Creating a Visual Representation of Data: A Step-by-Step Guide
Information visualization, a powerful tool in data analysis, allows users to transform and modify data to suit their needs. This process can involve varying parameters for analysis or choosing different visual mapping options for the data set.
A Consistent Process for Designing Visualizations
The process for designing information visualizations is consistent, regardless of the end product. Experts like Riccardo Mazza have proposed a 5-step process to ensure the creation of effective and user-centered visualizations.
- Understanding the Data and Context The first step involves analyzing the data characteristics, the context in which the data exists, and the user's goals and needs. This helps ensure that the visualization addresses the right questions and provides relevant insights.
- Identifying Visualization Objectives In this stage, designers specify what they want to communicate. This could be trends, comparisons, or relationships. Clearly defined objectives guide the choice of visual encodings and representation methods.
- Mapping Data to Visual Forms This step involves selecting graphical elements to represent data dimensions effectively. It helps translate complex data into clear, interpretable visuals.
- Designing Interaction and Layout This focuses on how users will interact with the visualization and how visual components are arranged for clarity and emphasis. It improves user engagement and comprehension.
- Evaluating and Refining the Visualization Iterative testing with users evaluates whether the visualization meets its goals and is usable. Refinements are made to enhance effectiveness and reduce misunderstandings.
Types of Data and Relationships
Information visualization can represent three main types of data: quantitative, ordinal, and categorical. Spatial relationships, or geographical relationships, involve data that relates to the real world, such as map data or an office floor plan. Networked relationships involve data that relates to other entities within the same data set. Hierarchical relationships exist in data that relates to positions in a defined hierarchy, from an office management structure to a simple flowchart. Temporal relationships refer to data that changes over the passage of time.
The Power of Transformable and Manipulable Models
Combining transformable and manipulable models can create the highest level of interaction in information visualization. Transformable models enable users to modify data, while manipulable models give the user control over the generation of views, allowing them to zoom in or out on a model or to rotate 3-dimensional models in space for viewing from other angles.
A Case Study: The Enron Communications Network
The complexity and comprehensibility of information visualization can be affected by the number of dimensions or attributes of a data set. As an example, the image presented is an organization of the now-defunct Enron group's communications, which demonstrates the potential for visualizing vast amounts of data in a meaningful way.
Understanding a user's needs, the data to be displayed, the relationships in that data, and the kind of model required can help the information visualization designer deliver a model that meets those needs, providing insight, not just pictures, as Ben Shneiderman stated.
- User research is crucial in the design process of information visualizations, as it helps designers understand the user's goals and needs, ensuring the visualization addresses the right questions and provides relevant insights.
- In the realm of technology, data-and-cloud-computing plays a significant role in the display and manipulation of information visualizations, enabling users to transform and modify data to suit their needs, such as zooming in or out on models, or rotating 3-dimensional models for better understanding.
