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Data visualization in general means to bring abstract data and relationships into a visually comprehensible form. So far so good. But what are the unfamiliar forms of representation? When do I apply this? When are other forms more meaningful? I would like to introduce the project of Severino Ribecca to all those who ask these questions more often:

www.datavizcatalogue.com

 

This online catalog is a library of various information visualization types. Initially, the project Ribecca served to expand its own knowledge through data visualization and as a tool for one’s own work.

He himself writes about the project: “However, I would like to know how it is. Although there is no such thing as a visualization method, it is not the only way to make sense.

And, fortunately, Severino Ribecca does not hide the knowledge, right on the home page is in the middle:

http://www.datavizcatalogue.com

 

In addition to the first overview, the “Search by Function” option is particularly appealing to practitioners. Here again, the initiator relies on a fast-to-capture image language:

http://www.datavizcatalogue.com/search.html

As soon as you click on an icon, you get a well researched and edited knowledge about the selected visualization type. Each display form is displayed with its functionality and application possibilities and is visualized with dummy data. At the lower end of the description, the reader also finds references to similar display forms:

http://www.datavizcatalogue.com/methods/network_diagram.html

So there are a maximum of three well-structured clicks up to the knowledge about individual visualization forms. I find this project visually very successful and meaningful. Perhaps this tip gives you some inspiration for your information visualization?

 

In any case, I wish you Happy Reporting 🙂

Yours, Silja Wolff

 

 

 

 

The origin of portfolios is in finance and describes a planning method of compiling a package of security papers (security holdings) dependent on to the criteria of return and risk. Later, this method has been applied to other areas in the 70ies. Since that time the portfolio analysis has been modified in many cases and is one of today´s widespread analysis and planning instruments of strategic management.  The main idea of each portfolio is the segmentation and evaluation of data volume.

 

Basics of illustration

Most portfolios are illustrated two- or tree-dimensional. With three-dimensional illustrations the point size  is the third value perspective next to the axes. You hardly see four-dimensional portfolios. Here the bubbles are segmented as circular chart next to their value based figure.

Basic requirements to all illustrations is, as always, the efficient legibility. This is manageable due to a fast visual comprehension to evaluate data by colouring of bubbles or using diverse symbols. Also marked segmentation criteria, such as lines, will support comprehension.

 

Scaling and value intervals

 

Other than the typical bar and variation diagrams the scales do not have to start necessarily with zero.

A deliberate choice of value interval is necessary, if the segmentation should be demonstrated reasonably.

In this context reasonable means all points are visible and do not waste space/room.

The more frequently a portfolio with diverse data sets is used, the more important is the deliberate choice of the scale. Note: often times a change of the software automation is necessary, as automated portfolio axes always start with zero in Excel. This is less beneficial if all of your data is between the value of 350 and 480.

 

 

Ledgends and captions

A special attention should be placed on the topic legends and captions. Mark/write directly at the relevant diagram components. That will increase the legibility immediately. Should you make the decision of using a three-dimensional portfolio, the value has to be written directly at the bubble as there is no scale for it.

Strategic management is unimaginable without portfolios. Every evaluation, every portfolio approach consists of strengths and weaknesses. But irrespective of the type and structure of each portfolio, the visualisation is key for a beneficial usage of this analysis tool. The mentioned universal criteria above are a good frame for portfolio illustrations.

 

 

What are Bullet Graphs and where are they used?

Key data overviews on dashboards are easier to understand by visualisation. The realisation is quite difficult, because standardised diagrams are uneligible for this function. Bullet Graphs, a special type of bar diagrams, have been especially developed by Stephen Few. Basically they are very suitable for  those purposes, but they hold some disadvantages in its common form (see illustration 1 and 2), which we have solved in our projects due to a modified, optimised form of visualisation.

 

Illustration 1: The components of a Bullet Graph as it is regularly used in dashboards

  • Bullet Graphs are a special form of bar diagrams
  • They compare a presented key figure with a target value
  • By using background colours, additonal information of quality will be allocated
  • Bullet Graphs are often used in dashboards. They save space and replace tachometer
  • Bullet Graphs can be aligned horizontally or vertically

 

Illustration2: Dashboards with Bullet Graphs as they are often recommended and used

 

 5 disadvantages of this Bullet Graph illustration

  • The graphics become confusing very quickly, because many detailed information is shared, which is not necessarily needed or partly not available at all. For example the quality statement “bad, okay, good”. This disadvantage mainly occurs when many Bullet Graphs are displayed on one page (list of key data).
  • Variations of the goal are not visualised and therefore difficult to see. The only part easy to read is, if the bar of the just value is overstepping the target value. For the viewer it still would be important if the overstepping is good or bad and how large the variation is.
  • Coloured background areas distract the viewer from the main information, which is the bar of the just value and the target value. The coloured areas always look the same, no matter if the goal was reached or not. They rather disrupt the perception than to support it.
  • Background areas decrease the contrast towards the bar of the just value and target value. Thus, these essential graphical elements are difficult to see in the front.
  • Target areas are difficult to illustrate. In practice there are not only set target values (single values) for key data but often also for target areas. With this key data (KPI) the goal is considered achieved as long as the just value is between the minimum and maximum level of the target area.

 

How to ideally use the idea of Bullet Graphs in dashboards

For the use in dashboards we use a specially optimised form of Bullet Graphs (Illustration 3), which avoid the named disadvantages and bring additional visual features.

 

Illustration 3: Dashboard with Bullet Graphs recommended by chartisan

 

  • The simplified illustration without unnecessary background areas allows a quick overview
  • Indicated are the target values (single values) or target value areas (minimum/maximum level)
  • Variations will be highlighted in colours: positive (desired)= green, negative (undesired) = red. The extend of the variation is easily captured. Viewers immediately see where there is “a lot” red or green flashing.
  • The value caption is space-saving and clearly stored within the columns of the chart.
  • This optimised graphic form uses the strengths of the original Bullet Graphs and complements them with a visual drift indicator. The detail level has been reduced as much as possible, whereby these optimised Bullet Graphs are ideal for lists of key data.

 

By the way, we have managed and automised the displayed example with some tricks in Excel. As often the idea was key not the tool. Having said this, we hopefully could inspire you. Should you look for further good ideas for your reporting, contact us!