes. Once, someone left a broken toilet in the driveway as a strange, indefinite threat.
The title is a little bit misleading – it’s not really a mapping glitch, but I can see how using IP-based geocoding in the title would turn most readers away without even reading the first sentence of the article.
Andrej Verity tells the story of the Humanitarian eXchange Language. Even though it turned out very different from our initial prototype, I’m glad it is still going strong. I learned a lot working on the HXL prototype and had a great time with the guys at UN OCHA.
I wrote a little wrap-up of this year’s Google Summer of Code Mentor Summit over on the 52° North Blog.
This is the most funny thing you will read this weekend:
The plan: get a robot arm, have it pour cereal and milk into a bowl and feed it to me with a spoon. The only catch was that I had to learn how to program a robot arm and code a pretty complicated sequence to have it serve me breakfast. But I was up for the challenge, because the best way to avoid real problems is to deal with fake ones.
The US Census provides an incredible wealth of data but it’s not always easy to work with it. In the past, working with the tabular and spatial census data generally meant downloading a table from FactFinder and a shapefile from the boundary files site and joining the two, perhaps in a GIS system. These files could also be handled in R but getting the data, reading it into R and, in particular, merging tabular and spatial data can be a chore. Working with slots and all the different classes of data and functions can be challenging.
A recent interesting post on stackoverflow by Claire Salloum prompted me to revisit this issue in R and I’ve definitely found some valuable new packages for capturing and manipulating Census data in R.
Great post explaining how to wrangle and map census data in R.