With web archives, journalists ﬁnd evidence and information to back up their stories, historians store information for later users, and social scientists can study the actions of humans during speciﬁc time periods. These diﬀerent groups gain value not only from creating their own collections but from using the collections of others. Web archive collections store the content that would otherwise be lost. As users, we currently have no eﬃcient way of understanding what is in each collection without manually reviewing all of its items. Web archives intentionally consist of diﬀerent versions of the same document. With these multiple versions, we can watch the evolution of a single resource over time, following the changes to an organization or how the public learns the details of an unfolding news story. As aggregations of archived web pages, or mementos, these collections become resources unto themselves. While past work has used mementos for studying how web resources change over time or evaluated the changes to various industries, there is still theoretical work to be done in improving the usability of web archive collections. Our goal is to help collection creators and the public at large to make better use of these collections through improvements to collection understanding. We build upon the work of AlNoamany by using visualizations from social media storytelling. Our goal is to produce a story for each web archive collection. Each story consists of representative mementos selected from the web archive collection that are then individually visualized as surrogates (e.g., screenshots, cards containing a summary of the page). This solution has the beneﬁt of using visualization paradigms familiar to users. In this work, we provide background on the problem, analyze previous work in this area, and highlight our preliminary work before providing a plan for future research.