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How do you cite and reference your data sources in your data visualization?

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Data visualization is the process of presenting data in graphical or pictorial forms, such as charts, graphs, maps, or diagrams. Data visualization can help researchers communicate their findings, highlight patterns and trends, and support their arguments with evidence. However, data visualization also requires careful planning, design, and citation to ensure accuracy, clarity, and credibility. In this article, you will learn how to visualize data in research reports using six steps.

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Adam Somers, ACAS

Actuarial Consultant at The Hanover Insurance Group

1 Choose the right type of visualization

The first step is to choose the type of visualization that best suits your data and your research question. Different types of visualization have different purposes and strengths, such as comparing, showing relationships, or illustrating distribution. For example, if you want to compare the performance of different groups, you might use a bar chart or a pie chart. If you want to show how a variable changes over time, you might use a line chart or a scatter plot. If you want to show how a variable is distributed across categories, you might use a histogram or a box plot. You can use online tools, such as Datawrapper or Tableau, to explore different options and create your visualization.

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Adam Somers, ACAS

Actuarial Consultant at The Hanover Insurance Group
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Selecting the best type of visualization of your data is paramount to translating all of your data and analysis into a story that engages your audience and advances your message. Taking the time to intentionally consider the type of visual you will use also helps to determine exactly what information is necessary to communicate your findings. We've all heard the phrase "that meeting could have been an email". The same sentiment applies to your visuals as well. A complicated graph with multiple lines, bars, and axes can often be less effective than simple charts that contain only the information you most want to convey.

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2 Follow the data visualization best practices

The second step is to follow data visualization best practices to ensure that your visualization is clear, accurate, and effective. Appropriate scales, labels, and legends should be used to make the visualization easy to read and understand. Consistent colors, fonts, and styles should be used to make the visualization visually appealing and coherent. Minimal and relevant text should be used to avoid clutter and distraction. Titles, captions, and annotations should be used to provide context and explanation for the visualization. Contrast, emphasis, and alignment should be used to draw attention to the most important elements of the visualization.

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Adam Somers, ACAS

Actuarial Consultant at The Hanover Insurance Group
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It's always worth it to budget time to format your reports or presentations. You may have identified a key piece of information and want to convey it quickly, but never underestimate the potential for your message to lose its full impact because your audience is distracted by inconsistent or poor formatting.

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3 Cite and reference your data sources

The third step is to cite and reference your data sources to acknowledge their origin and credibility. Data sources can be primary or secondary, depending on whether you collected the data yourself or obtained it from another source. You should cite your data sources in the text and in the reference list, following the citation style of your discipline or journal. For example, if you use the APA style, you should include the author, date, title, and URL of the data source in the text, and provide the full details in the reference list. You should also indicate the license and availability of the data source, if applicable.

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4 Embed or append your data visualization

The fourth step is to embed or append your data visualization to your research report, depending on the format and purpose of your report. If your report is digital, such as a web page or a PDF, you can embed your visualization directly in the text, using a suitable format, such as PNG, JPEG, or SVG. If your report is printed, you can append your visualization at the end of the report, using a high-resolution format, such as TIFF or EPS. You should also provide a clear link or reference to your visualization in the text, using a figure number and a title.

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5 Test and evaluate your data visualization

To ensure that your data visualization meets your objectives and expectations, you should test and evaluate it. Ask yourself or others questions such as if the visualization answers your research question or supports your argument, if it conveys the main message or insight that you want to communicate, if it follows the data visualization best practices and the citation style guidelines, if it fits the format and purpose of your research report, and if it appeals to your target audience and their needs and preferences. You can use feedback, surveys, or analytics to collect and analyze the responses and make improvements if needed.

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6 Share and disseminate your data visualization

The final step is to share and disseminate your data visualization to reach and engage your intended audience. You can share your visualization through various channels, such as social media, blogs, newsletters, or presentations. You can also use interactive features, such as filters, tooltips, or animations, to enhance the user experience and encourage interaction. You should also monitor and measure the impact and performance of your visualization, using metrics, such as views, shares, comments, or citations.

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How do you cite and reference your data sources in your data visualization?

1

2

3

4

5

6

1 Choose the right type of visualization

2 Follow the data visualization best practices

3 Cite and reference your data sources

4 Embed or append your data visualization

5 Test and evaluate your data visualization

6 Share and disseminate your data visualization

Research

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How do you cite and reference your data sources in your data visualization?

1

2

3

4

5

6

1 Choose the right type of visualization

2 Follow the data visualization best practices

3 Cite and reference your data sources

4 Embed or append your data visualization

5 Test and evaluate your data visualization

6 Share and disseminate your data visualization

Research

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