How do you evaluate the quality and credibility of data visualization and tables from other sources?

1 Check the source

The first step to evaluate the data visualization and tables from other sources is to check the source of the data and the author of the visualization or table. You should look for clues that indicate the reliability, reputation, and expertise of the source and the author. For example, you can check if the source is a peer-reviewed journal, a reputable organization, or a credible website. You can also check if the author has relevant credentials, affiliations, or publications. If the source or the author is unknown, unclear, or suspicious, you should be cautious about trusting the data visualization or table.

2 Check the data

The second step to evaluate the data visualization and tables from other sources is to check the data itself. You should look for information that explains how the data was collected, analyzed, and presented. For example, you can check if the data has a clear and relevant research question, a well-defined and representative sample, a valid and reliable measurement, and a transparent and appropriate analysis. You can also check if the data has any limitations, assumptions, or uncertainties that are acknowledged and addressed. If the data is missing, incomplete, or inconsistent, you should be skeptical about the validity and accuracy of the data visualization or table.

3 Check the design

The third step to evaluate the data visualization and tables from other sources is to check the design of the visualization or table. You should look for features that enhance the clarity, simplicity, and honesty of the visualization or table. For example, you can check if the visualization or table has a clear and informative title, a suitable and consistent format, a logical and coherent structure, and a legible and attractive appearance. You can also check if the visualization or table has any labels, legends, scales, or annotations that explain the data and its meaning. If the design is confusing, complex, or misleading, you should be critical about the interpretation and implication of the data visualization or table.

4 Check the message

The fourth step to evaluate the data visualization and tables from other sources is to check the message of the visualization or table. You should look for aspects that convey the purpose, significance, and implication of the data and its visualization or table. For example, you can check if the message is relevant, accurate, and complete. You can also check if the message is supported by evidence, logic, and context. You can also check if the message is objective, balanced, and unbiased. If the message is irrelevant, inaccurate, or incomplete, you should be wary about the credibility and quality of the data visualization or table.

5 Check the audience

The fifth step to evaluate the data visualization and tables from other sources is to check the audience of the visualization or table. You should look for factors that influence the reception, perception, and reaction of the audience to the data and its visualization or table. For example, you can check if the audience is intended, expected, or actual. You can also check if the audience is informed, interested, or engaged. You can also check if the audience is influenced by emotions, biases, or expectations. If the audience is unintended, unexpected, or different, you should be aware of the potential gaps, misunderstandings, or conflicts that may arise from the data visualization or table.