Authors:
Miriam Allalouf
1
;
Alex Artyomov
1
and
Dalia Mendelsson
2
Affiliations:
1
Azrieli College of Engineering (JCE), Israel
;
2
The Hebrew University of Jerusalem and, Israel
Keyword(s):
Linked Open Data for Library Catalog Data, Mapping MARC to Ontologies.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Collaboration and e-Services
;
e-Business
;
Enterprise Information Systems
;
Knowledge Engineering and Ontology Development
;
Knowledge-Based Systems
;
Ontology Matching and Alignment
;
Semantic Web
;
Soft Computing
;
Symbolic Systems
Abstract:
Linked Data principles offer significant advantages over current practices when publishing data. Linked Data
allows library interoperability by linking to data from other organizations with authoritative data, which enriches
library catalog-user search results. This paper describes LODLI, a Linked Open Data Back-End system
that we designed and developed to enhance library catalog searches. We integrated our system with the Hebrew
University library catalog, HUfind. While our platform can be used as is, it can also be customized
by Linked Open Data providers that desire to convert their MARC records into Linked Data information library
systems, making their data far more accessible. This research project faced the following challenges:
finding the most efficient way to translate binary MARC into MARC records; mapping the MARC records
into a variety of information models, such as Dublin Core, FRBR, RDA, OWL and FOAF, while selecting
the most appropriate MARC field combinations; and pro
viding links to resources in external datasets using a
distance algorithm to identify string similarity. LODLI is a generic system to which additional ontologies can
easily be added. We have demonstrated the system with two types of clients: FRBR visualization client and
VIAF-extension client.
(More)