Hypercane is a utility for intelligently sampling mementos from web archive collections. It is the first step toward automatically summarizing a web archive collection.
Individual web archive collections can contain thousands of documents. If a researcher wants to use one of these collections, which one best meets their information need? How does the researcher differentiate them? deally, a user would be able to glance at a visualization and gain understanding of the collection, but existing visualizations require a lot of cognitive load and training even to convey one aspect of a collection. Social media storytelling provides us with an approach. We want to use this proven technique because readers already understand how to view these visualizations. The Dark and Stormy Archives (DSA) Project explores how to summarize web archive collections through these visualizations. We make our DSA Toolkit freely available to others so they can explore web archive collections through storytelling.
Links to web resources frequently break, and linked content can change at unpredictable rates. These dynamics of the Web are detrimental when references to web resources provide evidence or supporting information. In this paper, we highlight the significance of reference rot, provide an overview of existing techniques and their characteristics to address it, and introduce our Robust Links approach, including its web service and underlying API. Robustifying links offers a proactive, uniform, and machine-actionable way to combat reference rot. In addition, we discuss our reasoning and approach aimed at keeping the approach functional for the long term. To showcase our approach, we have robustified all links in this article.
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. As users, we currently have no eﬃcient way of understanding what is in each collection without manually reviewing all of its items. 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. 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.
Raintale is the latest entry in the Dark and Stormy Archives project. Our goal is to provide research studies and tools for combining web archives and social media storytelling. Raintale provides the storytelling capability. It has been designed to visualize a small number of mementos selected from an immense web archive collection, allowing a user to summarize and visualize the whole collection or a specific aspect of it.
We examine different collections at the web archive collection service Archive-It. From here we demonstrate the use of several different structural features that can be used to predict the type of collection.
I have worked in industry for more than 18 years, participating in many aspects of systems and software engineering.
Now I am a Graduate Research Assistant at Los Alamos National Laboratory working for the Research Library Prototyping Team. I am also a Ph.D. candidate at Old Dominion University majoring in Computer Science under the guidance of Dr. Michael L. Nelson. My focus area is digital preservation, specifically web archiving.
Above, you can find out more information about my journey through academia.
Below, you can follow me on social networking.