In an increasingly complex and interconnected world, the ability to understand and analyze data in a meaningful way becomes crucial. One technique for gaining a deeper understanding of your connected data is to visualize it as it evolves over time. Visualizing data over time benefits a wide range of industries and use cases, including finance, healthcare, supply chain management, and social networks. Enabling organizations to track the evolution of connections over time provides a competitive advantage and opens up new possibilities for strategic planning, risk management, and improved operational efficiency.
A graph visualization of tweets.
Connected data refers to information that is linked or related in some way, such as through networks, graphs, or hierarchical structures. Traditional methods of data visualization often fall short when it comes to representing the dynamic nature of connected data. As connections change and evolve, traditional methods can fail to convey the intricacies and patterns that emerge over time, which is where visualizing connected data becomes imperative.
Visualizing connected data offers several key benefits. It improves understanding, enhances decision-making, and provides better communication to identify risks or opportunities early.
An example computer network management application built with Perspectives.
Synchronized data visualizations support the discovery of actionable insights.
To effectively visualize connected data as it evolves over time, we can rely on several techniques. For example, timelines and animation are effective techniques for visualizing changes over time. Timelines can show how the data has evolved, while animation can highlight the specific change. Other techniques that are used for visualization include temporal graphs, interactive networks, static visualization, and post-situation analysis.
Visually compare the differences between two versions of the process.
A variety of tools and technologies are available to help visualize connected data as it evolves over time, such as Tom Sawyer Perspectives, which offers an animated timeline view as well as customizable options for visualizing connected data. In addition to a timeline view to visualize connected data over time, Perspectives includes customizable toolbar options; graph animations to preserve the mental map; graph editing tools for adding, deleting, and moving nodes and edges; and customizable view types to facilitate interactions with graph data.
An animated timeline in Perspectives showing data evolving over time.
Other key features available that help you gain actionable insights into your data as it evolves include:
As we continue to navigate the complexities of an interconnected world, the ability to visualize connected data as it evolves over time becomes increasingly important as it takes data analysis to a whole new level through its ability to visualize the evolution of connections. By animating the progression of relationships between entities, users can uncover hidden patterns, track the impact of dynamic factors, and identify emerging trends that would otherwise go unnoticed.
By leveraging techniques such as temporal graphs, interactive network visualizations, and timeline visualizations, we can gain valuable insights, make more informed decisions, and communicate complex information more effectively. With the help of tools and technologies like graph animations, customizable view types, and editing tools, we can unlock the potential of connected data and harness its power to drive innovation and understanding in various domains.
Contact us to get started on your graph journey with a free demonstration of Perspectives from one of our graph experts.
Janet Six, Ph.D. is Senior Product Manager at Tom Sawyer Software, where she works with business, technical, and design teams to help create effective data visualization and analysis solutions within technical, time, and financial constraints. She has been in the graph field for almost 30 years. Her work has appeared in the Journal of Discrete Algorithms, Journal of Graph Algorithms and Applications, and the Kluwer International Series in Engineering and Computer Science. The proceedings of conferences on Graph Drawing, IEEE Information Visualization, and Algorithm Engineering and Experiments have also included the results of her research. Her interests include graph visualization, analysis, and artificial intelligence.