Further reading on hightlights

Data commentary is an essential aspect of research writing, allowing authors to present their findings in a way that is both informative and engaging. In this article, we will explore the second element of data commentary – highlighting – and discuss how it can be both descriptive and analytical. We will also provide practical examples to help you enhance your own data commentary.

• The Descriptive and Analytical Nature of Highlighting

Highlighting is an integral part of data commentary that involves selecting and emphasizing specific parts of the data. While the language used in highlighting is descriptive, the decision-making process of selecting which data to emphasize is analytical. This process requires the author to evaluate the data and choose the most significant or interesting aspects. By making these decisions, the author demonstrates their expertise and guides the reader through the data.

• Choosing the Right Information to Highlight

When selecting which data to highlight, authors should consider the overall trends, patterns, and interesting findings. It is essential to avoid repeating all the numbers and figures from the visuals, as this can be overwhelming for the reader. Instead, focus on the most dominant patterns or key points. This not only makes the commentary more concise but also ensures that the author’s voice is heard.

• The Language of Highlighting

In order to provide a clear and vivid description of the data, authors should use a combination of descriptive verbs, adjectives, and adverbs. Some common descriptive verbs include “shows,” “illustrates,” and “displays,” while adjectives like “stable,” “significant,” and “striking” can add depth to the description. Adverbs such as “slightly,” “rapidly,” and “steadily” can also be used to further clarify the data commentary.

• Describing Trends and Patterns

When describing trends and patterns in the data, authors should consider the overall direction and fluctuations of the data. This can be achieved by using specific verbs and adjectives to describe the peaks, dips, and plateaus in the data. Additionally, discussing the changes over time can help to emphasize the patterns and trends observed in the data.

In conclusion, effective data commentary involves a combination of descriptive and analytical elements, with the author carefully selecting which data to emphasize and using appropriate language to describe it. It is essential for authors to consult model articles in their specific field to ensure that their data commentary aligns with the conventions and expectations of their discipline. By mastering the art of highlighting, researchers can create more engaging and informative data commentaries that effectively communicate their findings.