Click the Original, Code and Reconstruction tabs to read about the issues and how they were fixed.

Original


Data

Visualisation

Source: Lau and Pan (2015).


Objective

The objective of the visualisation is to compare the number of authors, publications and citations of three different universities and to also compare the growth rate of each variable for the different universities. The figure provides a way of assessing which university focuses on research and has the potential to grow in the industry.

The audience would be people interested in the contribution and potential in research of each university.

The visualisation chosen had the following three main issues:

  • The graph is confusing and difficult to read due to too much information being presented in very little space.
  • Line graphs are usually used to track changes over periods of time. In this case it has been incorrectly used since it is comparing growth rates of different universities. This can also mislead viewers to assume there is a non-existent trend.
  • The graph conceals its point since it is sectioned by university rather than variable. It encourages viewers to compare between variables rather than compare the universities.

Reference

Code

The following code was used to fix the issues identified in the original.

# install.packages("ggplot2")
# install.packages("viridis")
library(ggplot2)
library(viridis)
Uni <- matrix(c(1000,3000,3100,1200,7890,9000,500,800,670),ncol=3,byrow=TRUE)
colnames(Uni) <- c("Authors", "Publications","Citations")
rownames(Uni) <- c("Athena University", "Bravo University", "Delta University")
Uni <- as.table(Uni)
Unidf <-as.data.frame(Uni)

Uni2 <- matrix(c(2.8, 5.2, 7.2, 2.5, 10.1, 3.3, 1.2 , 12.4, 5.5),ncol=3,byrow=TRUE)
colnames(Uni2) <- c( "Authors","Publications","Citations")
rownames(Uni2) <- c("Athena University", "Bravo University", "Delta University")
Uni2 <- as.table(Uni2)
Unidf2 <-as.data.frame(Uni2)

p1 <- ggplot(data = Unidf, aes( x = Var2, y= Freq, fill= Var1)) +
  geom_bar(stat="Identity", position=position_dodge(), width= 0.75) +
  scale_fill_viridis(discrete = TRUE) + theme_minimal()+ 
  labs(title = "Comparison of the Amount of Authors, Publications and Citiations", x = element_blank(), y="Total Number") + scale_y_continuous(limits = c(0,10000)) + theme(legend.position = "bottom", legend.title = element_blank())

p2 <- ggplot(data = Unidf2, aes( x = Var2, y= Freq, fill= Var1)) +
  geom_bar(stat="Identity", position=position_dodge(), width= 0.75) +
  scale_fill_viridis(discrete = TRUE) + theme_minimal()+ 
  labs(title = "Comparison of the Growth Rate of Authors, Publications and Citiations", x = element_blank(), y="Growth Rate") + scale_y_continuous(limits = c(0,13)) + theme(legend.position = "bottom", legend.title = element_blank())

Data Reference

Reconstruction

The following plot fixes the main issues in the original.