At the heart of all journalists is a drive to tell stories. Combine this drive with an endless sea of data, and writers are left in a strange place. Embrace the analytics? Or hold onto the seemingly primitive practice of relying solely on words to tell compelling stories? These questions will likely be challenging for writers to answer at first, considering how most writers dedicate their time to creative output rather than interpreting graphs and charts. At this point, though, I hope it is clear that there is no escaping our increasing reliance on data. Data is everywhere. Whether you are scrolling through Instagram, watching the weather report on your local news station, attending your yearly physical at the doctor’s office, requesting an Uber, or managing your bank account– you are constantly exposed to data. Information is being poured into our eyes at higher rates than ever before. It is only a matter of time before all journalists, maybe even all writers, begin to regularly incorporate data into their works.
Yet journalists must always remember their roots. Storytelling is fundamental to journalism. With the drive to tell stories comes the drive to find patterns in everyday occurrences. Applying this fascination with storytelling to the visualization and communication of data may be the perfect way to bridge our creative side with our analytical potential. This is truly why data storytelling is a perfect avenue for journalists to develop their data literacy. Not only does data storytelling enhance the reader’s connection to the data, but it equally allows for journalists to make their own connection to the data as well.
Journalists must also remember their purpose in society– to accurately inform their readers. In addition to facilitating strong connections between readers and the data, journalists are equally expected to represent and interpret the data in an accurate manner. In an age of misinformation, it is crucial for writers to understand the ramifications of misleading data visualizations, whether these misleading visualizations were originally meant to mislead the viewer or not.
Finally, journalists must not fear the current age of big data, even with little analytical experience. Given the plethora of free data visualization tools and open data sources just waiting to be used, there is no excuse for avoiding the analytics.
Embrace the data. Develop your data literacy. Continue telling your stories.
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Engebretsen, Martin, and Helen Kennedy. Data visualization in society, 2020, https://library.oapen.org/bitstream/handle/20.500.12657/22273/9789048543137.pdf?sequence=1%20
McCandless, David. "The Beauty of Data Visualization." TED-Ed, 2010, https://www.youtube.com/watch?v=5Zg-C8AAIGg.
Miller, Jed and Jarvis, Michael. "4 lessons covid-19 teaches us about data-driven communication." World Economic Forum, 2020, https://www.weforum.org/agenda/2020/06/4-lessons-covid-19-can-teach-data-driven-storytelling/.
Nussbaumer Knaflic, Cole. “What is Story?” Storytelling with Data, Spotify, 2017, https://open.spotify.com/episode/5Di9FxX4l1CxR9Zj8dloQJ
Patel, Hiren. “These Are the Best Free Open Data Sources Anyone Can Use.” FreeCodeCamp.org, 2020, https://www.freecodecamp.org/news/https-medium-freecodecamp-org-best-free-open-data-sources-anyone-can-use-a65b514b0f2d/.
Rogers, Simon. “The State of Data Journalism in 2017.” Google News Initiative, Google, 2017, https://blog.google/outreach-initiatives/google-news-initiative/data-journalism-2017/
Stobierski, Tim. "Top 6 data visualization tools for business professionals." Harvard Business School Online, 2021, https://online.hbs.edu/blog/post/data-visualization-tools.
Torban, Alli. “How to Turn Data into an Experience.” Data Viz Today, Spotify, 2020, https://open.spotify.com/episode/1OfF6GLWnMfFz3luajHQk6
Note: examples of data visualization throughout the e-text are cited in-text, underneath each visual.