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Data visualization is a critical tool for creating an effective engagement, understanding presented information and memorizing it. Engagement refers to being wholly involved in an activity based on the interest developed in the task. When one takes sufficient time on a certain task, it helps them have an in-depth understanding of different concepts and principles used to formulate the idea. Consequently, this makes one remember most of the elements presented in a particular activity. These three conceptions are critical in data visualization, hence discussed in this post.
Engagement is critical in data visualization, as it enables the audience to grasp key elements of any set of information. According to O’Reilly (2015), color and scales are some of the most useful tools to make effective engagements. Nuzzo (2019) agrees with O’Reilly by stating that color can help capture the attention of an audience to specific detail presented, for instance, through a stacked histogram. Therefore, when designing any data visualization tool, it is critical to consider how to maximize the time the target will be drawn to the presented information.
The essence of presenting data from research is to help the target audience understand and utilize it where necessary. According to O’Reilly, preattentive human cognition and understanding are two indistinguishable concepts. One should view the tool used to present the information and tell how various data relate. For example, the data visualization design should enable the comparability of different data elements, such as subgroups.
Lastly, it is also crucial for one to remember the different key attributes of the data. According to Kirk (2016), the effectiveness and the impact of a data visualization tool relies on its memorability. For example, using colors and scales can make one understand how various data elements relate. In a very large dataset, using different tools such as histograms, radars, pie charts, and scatter plots can help in memorizing the information.
References
Kirk, A. (2016). Data visualisation: A handbook for data driven design. Sage.
Nuzzo, R. L. (2019). Histograms: A useful data analysis visualization. American Journal of Physical Medicine & Rehabilitation, 11(3), 309-312.
O’Reilly (2015). Using Storytelling to Effectively Communicate Data Tutorial | Aims Of Data Visualization. [Motion Picture]. Web.
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