There’s no doubt about it: trying to apply responsive design to large-scale existing desktop-centric sites is really, really hard. The message I keep repeating in my workshops is that you can’t expect to just sprinkle on some magic media-query fairydust—it just doesn’t work that way. Instead, you’ve got to figure out a way to reframe all your challenges into a mobile-first way of thinking.
Instead of asking “How can I make these patterns (mega-menus, lightboxes, complex data tables) work when the screen size shrinks?”, you need to ask “What’s the problem they’re supposed to be solving, and how would I design a solution for the small screen to start with?” Once you’ve done that, then it becomes a matter of scaling up to the large screen …which is actually a much simpler problem space.
Chrys Wu does the journalism world a great service (as is her wont) by aggregating all the NICAR14 materials on her blog. Excellent resources abound, and it has been a blast “attending” from afar.
A little #NICAR14 goodness from me to you — I sat in this session and did as complete a writeup as I could. This is an important issue; as data journalism becomes a bigger thing, how do we edit it? This was a FAAAABULOUS session.
Over 2000 D3.js Examples and Demos
YES PLZ THX
As one of the creators put it, easy tools for creating data visualizations (Excel, Tableau) aren’t always very expressive. Tools like D3 are very expressive — but you have to write lots and lots of code. It’s hard.
Enter Lyra. Lyra puts a GUI on top of D3, and when you’re done, generates the code. It also puts out a flat JSON file in a format known as Vega. The cool thing about that? Vega is highly reusable. You can reuse a visualization simply by feeding it a different dataset. Cool.
One of the most frustrating things about this great job (so it’s not mildly frustrating as other things in life) is bad data:
I was faced last week with a dataset that we have and that needed to be parsed to be any useful. The difficulty is that it’s quasi-regular text, the sort where it’s…
Points for Futurama reference. Major points.
Nice visualisation of TV show ratings with trend lines. via Phil Gyford.
1. Would be nice if the vertical axis always covered the full 0-10 domain (This, along with the tooltip styling, is a give away to me that Highcharts was used — confirmed with a quick view source).
2. The consensus seems to be that Buffy S-6 isn’t much worse than all the others — it is.
Nice use of color.
Art Historical Dataviz - Lauren Munk’s art historical raod maps, data charts, diagrams, and flowcharts prompts Robin Cembalest to track down the other art-datviz projects, from Ward Shelley’s sci-fi timelines to George Maciunas’ 1933 diagram of the historical development of Fluxus. ( I once did a huge one for graduate school on a ream of computer paper, must find).
What in the hell? No. Yes.
British Library opens exhibit about the history of science visuals
Check out some of these historical big data artifacts on display in the British Library’s Beautiful Science exhibit. Included below is a sample image from 1854 plotting cholera deaths.
William Farr, Report on the Mortality of Cholera in England 1848-49, 1852
1. In the comments of your program, write down what you want each part of the program to do.
2. After each of those comments, type out the program the way you want it to work.
3. Edit what you’ve written to bring it in line with how the language you’re using actually works.
If you do not know…
—This post is a tribute to James Iry’s fantastic One Div Zero blog.
Did you say big fonts? Because. Yanno.
sstitches asked: Hi, I recently got accepted to Northeastern but want to find out more about the school before I make a decision. Not unlike you I'm also interested in pursuing Journalism & Computer Science, and just want to know what your thoughts are on your experience so far? The co-op program sounds so intriguing, have you had an opportunity to get involved yet and with what? And if this isn't too heavy... Why did you pick Northeastern? Thank you so much!
I loved Computer Science and I love Journalism so far! The classes in both disciplines are a lot smaller than you’d see in business or psychology, as CCIS and CAMD (the colleges holding both majors) are among the smaller colleges on campus. CS classes start a little bigger and narrow down as people choose their focuses (or for some, leave the major) but the professors really go out of their way to get to know you.
Some professors I’d suggest if you do choose to do CS/Journalism at Northeastern:
- For Fundies 1 (Fundamentals of Computer Science 1), Olin Shivers. Best professor I’ve had thus far.
- For Interpreting the Day’s News (intro Journalism course), Dan Kennedy. He’s a sweetheart and really tries to excite students about journalism.
- For Journalism 1, Carlene Hempel. People are wary of her cause she’s a tough grader, but she really strives to get to know her students and help them out with getting to their specific fields.
- For Discrete Structures, Ravi Sundaram. He also is very big on getting to know his students, which I find to be an essential part to succeeding in such a stressful major.
I have not gone on co-op yet, but the friends I have on co-op are doing everything from database at a bank (CS co-op) to working at NBC News in NYC (Journalism co-op).
I chose Northeastern for a lot of reasons. First and foremost, the campus feel in an urban setting really helped to make Northeastern feel like home to me. I also really wanted to go somewhere new, which is why I went from my home in LA to Boston. Lastly, the school’s experiential learning requirement really settled it for me, because I’m just a little bit Type A and stress about my future constantly, so having work experience while in school was really important to me.
If you have any other questions, feel free to ask!
In which Dan Kennedy gets a well-deserved shoutout.
That girls are bad at STEM (science, technology, math and engineering) subjects is a pervasive and harmful stereotype that remains far too common today. But in an introductory computer science class at UC Berkeley last spring women outranked men in enrollment — there were 106 women and 104 men — for the first time.
Yes, the numbers are subtle, but they indicate a growing trend of women and girls asserting themselves in a field largely dominated by men. The percentage of female computer science majors at Berkeley nearly doubled from 2009 to 2013, to 21%. Stanford has seen female computer science enrollment grow markedly, from 12.5% in 2008 to 21% in 2013.
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