Very early on in this semester I was tasked with the challenge of producing a story supported by and revolving around data and graphs. It came as a bit of a shock to the system, with no previous experience using excel or various sites such as DataWrapper.
For my story produced about AFL Crowd figures post-Covid, I had to familiarise myself with DataWrapper in order to create data visualisations for the article. This also required some knowledge of graphs and excel to create the data to go into the charts which was difficult to learn, but it was so clear how far visualisations could enhance a story when worked in correctly.
The quality of my graphs in terms of relevance and suitability may not have been up to the highest standard it could have been due to the skill being so new to me. I used afltables.com as my source of data regarding crowd figures and although I knew it was reliable, I did struggle to copy the data from the side into excel and ultimately into DataWrapper. I feel as though I spent so much time just figuring out the programs that I didn’t put as much time into actually developing the story.
My initial fears were that I may not be able to properly incorporate the data in a way in which the story revolves around it. I didn’t want it to be all about Covid and then hit the readers in the face with a couple of random graphs, but I was finding it hard to fill up the word count speaking just about the data.
I do think that the article came out quite well and very readable. Although I did end up maybe including a bit too much speculation and opinion, it still complimented the data visualisations well and made for a fluid digital story.
Overall the use of data visualisations in the story benefited me greatly because it has given me the tools and knowledge to use going forward in future assessments that may require it as well as actual work for when I am graduated and writing articles for a job. It taught me that proper research on the issue that I was talking about is required to be able to provide insightful facts and information that bolsters the data rather than not supporting it.
