Sometimes as a data scientist or regular scientist, we produce beautiful charts that are chock-full of meaning and data, however to those in the outside world, it can be misconstrued. To avoid the scenario of misreading your graphs on a dashboard, paper, or even a blog post, sometimes context is needed. The amount of context needed will depend on the complexity of understanding and severity of misinterpretation. The higher the complexity the more contextual text is needed to help the reader digest the information you are presenting. The higher the severity of misinterpretation, i.e. life-threatening if misread or loss of millions of dollars, should also include more contextual text.
Contextual text can help a reader understand your tables, graphs, or dashboards but not every instance requires the same level of detail throughout. The following are just meer examples of what light, medium, and heavy context could include:
Light Context (bullet points)
- Source system or source details
- Details on allocations impacting objects in a model
- Details on data joins or algorithms used
- Data nuances (excludes region x)
Medium Context (Calling out use cases)
- A succinct explanation of what the user should be able to get out of the report/reporting area, graph, table, or dashboard
Heavy Context (Paragraph Explanations)
- The best example is the results section of a scientific peer-reviewed journal, which not only has a figure description, but they go into detail about areas to pay attention to, outliers, etc.
Below is an example from the National Hurricane Center’s (NHC) 5-day forecast cone for Tropical Storm Sebastian. Notice the
“Note: The cone contains the probable path of the storm center but does not show the size of the storm. Hazardous conditions can occur outside of the cone.” (NHC, 2019).
This line alone falls under light context until you add the key below, which is a succinct explanation of how to read the graphic, making the whole graphic fall under medium context.
A secondary image produced originally by the NHC for Hurricane Beryl in 2016 shows an example of a heavy context below the NHC image, when text is added by an app. In this application, where this image is pulled from, the following block of text states the following (Appadvice.com, n.d.):
“This graphic shows an approximate representation of coastal areas under a hurricane warning (red), hurricane watch (pink), tropical storm warning (blue) and tropical storm watch (yellow). The orange circle indicates the current position of the center of the tropical cyclone. The black line, when selected, and dots show the National Hurricane Center (NHC) forecast track of the center at the times indicated. The dot indicating the forecast center location will be black if the cyclone forecast to be tropical and will be white with a black outline if the cycle is …”
- NHC (2019). Tropical Storm Sebastien 5-day forecast cone. National Hurricane Center. Retrieved from https://www.nhc.noaa.gov/archive/2019/SEBASTIEN_graphics.php?product=5day_cone_with_line
- Appadvice.com (n.d.). App Advice: National Hurricane Center data. Retrieved from https://appadvice.com/app/national-hurricane-center-data/1289108781