The Fascinator: a lightweight, modular contribution to the Fedora-commons world

Sefton, Peter and Lucido, Oliver (2009) The Fascinator: a lightweight, modular contribution to the Fedora-commons world. In: Open Repositories 2009, 18-21 May 2009, Atlanta Georgia, USA.

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The ARROW project sponsored a hybrid commercial/open-source approach to building vendor-supported repository infrastructure with open-source underpinnings. The Fascinator was conceived initially as a way to prove a point in an ongoing dialogue within the ARROW project about repository architecture. The goal was to test the hypothesis that it would be possible to build a useful, fast, flexible web front end for a repository using a single fast indexing system to handle browsing via facets, full-text search, multiple 'portal' views of subsets of a large corpus, and most importantly, easy-to administer security that could handle the most common uses cases seen in the ARROW community. This contrasted with the approach taken by ARROW's commercial partner, which used several different indices to achieve only some of the same functionality in an environment which was much more complex to manage and configure. The Fascinator has also been used experimentally to index research data on desktop computers, with a view to allowing academics to classify their data and have it routed to downstream repositories via protocols such as ATOM and OAI-PMH.

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Item Type: Conference or Workshop Item (Commonwealth Reporting Category E) (Paper)
Refereed: No
Item Status: Live Archive
Additional Information: Author retains copyright.
Faculty/School / Institute/Centre: Current - USQ Other
Faculty/School / Institute/Centre: Current - USQ Other
Date Deposited: 22 May 2009 04:58
Last Modified: 23 Sep 2011 03:22
Uncontrolled Keywords: ARROW; Fascinator; Fedora Commons; Apache Solr; repositories
Fields of Research (2008): 08 Information and Computing Sciences > 0806 Information Systems > 080612 Interorganisational Information Systems and Web Services
Fields of Research (2020): 46 INFORMATION AND COMPUTING SCIENCES > 4605 Data management and data science > 460507 Information extraction and fusion

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