Graphical excellence is that what gives the viewer the greatest number of ideas in the shortest time with the least ink in the smallest space.

I read this quote in different variations over the years, and you can see that it is old as it refers to ink rather than pixels. Nevertheless, it is very true still today. In terms of data visualization this is the one single rule you need to remember. In this blog I will apply it to a report, however the rule is not limited to that – it applies to any data visualization.

So, how can we save some ink, space and time?

This golden rule works in many different ways, but in the big picture there are four categories that you can follow

1. Remove redundant information. If data is redundant it can generally be grouped, so you only need to label it once. This saves space, ink and time.
2. Maximize information density, sometimes explained as maximizing the data ink-ratio. Can you use less words to convey the same information? A bar chart may visualize data of a million records in just a small space.
3. Show the information. Don’t forget to show all information. Leaving critical information out may be as serious as distorting the information. Also make sure that the viewer understands the information the way it is presented, and keep your audience in mind. Printing on a monochrome paper should not reduce the information and don’t forget that 10% of your audience may be colorblind.
4. Remove useless information. If the information does not add any value, don’t show it. Respect the cost of screen real estate, and don’t distract your viewer with data that is not necessary. Practical examples are useless labels or thick distracting borders around charts or tables.

Represent the truth.

Only show data that is reliable and correct. Your user must be able to trust your report blindly or it is absolutely useless. This is a big responsibility that lies with the developer of the report, and should not be taken lightly. Needless to say the consequences of making the wrong decisions based on unreliable data can be disastrous in any industry. If there is data that can be questionable at times and you have no other option than to display what you have right now this needs to be indicated clearly. My opinion? Better not to show it at all.

Also make sure that if the user runs the same report for a second time that it shows the same data. Sure, your busy OLTP database may have new records or updated information in it by now, but it means that the previous reports’ data was incomplete – so you allowed your user to potentially make a bad decision based on incomplete data.

Representing the truth is not limited to just showing valid and up-to-date data. Practices like changing the Y axis’ value to 1000 instead of 0 may be useful to save space and ink, but you may risk that the data is misinterpreted. Using logarithmic scales can have the same negative effect. When visualizing numbers make sure that the representation is directly proportional to the surface of the graphic itself, and that these proportions are the same through-out your report – even if the value represents something else.

Final thoughts

These two rules are clearly not limited to reports. Think about every pixel that you use in your UI, so always respect your screen real estate. Is it a distraction or does it add value to the viewer? Is that label absolutely necessary or are my users smart enough to recognize that values meaning? These are questions you should ask yourself every time you visualize data. Representing the truth is probably more important than thinking about any pixel; feed your user invalid information once and he will refrain from using your system. The details of good data visualization goes way beyond the scope of this post, however these two rules are a great starting point that everyone should know. What do you think about these rules?

Please share the post if you learned something, and leave your comments or questions below!