Join Bill Shander for an in-depth discussion in this video Flow diagrams, part of Data Visualization: Storytelling.
- [Narrator] Flow diagrams have been used for a very long time to visualize things like org charts, database diagrams, and business processes, they're such mainstays in business communications that they've become the platform for an entire category of memes. Whether self-referential flow charts like this one, or flows that help with decision making. Some, like this one, are very dense and rich flows with a lot of information to digest.
You'll only read part of this story maybe, so you're choosing the story for yourself. Structurally, this is a flow diagram, but it reads in a much less linear way, right? So, I might start in the middle, So You Want To Watch Youtube, of course, and I might see the word musician and then read to the right wizard, rocker, or muggle, I might say oh, that's not really for me. Oh yeah, I'm more of a vlogger, right? A Video logger, and so I want to go up and start up there and start reading out that way, and you know the odds of my really following this flow to the end maybe are low, but I am deciding what flow to follow to tell the story that I want to tell, or that I want to learn.
Or, in this example of what is really not at all a traditional flow diagram, this is an interesting project, it's a recreation of a classic visual that appeared in a statistical atlas of the United States from 1890, so I'm actually gonna jump over and just show you that one. This is the original, so what we're looking at here is starting in 1790 on the right-hand side here, we see the top population centers in the United States, New York, Philadelphia, Boston, Charleston, and Baltimore, et cetera, and then all the way, if I go all the way to the left-hand side here I see the top metropolitan areas again, it's a much longer list, and I can see more examples, and if you follow the colors and the connecting lines through, and so for instance, New York is number one all the way in 1790, all the way through 1890, but some of these others, like if I go down here to Providence, which was number, you know whatever this is, seven or eight in 1790, and then it drops much further down the list by the time I get to 1890, or if I look at Marblehead, which essentially drops off the list, it's really hard to read in this original format, but this interactive version is a really interesting recreation of it, and essentially I can actually sort of roll over them and see, so for instance Charleston, which disappears of the list in the mid to late 1800's, or Newport, which drops of the list in the early 1800's.
You know, essentially it is a flow diagram, but not that traditional flow diagram. And again, there's the famous Charlesman art graphic telling the story of Napoleon's disastrous march on Moscow. This is a classic example of data storytelling using a flow diagram as its primary visual mechanism. Go search Napoleon infographic to get more information about this example if you're interested, but quickly I'll mention that when including the quantities of data in flow diagrams, the go-to method is to use techniques like this where the thickness of the line reflects the quantity.
In this case, the size of Napoleon's army. This is typical in the sankey diagrams you see in a lot of visualizations of data. There are a lot of software programs that make it easy to generate sankey diagrams, which is what this type of flow is called. So, you see a lot of these nowadays. This is a great example of a flow diagram that really is effectively telling this story of the flow of petroleum in our daily lives. The orientation of it is perfect, you start reading the upper left-hand corner, right? That's where the text is, you're gonna start there, it's left to right language society like English, and if you read down, you see the primary sources of energy, right? You can see renewable, nuclear, natural gas, coal, and then petroleum, then you see the US consumption of petroleum compared to the world consumption, right? Sort of broken out that way, and then as you start to flow to the right, which is where your eye is gonna be drawn, you start to see the breakdown of that US consumption number.
This sankey diagram is a linear flow, really a series of linear flows that lead your reader right through a story. The key to telling a story using a flow diagram, whatever kind it is, is sometimes to realize that you can convert a conversation from being about proportions and turn it into a flow. For instance, the temptation in telling this story about oil might be to create a bunch of pie charts, so for instance, you know we have the sources of energy on the left, and what percentage are renewables versus gas versus petroleum, 40% petroleum, that could've been one pie chart, right? And then we could've been oil consumption versus US consumption, that could've been one pie chart in two pieces, and then we could've had domestic production versus imports, right, another pie chart.
Instead of doing that, it's just a series of flows instead of pies, right? The sankey does a better job at this kind of a thing, especially in the case when you're showing proportions after proportion of a proportion, right? Succeeding proportionality let's call it. If your data describes a flow from one thing to the next, or some sort of hierarchy, or if you can use the metaphor of a flowing process, or if you are telling a story of proportionality, especially successive proportionality, using a flow diagram might be great way to tell your data story.
Join data visualization expert Bill Shander as he guides you through the process of turning "facts and figures" into "story" to engage and fulfill our human expectation for information. This course is intended for anyone who works with data and has to communicate it to others, whether a researcher, a data analyst, a consultant, a marketer, or a journalist. Bill shows you how to think about, and craft, stories from data by examining many compelling stories in detail.
- Creating a narrative structure for data
- Applying narrative to data
- Identifying what you want to say with the data
- Analyzing what your data is saying
- Determining what your audience needs to hear
- Leveraging tables, charts, and visuals
- Ensuring your narrative provides context and direction