Conference Paper: “The Memento Tracer Framework: Balancing Quality and Scalability for Web Archiving”

The following paper (open access version) was presented today at the TPDL 2019 (23rd International Conference on Theory and Practice of Digital Libraries) taking place this week in Oslo, Norway.

Title

The Memento Tracer Framework: Balancing Quality and Scalability for Web Archiving

Authors

Martin Klein
Los Alamos National Laboratory

Harihar Shankar
Los Alamos National Laboratory

Lyudmila Balakireva
Los Alamos National Laboratory

Herbert Van de Sompel
Data Archiving and Networked Services, The Netherlands

Source

via arXiv

Abstract

Web archiving frameworks are commonly assessed by the quality of their archival records and by their ability to operate at scale. The ubiquity of dynamic web content poses a significant challenge for crawler-based solutions such as the Internet Archive that are optimized for scale. Human driven services such as the Webrecorder tool provide high-quality archival captures but are not optimized to operate at scale. We introduce the Memento Tracer framework that aims to balance archival quality and scalability. We outline its concept and architecture and evaluate its archival quality and operation at scale. Our findings indicate quality is on par or better compared against established archiving frameworks and operation at scale comes with a manageable overhead.

Direct to Full Text Paper
14 pages; PDF.

Filed under: Data Files, Journal Articles, Libraries, News, Open Access