Submission + - Science Commons: Freeing and Forgetting Data (oreilly.com)
He also points of that as the volume of data grows from new projects like the LHC and the new high-resolution cameras that may generate petabytes a day, we'll need to get better at determining what data to keep and what to throw away. "We have to figure out how to deal with preservation and federation because our libraries have been able to hold books for hundreds and hundreds and hundreds of years. But persistence on the web is trivial. Right? The assumption is well, if it's meaningful, it'll be in the Google cache or the internet archives. But from a memory perspective, what do we need to keep in science? What matters? Is it the raw data? Is it the processed data? Is it the software used to process the data? Is it the normalized data? Is it the software used to normalize the data? Is it the interpretation of the normalized data? Is it the software we use to interpret the normalization of the data? Is it the operating systems on which all of those ran? What about genome data?""