I am not terribly familiar with local politics outside of my local areas. So the background and details of this piece escape me. However, this interactive graphic and story from the Los Angeles Times does a really great job of leading the reader through the story.
First, the piece starts with a general overview or flowchart of the network of connections. Mouseovers do a fine job of highlighting and filtering for the appropriate piece. For example, a person shows the entities to which he is connected whereas the entities show the people to which it is connected.
Secondly, the piece then goes in detail about the different connections. The example screenshot below shows how each story is highlighted by a red dot as the user scrolls down the page. When that story is highlighted, the network diagram to the left changes, either replacing the contacts or highlighting the contacts specifically noted in the story.
As I said at the outset, this is a very nice piece that step-by-step shows and explains how all the connections work while filtering out the momentarily irrelevant data. Very well done.
I’m not a coffee guy. I drink tea. At most I have one or two espresso drinks per year. But up in Boston, they have been looking this week at coffee preferences. The question is which is your coffee spot? Dunkin Donuts (from Massachusetts) or Starbucks (from Washington)? Northeast or Pacific Northwest? In a piece that reminds me of the New York Times’ Wawa vs. Sheetz graphic, the Boston Globe plotted the locations of the two national coffee chains. This interactive piece allows you to toggle between dots for Dunkin Donuts (orange, naturally) and Starbucks (green, of course).
They complemented the Massachusetts-focused piece with a longer article that looked at the national distribution.
Credit for the piece goes to Alvin Chang and Matt Carroll.
Well maybe not so much the space. Anyway, Nicolas Rapp, who does a lot of work for Fortune Magazine and previously the AP, created his first connected scatter plot. I have been a fan of them for quite some time and have been able to use them fromtimetotime. Rapp’s scatter plot looks at the profits and revenues of the Fortune 500 in the last 20 years. But what I think makes his piece particularly strong are the two annotations he provides to explain the “loops” in the data: the two big recessions.
Once when I worked at the Jersey shore as a kid a woman purchased her books and then asked me the location of the nearest ATM. I replied “Wawa”. She looked at me as if what I said was gobbledy-gook. She asked again. I replied “Wawa” again but with probably a look of confusion upon my face. It turned out she was from California and she thought I was mentally ill. I did not understand how anyone did not or could not know about the awesomeness of Wawa.
But for all of my upbringing in the Philadelphia suburbs/South Jersey loyalty to Wawa, I must confess to an unfortunate divide in Pennsylvania between we civilised folks near Philly and, well, the rest of the state. We in the Philadelphia metropolitan area are loyal to Wawa. The rest of the state swears allegiance to Sheetz. But how stark is this geographic loyalty? The New York Times mapped store locations with Wawa in blue and Sheetz in red to accompany an article about the “tribal loyalties” to the two chains.
For those more curious about this author’s loyalties, the author of the article, Trip Gabriel, included photos by Mark Makela of one of my local Wawas (the one near Malvern at 202 and 29 for my hometown readers) as the main image for the article along with photos of interiors in West Chester. And of course the Wawas where I grew up:
Google is a big company. What do big companies do from time to time? Market themselves. And so this is a screenshot from a fun interactive infographic piece that has supplementals from text to photos to videos as Google explains how an e-mail is sent. All the while Google touts its green energy initiatives and energy efficiencies. It’s a game changing win-win paradigm-shifting grand slam of a piece. (Sorry, that just felt like an appropriate place to use CorporateSpeak.)
Kickstarter has been around for a little while now, financing some interesting projects. The New York Times has an infographic about how much each project earned. And while there is nothing particularly fancy about each, they are all scatter plots, the quirk is that the time and value axes have been reversed from their customary positions. While unusual, it supports the longer range for the monetary figures and the short range for the three years of Kickstarter history.
Furthermore, the data is broken out into different industries, e.g. design, food, and dance, that have adjusted value scales to make intra-industry comparisons easier. Nothing fancy, but an attentive care to the detail of the data.
Everybody knows that executives make a lot of money. But not all of it comes from just salary, some comes from bonuses, stocks, options, and other perks. So who makes the most?
The New York Times put together an interactive piece with data from Equilar about the 50 most-highly paid chief executives from companies over $5 billion in size. The data is arranged as stacked bars, with—when available—2010 data to compare to 2011. The order can be sorted a number of different ways and the executives on display can be filtered by what industry his or her—granted only 3/50 are women—company works in.
Credit for the piece goes to Lisa Waananen, Seth Feaster, and Alan McLean.