DATA VISUALIZATION

One of the constant features of M&E work is the representation of data. M&E personnel find themselves in positions where they need to or have to represent data to different audiences such as donors, local level stakeholders, and organizational hierarchy among others. Not planning how to represent or visualize data means that M&E personnel find themselves in a situation where the method they choose is inappropriate for the audience, or generally becomes misleading.

Representing data in form of tables, pie charts and bar graphs is as basic as it can get. These data visualization techniques are age old and hardly, if at all, useful for demonstrating moderately complex associations/relationships. In some cases, they are ineffective or inadequate in illustrating trends that a RESEARCHERmight want to illustrate. In the evolving world of technology and advanced applications, there have emerged more appropriate ways of illustrating data. Here, we discuss five emerging trends in data visualization

1. Mapping

Mapping has, over the years, gained as an ideal way of visualizing data. This technique is both convenient and easy to interpret. Maps are an excellent ways of demonstrating prevalence or concentration and as such, identifying priority areas. With softwares out there such as ArcGIS and QGIS, this technique has quickly gained popularity, and deservedly so. The only back side to this is that a high level of expertise is required to create the maps. Training on the use of the relevant software is necessary. Nevertheless, with plenty of open source learning platforms out there, this is technique is worth investing time on. In any case, once you learn how to create maps, it is pretty much exiting all the way.

 

Map courtesy of WFP (2013): Global Food Security Update, Issue 9

2. Infographics

Another data visualization trend to emerge recently is the Info-graphic. An info-graphic is a diagrammatic representation of data. The good thing about info-graphics is that it allows the data analyst to make total use of his/her imagination in order to most appropriately represent the data. In designing info-graphics, there are simply no conventions. The more unique it is the better. Also works well for both elite and illiterate audiences. As is the case with GIS, several platforms online allow you to create info-graphics. Some even have customizable templates, allowing one to simply tweak them to suit their own needs. Online platforms for this include Infogr.am and Visual.ly

 

Infograph courtesy of GOOD Worldwide LLC (2013)

 3. Boxplots

Box plots, although a relatively old data visualization technique has not been widely used in the past. However, in recent years, the use of boxplots in representing data is slowly increasing. This technique is emerging as an alternative for having summary statistics such as mean, median and interquartile ranges. Boxplots can also be used to show how varied data is from the mean and in what direction the data is skewed. It is simple to draw even in programs such as Excel, R, Stata and SPSS and requires little or no expertise.

 

 4. Scatter Diagrams

Scatter diagrams are a good way of showing linear relationships between two variables. In scatter diagrams, data is plotted on a graph.  It is called a scatter diagram since the plotted data is usually scattered all over the graph. Nevertheless, it is usually possible to establish the relationship between the variables being plotted by drawing a line of best fit. The line of best fit is a straight line that attempts to cut across all the plotted dots. This line of best fit shows whether there is a positive or negative relationship between the variables that have been plotted.

What other data visualization techniques are you using to visualize your data?

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