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Podcast: Memento - Protocol-Based Time Travel for the Web

Frustrated attempts to retrieve old versions of Web pages abound. Web site visitors frequently bookmark pages only to find later, upon revisiting the site, that the current content is not even remotely related to what caught their initial interest. Remnants of the past Web are available, and there are many efforts ongoing to archive even more Web content, but the past Web is not as readily accessible as today's. For example, someone wanting to see an archived version of can go to the Internet Archive's Wayback Machine and search for it there. Or old versions of a Wikipedia page are available by going to the current page and from there following a link to one of the prior versions.

But accessing archived Web content feels more like walking to a library than using the Web in the usual way. It would be much easier to simply connect to a Web site indicating an interest in the pages of March 20, 2008, for example, instead of the current pages, by activating a time machine in your own browser or bot. The Memento solution has been designed to achieve this solution. It is based on existing HTTP capabilities applied in a novel way to add the temporal dimension. The result is a framework in which archived resources can seamlessly be reached via the uniform resource identifier (URI) of their original: protocol-based time travel for the Web.

Joining us for this podcast are Memento's creators:

  • Herbert Van de Sompel, Digital Library Researcher, Los Alamos National Laboratory
  • Robert Sanderson, Scientist, Los Alamos National Laboratory
  • Michael Nelson, Assistant Professor, Department of Computer Science, Old Dominion University


This interview is provided courtesy of CNI and was recorded at their 2009 Fall Task Force Meeting.  The Coalition for Networked Information (CNI) is an organization dedicated to supporting the transformative promise of networked information technology for the advancement of scholarly communication and the enrichment of intellectual productivity.  You can learn more about CNI at their web site,


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Running time: 10m 49s
File size: 7.43 MB

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