Visualization and Immersion of Life Sciences Data

Seeing is Believing is a very interesting article in The Scientist about information visualization. It tackles the fact that lift scientists have to deal with a huge amount of information. The challenge would be to develop relevant visual techniques.

Computers do a great job of finding patterns in data when they're programmed to look for them, notes Jim Thomas, who heads the National Visualization and Analytics Center at Pacific Northwest National Laboratory (PNNL) in Richland, Wash., "but many times, you are discovering what questions to ask. Only the human mind has the ability to reason with what is seen, apply other human knowledge, and develop a hypothesis or question." High-end visualization tools have been long used in applications such as the study of jet turbulence and by security experts looking for "chatter" in reams of telephone calls and transmissions, but only now are such tools being used in the life sciences, says H. Steven Wiley, director of the Biomolecular Systems Initiative at PNNL.

What is also intriguing is this sentence: "Without them, more data won't necessarily translate into better science", a nice evocation of Latour's inscription theory.

For that matter, it seems that VR is still around:

A next generation of visualization software may strive not just to offer a view, but allow the viewer to enter the data. This total immersion concept is the idea behind Delaware Biotechnology Institute's "cave," a Visualization Studio that Silicon Graphics developed, which allows users to literally immerse themselves in the data, both visually and physically. (...) One of the great benefits of the immersive system, Steiner says, is that scientists can "walk around" the data and peer at it from every angle, and do so collaboratively, either remotely or from the same room. And that, Steiner adds, is the great benefit of visualization in general: It can foster interdisciplinary collaboration by helping scientists from a variety of backgrounds understand a problem in order to solve it in a more effective manner.

(image taken from the Delaware Biotechnology Institute)

Why do I blog this? it's interesting to see that VR is still relevant in data manipulation.