In the era of information overload, visual data has emerged as a powerful tool to communicate complex information succinctly and effectively. From infographics capturing global trends to charts explaining financial data, the vocabulary of visual data is rich and diverse. This compendium provides an A-Z guide that explores the language of infographics, charts, and graphs, offering insights into the terms and concepts that shape how data is presented visually.
A
**Abstract Visualization**: An abstract representation of information, which eschews literal depictions in favor of shapes, symbols, and patterns to convey meaning.
**Alphabet chart**: A graph that uses the letters of the alphabet to represent data points, often found in educational materials to simplify complex numerical information.
B
**Bar Chart**: A chart that uses rectangular bars of varying lengths to illustrate the values of different variables; horizontal bars are typically referred to as “horizontal bar charts.”
**Bubble Chart**: A chart that uses bubbles to represent different variables in a statistical model, particularly useful in displaying the relationships between three quantitative variables.
**Color Coding**: A means of visually differentiating data points within a visual graph or map based on different color shades or hues.
C
**Cartesian Coordinates**: A system used to map objects in a plane or space using two or three numerical parameters, which makes it an essential part of graphic representation.
**Complexion**: A set of colors used together as a background color or within a visual graph to convey meaning or emphasize differences.
D
**Dashboard**: A visual display presenting information in easy-to-digest formats, such as charts, graphs, and other visual elements, typically for monitoring and managing a business metric.
**Data Visualization**: The use of visual elements like charts, graphs, and maps to present data in a visually understandable format, making it easier to extract insights from the information.
E
**Edge-to-Edge**: A design technique where visual elements continue across the edges of a display, providing an unbroken flow of graphics and information.
**Efficiency**: The degree to which the visual presentation of data requires a viewer to process information quickly and accurately.
F
**Flesch Reading Ease**: A measure that indicates how easily a reader will be able to understand a written piece, often employed in creating accessible infographics.
**Fractal**: A pattern that is self-similar across different scales; fractal images can offer a unique and intricate way to represent complex data.
G
**Genre**: A type of visual data representation, like a flowchart, pie chart, or graph, each of which has its own purpose and typical use case.
**Graphical Clutter**: An overly busy arrangement of visual elements that can make an infographic difficult to interpret and overwhelming to the viewer.
H
**Hierarchical Charts**: A way of organizing items in layers, often in vertical stacks, where categories are nested within other categories.
**Hue, Saturation, and Value**: The three components of color that together establish the way an individual perceives and describes color.
I
**Image Map**: An image divided into rectangular or irregular sections that function as a map; each section can correspond to a different destination or action.
**Interactivity**: Allowing the viewer to manipulate or interact with a visual representation to gain different perspectives or insights.
J
**Juxtaposition**: The act of placing or presenting things side by side or in close proximity to each other, often to highlight differences or comparisons.
K
**Kinetics**: The study of motion in the context of visualization, such as the gradual animation of a graph or map to display changes over time.
L
**Legibility**: How clear and easy-to-read the data is, a critical factor in making sure the intended message is not lost in visual noise.
**Line Graph**: A graph with a series of data points connected by straight lines to help understand the change in value over time or another continuous variable.
M
**Mapping**: Representing the elements of data, such as quantities or distribution, as spatial areas within defined boundaries of the Earth or another space.
**Modularity**: The degree to which separate elements of an infographic or visual display can be easily interpreted by themselves or as a part of the whole.
**Narrative Visualization**: Approaches to visualizing data that employ storytelling techniques to make complex information more relatable and engaging.
N
**Node**: A point within a graph or visual layout that represents a single element such as a data point or a collection of points.
**Normalization**: The transformation of data to make it more intuitive for plotting, commonly used in the construction of charts and graphs.
O
**Orbit Chart**: A chart that uses ellipses to represent the path of an object in a gravitational field, such as a solar system, which can also be adapted to data visualization.
P
**Pan and Zoom**: Enabling viewers to move through a visual display, zoom in or out, and explore the data on smaller or larger scales.
**Pie Chart**: A circular statistical chart divided into segments to represent quantities or percentages of a whole.
**Pattern Language**: The use of a series of graphical rules that can be combined to create visually cohesive and understandable infographics.
Q
**Quantitative Visualization**: Presenting data using maps, graphs, illustrations, or images, to show the magnitude, frequency, or distribution of values.
R
**Realism**: The degree to which a visual representation accurately reflects the real-world phenomenon it is meant to depict, often a goal for scientific and economic charts.
**Representation**: Any form of data — be it a chart, graph, or map — that displays relationships or differences between variables.
S
**Stacked Bar Chart**: A bar chart where the categories are stacked on top of each other to compare the percentage contribution of each category to the whole.
**Scatter Plot**: A graph that uses dots to show the relationship between two quantitative variables, which can reveal trends or clusters in the data.
**Semantic Mapping**: Representing the relationships between different elements in a dataset through symbols and their meanings within the context of the given data.
**Sympathy**: How the audience resonates or connects emotionally with the visual representation of data.
T
**Temporal Visualization**: Presenting data that includes or incorporates the element of time.
**Tone**: The emotional message or mood conveyed by a visual, which can influence the viewer’s interpretation and perception of the data.
U
**Univariate Analysis**: Examining a single dataset at a time, which is often the foundation for creating plots such as histogram or line graph.
**Visualization Taxonomy**: A classification system that categorizes various types of visual data representation according to their characteristics.
V
**Variable**: Any quantity, quality, or aspect of a phenomenon that can change and be observed or measured in an experiment or data collection.
**Vocalization**: Enhancing an infographic’s storytelling ability through the addition of labels, annotations, and other descriptive elements.
W
**Whitespace**: The areas within a visual representation that are empty or unoccupied by visual elements, often used for organization and readability.
X
**X-axis**: A horizontal axis used in plotting data. In two- or three-dimensional plots, it is often used for quantitative, independent variables.
**X-Y Plot**: A type of plot in which the horizontal axis represents one variable, and the vertical axis represents another. It is often used to display correlations between variables.
Y
**Y-axis**: The vertical axis in an X-Y plot, typically displaying the dependent variables when the X-axis represents independent ones.
**Yin and Yang**: The Chinese concept of complementary forces that are interdependent and give rise to each other’s traits. In data visualization, this can be applied to the concept of balance in presentation.
Z
**Zero-Length Bar**: In a bar chart, a bar that has no real length, indicating the absence of data or a category that makes zero sense in the context.
The vocabulary of visual data is a nuanced array of terms and concepts that encapsulate the art and science of turning complex information into clear, compelling narratives. Understanding these terms will empower anyone to create and decode the visual stories that lie within infographics, charts, and graphs.