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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao ACM Transactions on ...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
DBLP
Article . 2019
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On the Lifecycle of the File

Authors: Michael J. May; Etamar Laron; Khalid Zoabi; Havah Gerhardt;

On the Lifecycle of the File

Abstract

Users and Operating Systems (OSs) have vastly different views of files. OSs use files to persist data and structured information. To accomplish this, OSs treat files as named collections of bytes managed in hierarchical file systems. Despite their critical role in computing, little attention is paid to the lifecycle of the file, the evolution of file contents, or the evolution of file metadata. In contrast, users have rich mental models of files: they group files into projects, send data repositories to others, work on documents over time, and stash them aside for future use. Current OSs and Revision Control Systems ignore such mental models, persisting a selective, manually designated history of revisions. Preserving the mental model allows applications to better match how users view their files, making file processing and archiving tools more effective. We propose two mechanisms that OSs can adopt to better preserve the mental model: File Lifecycle Events (FLEs) that record a file’s progression and Complex File Events (CFEs) that combine them into meaningful patterns. We present the Complex File Events Engine (CoFEE), which uses file system monitoring and an extensible rulebase (Drools) to detect FLEs and convert them into complex ones. CFEs are persisted in NoSQL stores for later querying.

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    influence
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
4
Top 10%
Average
Top 10%
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