Graph Reconstruction

Introduction

This assignment involved locating a graph online detailing scientific findings in a relatively improper way. Subsequent tasks involved pinpointing the areas for improvement, extracting the data from the graph, and altering the graph accordingly in R studio. I utilised GitHub, a social coding platform that allows users to create, manage, and collaborate on code in real-time. GitHub is an advantageous software to learn, given its capabilities in facilitating collaboration in research analyses.

Previous Graph

Figure 1. Mortality caused by whaling efforts: A bar graph absent of uniformity, x and y axes, and proper time series visualisation.

The authors are attempting to illustrate the number of whales intentionally killed by humans each year. These values are divided into 3 categories: traditional whaling, commercial whaling, and whaling for “scientific purposes.” The data is derived from various countries including Denmark, St. Vincent and the Grenadines, Russia, USA, Norway, Iceland, and Japan.

While the colours used in the plot aid in distinguishing the causes of death, the visualisation of the graph could be improved. Namely, 3 problems with the plot include the lack of uniformity regarding the use of numbers above each bar, the absence of x and y axes labels, and the unclear legend concerning the effects imposed by each country. Additionally, a line graph would have been more suitable for displaying the data as opposed to a bar graph.

Reconstructed Graph

Figure 2. Mortality caused by whaling efforts from 2005-2017. Graph illustrates the number of individual deaths associated with each type of whaling (commercial, scientific, and traditional). Commercial whaling involves Norway and Iceland, scientific whaling involves Japan, and traditional whaling involves Denmark, St. Vincent and Grenadines, Russia, and the United States.

The bar graph was obtained from the Statista website. The article containing the bar graph of interest is entitled “Whaling: No End In Sight.” Although the graph indicates the source to be the International Whaling Commission (IWC), the dataset was not provided as ‘supplementary information’ within the article. In order to overcome this obstacle, the application ‘plotdigitizer’ was utilised to extract the data from the published bar graph. Once the data had been extracted and formatted into a .csv file, I imported it into R studio for analysis. To address the issues within the graph and enhance visualisation, I opted to transform the initial bar graph into a line graph. Furthermore, I added x and y axes labels and ensured the time-series data was illustrated in a clear manner.

Code

The code used to formulate the graph is linked below using the GitHub platform.

Link to Repository

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