[MUSIC] Hi and welcome back. One of my favorite pastimes is landscape painting. Before I start a new piece, I look at the subject, sketch it out, what will be included on the canvas and just as importantly what will be left out. The same idea applies to storytelling in general and data stories in particular. For the purposes of this lesson, I'm going to apply the word framing in a few different ways. All of which boil down to this. What's left in and what's left out. We will also discuss story conventions and when to bend them, as well as how to prime perception with framing and context. After this lesson, you will be able to recount the aspects of framing that you can use to craft your data story. You will also be able to describe how priming effects perception and interpretation. Let's get started. One of the most important sets of decisions that you will need to make for your data story is how to frame it. I'm going to use the term, framing, in a few different ways that all essentially mean what to include in what you present. There are several facets of framing to consider. One form of framing is literally what is included within a single view or a sequence of views. In other words, what is and what isn't shown inside of the viewer frame. Examples of this include a single slide in a presentation deck or a selected story point in Tableau. For our somewhat expanded definition, framing can also mean what level of granularity or level of detail is included in the story. As well as other parameters such as appropriate tone of the story and the domain to which the content belongs. Let's take a few moments to think about framing a story in relation to the design consideration checklist. We should have a good sense of the purpose, audience, and presentation constraints for our data stories. These will help us make decisions about the format, tone, and level of detail within the story. For example, for a presentation to the Acme Inc executive team, it might be a sequence of three Tableau visualizations using three story points. The tone for the story is somewhat conversational and it's about the success of the most recent marketing campaign. The audience is generally knowledgable about the topic but is time constrained and not interested in a lot of details at this point. Now because the presenter and audience know and trust each other, establishing credibility is not required in this particular presentation. However, it may be appropriate to indicate the level of uncertainty in the story and the potential need for further verification of the results. Now I'll note here that along with other efforts to make it as easy as possible to work with data, Tableau has created a level of detail or LOD expressions function. Which helps to make the process of aggregation and desegregation based under the desired level of detail easier to accomplish. Although this can be a somewhat more advanced topic, you might want to take a look at the Tableau Whitepaper, understanding level of detail expressions that is included in your resources. Now in traditional forms of storytelling, there are many clear conventions or common ways to do things within a certain context. For example, to read a play by Shakespeare, your eyes will move from left to right scanning the words. If you are watching a TV sitcom, you often see an establishing shot, like a coffee house or apartment exterior to set the scene. The conventions for telling stories with data are often far less clear-cut. In the case of a dashboard, our eyes may scan around quite a bit to try to make sense of what's going on and where to focus. The conventions for how to read a dashboard can be less clear-cut than say a traditional story obviously. In a dashboard the strongest visual elements, wherever they are, may capture our attention first rather than us directly focusing on a clearly designated starting point. Different formats have different conventions for how to utilize them. Of course conventions can also sometimes be broken to create more impact. That's said, breaking with convention can be tricky and requires a lot of solid thinking about why and how to do it. Let’s revisit the Minard visualization for a moment. The entire story of Napoleon’s ill-fated march into Russia is told in a single frame or view. That's very impressive. But if you think more deeply about it, some conventions are literally bent to make this work. For example, the path of the army's march begins on the left and moves towards the right. And then after many losses, the return path begins from the right and ends back on the left side. However, typically timelines start on the left and continue in one direction. In the case of Minard's visualization, time essentially doubles back on itself. The return proceeds from right to left which makes sense geographically, but less so in the context of a timeline as convention would have it. In a sense, the timeline convention is bent to make it work within a single frame, and with a map as a dominant context setter. The story of the march could be shown in a sequence of multiple frames, from left to right. But perhaps, that would have less impact than Minard's version. Again, it's generally a good idea to follow conventions, but they can be circumvented, if done for good reasons and you execute them well. Framing in context can change your perception quickly and with amazing effect. For example, look at this image. You may notice that when reading it from the left to right, it's an alphabet context, and there's a B that pops out in the middle. But if you read this from top to bottom in a number context, the middle figure is a 13. This is a simple example, but it suggests how much our perception of something can sometimes change dramatically depending on the context and the way it is viewed. In other words, an initial visual or textual stimulus can affect to how people react to subsequent content. Let's look at this picture, it may look like a bunch of black splotches in a white background. Now if I say, look at the dog, the Dalmatian in this image, do you see it? Some people might see the dog without prompting, but many others are more likely to see a dog if the word dog is presented to them when they first look at the image. Overall, this is an example of Gestalt principles, in that the animal emerges from a collection of black blobs. The ability to assemble those blobs into a meaningful image can be aided by how the image is initially described. Think about that in relation to a data story. Imagine something like a scatterplot with its collections and clusters of dots. Consider how the pattern of those dots might be affected by how the chart is labeled. Practice with using framing, conventions, and priming will improve your data storytelling skills. However, these same skills can be used to design a convincing story that turns out to be a false narrative as well. We will look at that in our next lesson. See you again soon.
