Choosing the right way to visualize your data makes the difference between telling a clear, compelling story or creating cognitive overload. Here's how to pick. Data is best understood when presented ...

Data visualization is a process in data analytics where visual representation communicates the data and insights to facilitate good data-driven decisions. Basically, data visualization is ...

Data visualization — and its close cousin, visual information design — is an often underrated skill; however, it plays a critical role in communicating information to an audience. More than just ...

The field of network visualization and graph analysis has emerged as a crucial interdisciplinary area, merging advanced computational algorithms with sophisticated visual representation techniques.

Pictured is an example multi-modal representation of stock data created with Umwelt. It includes a line chart, a sonification (top right), and a multi-level textual description describing various ...

Machine learning, task automation and robotics are already widely used in business. These and other AI technologies are about to multiply, and we look at how organizations can best take advantage of ...

Neo4j Inc. today announced a new serverless offering that dramatically simplifies the deployment of its graph database offering, making it easier to use with artificial intelligence applications. Most ...

The MPS Data Visualization & Communication (DV&C) program equips you with the tools to translate complex information into powerful stories that grab attention and move people to action. With a ...

Benjamin Franklin once said, “Believe none of what you hear and half of what you see.” Could Franklin, a founding father of the United States and considered a genius by many, have predicted that art ...

Through rigorous, data-based analysis, researchers and analysts can add to our understanding of societal shortcomings and point toward evidence-based solutions. But carelessly collecting and ...

Data visualizations can significantly affect how people understand and interpret data. But data visualizations can be biased and exclusionary, perpetuating inequity and harmful stereotypes.