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Discovering Links for Metadata Enrichment on Computer Science Papers
[working paper]
Corporate Editor
GESIS - Leibniz-Institut für Sozialwissenschaften
Abstract At the very beginning of compiling a bibliography, usually only basic information, such as title,
authors and publication date of an item are known. In order to gather additional information about a specific item, one typically has to search the library catalog or use a web search engine.
This loo... view more
At the very beginning of compiling a bibliography, usually only basic information, such as title,
authors and publication date of an item are known. In order to gather additional information about a specific item, one typically has to search the library catalog or use a web search engine.
This look-up procedure implies a manual effort for every single item of a bibliography. In this
technical report we present a proof of concept which utilizes Linked Data technology for the
simple enrichment of sparse metadata sets. This is done by discovering owl:sameAs links between
an initial set of computer science papers and resources from external data sources like DBLP, ACM and the Semantic Web Conference Corpus. In this report, we demonstrate how the link discovery tool Silk is used to detect additional information and to enrich an initial set of records in the computer science domain. The pros and cons of silk as link discovery tool are summarized in the end.... view less
Keywords
bibliography; automation; computer science; software; information science; new technology
Classification
Information and Documentation, Libraries, Archives
Natural Science and Engineering, Applied Sciences
Free Keywords
bibliographische Daten; Linked Data
Document language
English
Publication Year
2012
City
Mannheim
Page/Pages
22 p.
Series
GESIS-Technical Reports, 2012/10
Status
Published Version; reviewed
Licence
Deposit Licence - No Redistribution, No Modifications