Reinventing Discovery_ The New Era of Networked Science - Michael Nielsen [2]
This human genetic map was the combined work of many, many biologists around the world. Each time they obtained a new chunk of genetic data in their laboratories, they uploaded that data to centralized online services such as GenBank, the amazing online repositoryf genetic information run by the US National Center for Biotechnology Information. GenBank integrates all this genetic information into a single, publicly accessible online database, a compilation of the work of thousands of biologists. It’s information on a scale that’s almost impossible to analyze by hand. Fortunately, anyone in the world may freely download the genetic map, and then use computer algorithms to analyze the map, perhaps discovering previously unsuspected facts about the human genome. You can, if you like, go to the GenBank site right now, and start browsing genetic information. (For links to GenBank and other resources, see the “Notes on Sources,” starting on page 347.) This is, in fact, what makes those studies linking genes to disease possible: the scientists doing the studies start by finding a large group of people with the disease, and also a control group of people without the disease. They then use the human genetic map to find correlations between disease incidence and the genetic differences of the two groups.
A similar pattern of discovery is being used across science. Scientists in many fields are collaborating online to create enormous databases that map out the structure of the universe, the world’s climate, the world’s oceans, human languages, and even all the species of life. By integrating the work of hundreds or thousands of scientists, we are collectively mapping out the entire world. With these integrated maps anyone can use computer algorithms to discover connections that were never before suspected. Later in the book we’ll see examples ranging from new ways of tracking influenza outbreaks to the discovery of orbiting pairs of supermassive black holes. We are, piece by piece, assembling all the world’s knowledge into a single giant edifice. That edifice is too vast to be comprehended by any individual working alone. But new computerized tools can help us find meaning hidden in all that knowledge.
If the Polymath Project illustrates a shift in how scientists collaborate to create knowledge, and GenBank and the genetic studies illustrate a shift in how scientists find meaning in knowledge, a third big shift is a change in the relationship between science and society. An example of this shift is the website Galaxy Zoo, which has recruited more than 200,000 online volunteers to help astronomers classify galaxy images. Those volunteers are shown photographs of galaxies, and asked to answer questions such as “Is this a spiral or an elliptical galaxy?” and “If this is a spiral, do the arms rotate clockwise or anticlockwise?” These are photographs that have been taken automatically by a robotic telescope, and have never before been seen by any human eye. You can think of Galaxy Zoo as a cosmological census, the largest ever undertaken, a census that has so far produced more than 150 million galaxy classifications.
The volunteer astronomers who participate in Galaxy Zoo are making astonishing discoveries. They have, for example, recently discovered an entirely new class of galaxy, the “green pea galaxies”—so named because the galaxies do, indeed, look like small green peas—where stars are forming faster than almost anywhere else in the universe. They’ve also discovered what is believed to be