Please use this identifier to cite or link to this item: doi:10.22028/D291-23714
Title: Access data mining : a new foundation for added-value services in full text repositories
Author(s): Mittelsdorf, Björn
Herb, Ulrich
Language: German
Year of Publication: 2009
OPUS Source: Summary / Breakout Group at the 6th Open Archives Initiative Workshop (OAI 6) ; CERN Workshop on Innovations in Scholarly Communication : Geneva in June 2009. - Geneva, CH, 2009
SWD key words: Open Access
Elektronisches Publizieren
Dokumentenserver
Benutzeroberfläche
Free key words: repository
usage
usage pattern
usage behaviour
metadata extraktion
Repository Features
Visualisation
Easy Submission
Seamless Integration
DDC notations: 020 Library and information sciences
Publikation type: Part of Conference Proceedings
Abstract: This paper describes the results of a breakout group at the 6th Open Archives Initiative Workshop (OAI 6) at Geneva in June 2009, also known as the CERN workshop on Innovations in Scholarly Communication. The breakout group focussed on the following issues: Users have many different needs and interests. Sometimes they are exploring the unknown at other times they would like to revisit some document vaguely remembered. Bibliographies, compilations of highly frequented works, lending records and many other methods were and will be employed to guide researchers towards the publications sought after. In the realm of electronic publications user behaviour can be observed in new ways. For example it is possible to track the browsing path of a visitor, a user's history is no longer confined to objects actually lended. Furthermore metadata describing and identifying the documents is obtainable just as easily. Many people are convinced that the combination of these types of data can yield great results, simplifying library searches, shedding light on the shadows of the deep web, or more generally speaking: Giving the user what he really needs. Two of the most outstanding applications of this paradigm are Amazon Recommendations and Google Search String Recommendations. Both are implemented to some extent in some repository solutions, but there is no doubt, that there are other services of which no one has thought before. The breakout was divided into four sections: 1. Free production (brain storming) of -preferably data based- possible Added-value Services 2. Integration of brainstorming results with ideas gathered in advance by the moderator 3. Estimation of the utility of the elements in the combined set of possibilities 4. Critical evaluation of the possibilities.
Link to this record: urn:nbn:de:bsz:291-scidok-26372
hdl:20.500.11880/23770
http://dx.doi.org/10.22028/D291-23714
Date of registration: 7-Dec-2009
Faculty: ZE - Zentrale Einrichtungen
Department: ZE - Zentrale Verwaltung
Collections:SciDok - Der Wissenschaftsserver der Universität des Saarlandes

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