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Susanne Reffert | IPMU | Japan

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Are You an Infovore?

The Urban Dictionary defines an infovore as “A person that has a voracious appetite for information”. This term is pretty popular on the blogosphere these days.
The people who actually coined the term are neuroscientists: Irving Biederman of the University of Southern California in University Park and Edward Vessel of New York University. Their findings show that humans are natural infovores. When the human brain processes information, endorphins are released, giving us a feeling of pleasure.
It is probably not wrong to assume that people who are drawn to a carrier in science have a particularly strong predilection for processing and interpreting information.
Even though I am a theorist, I am fascinated by data, and I love how much data is freely available to the public via the internet. Be it astronomical data via the Sloane Digital Sky Survey which will have a dataset of 230 million celestial objects, or from the Hubble Space Telescope, to mention just two scientific data sources.

I would definitely classify myself as an infovore, and I have a confession to make: I am addicted to the weather forecast. I check the satellite image and the rain radar echos several times a day. I am just thrilled to have access to up to date satellite and radar data. It might sound silly, but when you think about it, it’s actually pretty cool and wouldn’t have been possible 20 years ago. We’re living in a time in which huge amounts of data are being compiled (the LHC alone produces about 1.3GB per second!), a huge wealth for all flavors of science. The challenge is to find ways of effectively extracting useful information from it.

Check out a very cool instance of automated processing of astronomical images which is accessible to everyone: Any picture of the night sky submitted to the pool of the astrometry group on Flickr is run through an engine, which posts a comment to the picture with the astronomical data of the depicted objects, and adds notes directly on the image which identify the visible objects. I think that’s pretty neat!

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