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

Martin Klein, Harihar Shankar, Lyudmila Balakireva, Herbert Van de Sompel

Research output: Chapter in book/volumeChapterScientificpeer-review

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.
Original languageEnglish
Title of host publicationDigital Libraries for Open Knowledge
Subtitle of host publication23rd International Conference on Theory and Practice of Digital Libraries
Place of PublicationOslo
Pages163-176
Number of pages14
Volume1909.04404
Editionv1
DOIs
Publication statusPublished - 10 Sep 2019

Publication series

NamearXiv
ISSN (Print)2331-8422

Keywords

  • cs.DL

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    Klein, M., Shankar, H., Balakireva, L., & Sompel, H. V. D. (2019). The Memento Tracer Framework: Balancing Quality and Scalability for Web Archiving. In Digital Libraries for Open Knowledge: 23rd International Conference on Theory and Practice of Digital Libraries (v1 ed., Vol. 1909.04404, pp. 163-176). (arXiv).. https://doi.org/10.1007/978-3-030-30760-8_15