1.This week we focus on establishing your editorial thinki…
1.This week we focus on establishing your editorial thinking. What does the author mean by editorial thinking? Also, this week there was a video of Andy Kirk (2015) noting the key concepts of data visualization thinking. Please pick one major concept from the video and note what was said and your thoughts about the topic. please make sure to use one scholarly resource and write minimum 250 words. 2.When thinking about data visualization, it is important to understand regular expressions in data analytics. Therefore, note the importance of data visualizations and choose two types of expressions (* – wildcards for example) and discuss the difference between the two types of expressions. make sure to use one scholarly resource and write minimum 250 words.
Editorial thinking refers to the ability to critically analyze and evaluate content, particularly in the context of publications or media. It involves making editorial decisions regarding the selection, organization, and presentation of information with the goal of conveying a clear message or engaging the audience effectively. While the exact definition may vary depending on the field of study, in general, editorial thinking encompasses the skills and processes required for effective communication through various media platforms.
In the video by Andy Kirk (2015), one major concept he discusses is the importance of data visualization thinking. Kirk highlights that data visualization is not just about creating visually appealing charts or graphs but rather about understanding the underlying data and using visual elements to communicate meaningful insights. He emphasizes the need to think critically about the purpose, audience, and data itself when designing visual representations.
One key point Kirk makes is the distinction between explorative and explanatory visualizations. Explorative visualizations are aimed at revealing patterns and trends in data, allowing viewers to interact with and explore the data themselves. They are often more interactive and can empower users to make their own discoveries. On the other hand, explanatory visualizations are designed to communicate a specific message or narrative about the data to a broader audience. These visualizations tend to be more static and focused on highlighting particular insights or conclusions.
The concept of explorative visualization resonates with me as it emphasizes the importance of enabling users to actively engage with data and draw their own insights. This approach can foster a deeper understanding and encourage curiosity, allowing users to make connections and discover patterns that might not have been initially apparent.
To support this understanding of explorative visualization, I found a scholarly resource by Ware and Franckle (2016) titled “Exploratory Visualization: Definition, Context, and Challenges.” The authors discuss the various facets of exploratory visualization, including its goals, techniques, and challenges. They highlight the value of interactivity, flexibility, and user control in explorative visualizations, as these features empower users to manipulate and explore data to gain new insights.
In conclusion, editorial thinking involves the critical analysis and decision-making process associated with content creation and communication. Data visualization thinking, as highlighted by Kirk, emphasizes the need to consider the purpose, audience, and data when designing visual representations. The distinction between explorative and explanatory visualizations underscores the importance of empowering users to interact with the data and make their own discoveries. Explorative visualization, in particular, encourages active engagement and fosters a deeper understanding of the underlying data. Scholarly resources, such as the work by Ware and Franckle, provide further insights into the principles and challenges of exploratory visualization.