Web archives do not capture every resource on every page that they attempt to archive. This results in archived pages missing a portion of their embedded resources. These embedded resources have varying historic, utility, and importance values. The proportion of missing embedded resources does not provide an accurate measure of their impact on the Web page; some embedded resources are more important to the utility of a page than others. We propose a method to measure the relative value of embedded resources and assign a damage rating to archived pages as a way to evaluate archival success. In this paper, we show that Web users' perceptions of damage are not accurately estimated by the proportion of missing embedded resources. The proportion of missing embedded resources is a less accurate estimate of resource damage than a random selection. We propose a damage rating algorithm that provides closer alignment to Web user perception, providing an overall improved agreement with users on memento damage by 17% and an improvement by 51% if the mementos are not similarly damaged. We use our algorithm to measure damage in the Internet Archive, showing that it is getting better at mitigating damage over time (going from 0.16 in 1998 to 0.13 in 2013). However, we show that a greater number of important embedded resources (2.05 per memento on average) are missing over time.

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Web archives do not always capture every resource on every page that they attempt to archive. This results in archived pages missing a portion of their embedded resources. These embedded resources have varying historic, utility, and importance values. The proportion of missing embedded resources does not provide an accurate measure of their impact on the Web page; some embedded resources are more important to the utility of a page than others. We propose a method to measure the relative value of embedded resources and assign a damage rating to archived pages as a way to evaluate archival success. In this paper, we show that Web users' perceptions of damage are not accurately estimated by the proportion of missing embedded resources. In fact, the proportion of missing embedded resources is a less accurate estimate of resource damage than a random selection. We propose a damage rating algorithm that provides closer alignment to Web user perception, providing an overall improved agreement with users on memento damage by 17 % and an improvement by 51 % if the mementos have a damage rating delta >0.30. We use our algorithm to measure damage in the Internet Archive, showing that it is getting better at mitigating damage over time (going from a damage ). However, we show that a greater number of important embedded resources (2.05 per memento on average) are missing over time. Alternatively, the damage in WebCite is increasing over time (going from 0.375 in 2007 to 0.475 in 2014), while the missing embedded resources remain constant (13 % of the resources are missing on average). Finally, we investigate the impact of JavaScript on the damage of the archives, showing that a crawler that can archive JavaScript-dependent representations will reduce memento damage by 13.5 %.

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We describe Mink, a new web browser extension that provides a different model for integration of the live and archived web. While a user browses the live web, Mink actively queries the archives and reports other instances of the page in the archives without requiring active querying by the user. Further, by querying the archives dynamically and asynchronously, a user can view the extent to which the currently viewed page on the live web has been archived and proactively submit a request to various archives using an overlay on the live web page and a simple interface.