The Significance of Data Visualization
Over thousands of years, humans have developed and perfected the practice of collecting and analyzing data. Over time, we have found that data is a valuable asset that empowers people and organizations to identify problems, gather accurate information, and make informed decisions. Data collection and analysis are highly effective. Even so, data visualization takes things a step further, allowing people to dissect and display complex information in a comprehensible and user-friendly way.
According to TechTarget, “Data visualization is the practice of translating information into a visual context, such as a map or graph, to make data easier for the human brain to understand and pull insights from. The main goal of data visualization is to make it easier to identify patterns, trends, and outliers in large data sets. The term is often used interchangeably with others, including information graphics, information visualization, and statistical graphics.”
Data visualization is powerful and impactful. Visual representations of data allow people to relay a specific message utilizing numbers and records to support their case. However, data visualization can also misconstrue messages, aid with misinformation, and result in the use of data to tell a desired story as opposed to the truth.
Technological Advances and Data Visualization
With time, humans have discovered and invented more efficient ways to collect, process, analyze, and display data. Today, “software tools for a wide range of visualization methods and data types are available for every desktop computer.” With the impact of the Information Age, people’s practices have generally evolved, resulting in the replacement of physical objects with digital representations. This makes capturing and displaying data much more accessible and cost-effective.
However, now that data visualization exists within anyone and everyone’s reach, it is much more difficult to track progress within the world of data visualization, especially historical progress. Michael Friendly writes, “it is hard to provide a succinct overview of the most recent developments in data visualization, because they are so varied, have occurred at an accelerated pace, and across a wider range of disciplines. It is also more difficult to highlight the most significant developments, that may be seen as such in a subsequent history focusing on this recent period.”
Furthermore, data visualization, like everything else, requires context that communicates our reality. Without this context, an audience will not receive correct, important, and meaningful information. Although technological advances make it easier to automate data visualization, these advances can also result in missed opportunities in which we are displaying and sharing data that is useless, confusing, or misleading instead of sharing information with its significance and relevance in mind. To incorporate our reality into data visualization, Giorgia Lupi suggests that, when dealing with data, people should prioritize and practice data humanism. With the implementation of technological advances, we begin losing our human touch. According to Lupi, achieving data humanism occurs by embracing complexity, moving beyond standards, incorporating context, and remembering that data is imperfect. She states, “to make data faithfully representative of our human nature, and to make sure they will not mislead us anymore, we need to start designing ways to include empathy, imperfection, and human qualities in how we collect, process, analyze, and display them.”
Though technology has benefited us in many ways, it is imperative to ensure that what we publish and share is genuine, true, and captures the essence of human nature.
What Makes a “Good Chart”?
A good chart must be easily understandable. Most audiences include individuals from varied backgrounds who have distinct ways of processing information. Therefore, a good chart should be simple, clear, and self-explanatory. Elements that support a comprehensible chart include keys/legends, explicit titles, stated units of measurement, and labels.
From a designer’s standpoint, a good chart must involve the elements and principles of design. Some examples of elements are line, shape, color, texture, type, space, etc. Principles include alignment, balance, hierarchy, emphasis, contrast, movement, proportion, white space, and more. Maintaining the elements and principles of design help with creating charts that are widely understood.
I respond well to charts and graphs that maintain a distinct use of color balanced with decent whitespace. Additionally, I am easily overwhelmed by graphics that contain a sizable amount of complex information, so I appreciate charts that are simple and easily absorbable. Furthermore, I love work that pushes the boundaries of how data can be visualized, displaying data in unique and engaging ways. I also love charts that include visual elements such as photos, illustrations, and icons. Finally, I value useful, functional, and interactive data visualizations. In recent years, I have become familiar with bullet journaling and mood tracking, which has been very helpful for me.
Here are some examples of good charts I respond to:
Distinct Color Balanced with Decent Whitespace
Simple and Easily Absorbable
Charts that Exemplify Divergent Thinking and/or Include Visual Elements
Source 1, Source 2, Source 3, Source 4: Photos I took of the menu of a restaurant I visited in Orlando last year
Functional, Useful, and Interactive Data Visualizations
Source 1: Functional information to navigate the DMV subway system, Source 2: A quick reference guide for photography, Source 3: Useful information to support color theory in design, Source 4: Informative information about typography for designers, Interactive Data Viz
Sola's Thoughts 