Charts are frequently used to ease individual understanding of the massive data and the connection between different parts of the data (Walker et al. 2015). Through the use of charts, one can quickly read and understand raw data. In this paper, I will examine the hierarchical charts and state the reasons for selecting this category of charts.
Hierarchical charts are tools used to portray information relating to different organizations, systems, or ideas from the highest to the lowest position. The connection lines between the two elements explain the relationship or connection between them (Walker et al. 2015). Thiscategory of charts most applies in the business and education fields. Hierarchical diagrams are an excellent example of charts commonly used to portray information in an essay to read way and in a friendly format. For individuals who are visual learners, these categories of charts can immensely improve their ability to understand information. People use hierarchical diagrams in meetings, and lectures to help reduce the monotony of written words by using visual representations to communicate specific ideas (Bikakis et al. 2017). Therefore, hierarchal charts apply to people and other concepts and ideas such as the hierarchy of needs and values where particular element remains positioned above another based on their importance.
The reason for choosing this chart over other categories is that it can easily portray information in situations where one concept of object is directly related to each other. Different from other groups of charts, hierarchical charts define its features, thus enabling an individual to understand the whole relationship concept clearly (Walker et al. 2015). In this category of charts, representation of information happens in the form of different distinct levels. Primarily, Hierarchical chars highly benefit users for its visual communication of data and information, which is more influential than using classic texts.
Bikakis, N., Papastefanatos, G., Skourla, M., &Sellis, T. (2017). A hierarchical aggregation framework for efficient multilevel visual exploration and analysis. Semantic Web, 8(1), 139-179.
Walker, J., Borgo, R., & Jones, M. W. (2015). TimeNotes: a study on effective chart visualization and interaction techniques for time-series data. IEEE transactions on visualization and computer graphics, 22(1), 549-558.
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