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Introducing the Academic Reader

by Michael Nielsen on April 10, 2007

The Academic Reader is a new web site that makes it easier to keep track of your scientific reading. Rather than going to multiple websites every day to keep up, we pull all the sources together in a single location, so you can keep track easily. Sources include the preprint arXiv, the Physical Review, and Nature, and many new sources will be added in the months to come, including sources outside physics.

Visit version 0.01 of the site at http://www.academicreader.org.

Update: Last week the preprint ArXiv overhauled its paper numbering. A side effect, which became visible just as we announced (!), is that their back-end interface for extracting paper data is currently completely down. They promise it’ll be back soon. In the meantime, the ArXiv feeds on the Academic Reader will be bit dated. Our apologies for that.

Update 2: The ArXiv appears to be back to normal.

Update 3: We had some server downtime for about 15 mins (around 0700 UTC) due to a hastily scheduled memory upgrade needed to speed things up (thanks everyone for registering!) Sorry if you got booted off the server – we’ll try to make this more transparent in future.

From → General

2 Comments
  1. sean permalink

    I think this is a gret idea! I think the main value from this sort of thing is some kind of “recommendation system” by which I’m lead to papers that I otherwise wouldn’t have seen, based on the sort of papers I already read (similar to what Amazon and itunes do… “Other customers also bought…”). As such it would be nice if this was based not just on papers that I have actively placed in my library – presumably you could also collect other levels of data, such as whether I have looked at the abstract, or whether I have actually downloaded a pdf. It would also be nice to access this information for other particular users (presuming that they consent to this of course). If enough people start using this system as their primary means of accessing papers you could build up a lot of useful data this way.

  2. Thanks, Sean! We’ve actually written the code for a recommendation system, but it still has a fair bit of testing and refinement to go through before we deploy it.

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