Search

The metadata search is an important way to access and manage file systems. Many solutions have been proposed to tackle performance issue of metadata search. However, the existing solutions build a separate metadata index at the internal or external file system through the related data structure or database use semantics and event-notification method to construct the index structure, utilize the sampling-based method to conduct direct metadata search on the namespace, face problems of the high I/O overhead for maintaining consistency between metadata indexes and metadata, have enormous space overhead for metadata indexes storing and low accuracy of results and so on. To address these problems, this paper presents MBFS, a fast, accurate and lightweight metadata search method based on multi-dimensional Bloomfilters. We create a multi-dimensional Bloomfilter structure on the basis of the directory entry that can prune sub-trees to narrow the search scope of namespace. MBFS is capable of producing fast and accurate answers for a class of complex search over a file system after consuming a small number of disk accesses. MBFS residing in the file system does not need additional I/O overhead to maintain consistency. MBFS consists of Bloomfilters which are composed of bits, so it is a lightweight metadata search method that consumes marginal space overhead. Moreover, MBFS employs MapReduce for speeding up search under the environment of multiple metadata servers. Extensive experiments are conducted to prove the effectiveness of MBFS. The experimental results show that MBFS can achieve an excellent performance not only on the search latency, but also on the accuracy of results with low space and time overhead. [ABSTRACT FROM AUTHOR]

The paper focuses its attention on the legal and practical possibilities when utilizing public licenses as a tool in making metadata available to the wider public in a form that is as open as possible, as well as on the obstacles that need to be overcome in doing so, in particular with regard to the rights of third parties. The paper will draw on the experience gained from publishing the database of NRGL metadata and will present generally applicable conclusions based on this. [ABSTRACT FROM AUTHOR]

ABSTRACT: This study analyzes more than 400 SFX broken-link reports sent by users of an academic library. It raises technical issues regarding OpenURL linking in the handling of special journal volume and issue numbers, journal supplemental issues, embargo release dates, book reviews, DOIs, and other areas. It reports on full-text resources with the most broken links, causes of broken links, and the library''s responses to users. It also explores how journal publishers, database vendors, and OpenURL vendors can improve the quality of their products and how librarians can better serve users. [Copyright &y& Elsevier]

In recent years, link resolver technology has become integral to ensuring successful institutional access to electronic content. The corresponding take-up of OpenURL compliance amongst content providers in response has resulted in a global solution to the 'appropriate copy' problem. However, this solution is only effective if the knowledge base behind the link resolver is up to date, accurate and comprehensive and this is a factor that is often overlooked in establishing OpenURL compliance. This article explores the importance of OpenURL and knowledge bases to the information community as a whole and provides an overview and update of the role that the KBART (Knowledge Bases and Related Tools) project has to play in improving knowledge base metadata. [ABSTRACT FROM AUTHOR]

LibX (http://libx.org/) is an open source Firefox extension that provides direct access to library resources in multiple ways: through a toolbar, a context menu, and via cues that LibX places into web sites a user visits. A LibX edition integrates support for the resources to which a particular user community has access, including the library OPAC, databases, and their OpenURL link resolver. As one of its features, LibX supports the fast (one-click) retrieval of known items. such as research articles. This frequent task is automated by exploiting Google's Scholar service as a hidden backend that is used for searches. In this paper, we evaluate the effectiveness of LibX in retrieving known items that were listed as references in a sample of articles in four widely read journals. We conclude that LibX's matching algorithm can lead the user to an accessible copy of an item on average in 81% of cases with a negligible number of irrelevant items retrieved. As a result, LibX can dramatically reduce the time spent on known item searches [ABSTRACT FROM AUTHOR]