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**Commentary:** Astronomy began as a visual science. Then, it diversified. New wavelengths, new physics, new computers, new statistics, new math. As we got better at manipulating data and equations with computers, some scientists stopped appreciating, for a while, how good we are, as humans, at pattern recognition. Our cognitive systems have _evolved_ over millennia to become better and better at recognizing shapes, colors, and change, faster, and faster. Two groups of people know that humans are still better at finding patterns in images than computers--small children who would never think a computer smarter than they are, and visualizaiton researchers who know that no algorithm can yet beat a human. How good are you at recognizing faces in photos? I'm willing to bet that you are at 100% using clear photos of people you know. No computer is at 100%.  Given that people are still better than computers at creative and inferential tasks when presented with visual information, the question becomes how to present the most useful "visual information." Domain scientists typically call that visusal the presentation of visual  information "data visualization," and computer scientists and visualization researchersoften  call it either  "information visualization" or "scientific visualizaiton." Why the different names? Many visualization researchers make a distinction between literal representation of data ("scientific visualization", like a 3D image of a heart) and abstract representation of data ("information visualization", like an EKG).In the talk I am delivering at the American Astrononimcal Society Meeting today,  Iwill  argue that this distinction can hold science back, and that the most progress is made when various kinds of visualization are used _together_, in ways that effectively "link" views of data. For example, a linked view showing a manipulateable 3D image of a beating heart alongside an EKG is a much better way to "look" for sources of heartbeat irregularities than is either a 3D image or an EKG alone.