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Conference proceeding
Framework for Aggregating Private and Public Web Archives
JCDL'18: PROCEEDINGS OF THE 18TH ACM/IEEE JOINT CONFERENCE ON DIGITAL LIBRARIES, pp 273-282
01 Jan 2018
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Personal and private Web archives are proliferating due to the increase in the tools to create them and the realization that Internet Archive and other public Web archives are unable to capture personalized (e.g., Facebook) and private (e.g., banking) Web pages. We introduce a framework to mitigate issues of aggregation in private, personal, and public Web archives without compromising potential sensitive information contained in private captures. We amend Memento syntax and semantics to allow TimeMap enrichment to account for additional attributes to be expressed inclusive of the requirements for dereferencing private Web archive captures. We provide a method to involve the user further in the negotiation of archival captures in dimensions beyond time. We introduce a model for archival querying precedence and short-circuiting, as needed when aggregating private and personal Web archive captures with those from public Web archives through Memento. Negotiation of this sort is novel to Web archiving and allows for the more seamless aggregation of various types of Web archives to convey a more accurate picture of the past Web.
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Details
- Title
- Framework for Aggregating Private and Public Web Archives
- Creators
- Mat Kelly - Old Dominion UniversityMichael L. Nelson - Old Dominion UniversityMichele C. Weigle - Old Dominion UniversityAssoc Comp Machinery
- Publication Details
- JCDL'18: PROCEEDINGS OF THE 18TH ACM/IEEE JOINT CONFERENCE ON DIGITAL LIBRARIES, pp 273-282
- Series
- ACM-IEEE Joint Conference on Digital Libraries JCDL
- Publisher
- Assoc Computing Machinery
- Number of pages
- 10
- Grant note
- HK-50181-14 / NEH; National Endowment for the Humanities (NEH) RE-33-16-0107-16 / IMLS
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Information Science
- Web of Science ID
- WOS:000458178700038
- Scopus ID
- 2-s2.0-85048899827
- Other Identifier
- 991021786445504721
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InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Computer Science, Information Systems
- Computer Science, Interdisciplinary Applications
- Information Science & Library Science