Linked Open Citation Database : enabling libraries to contribute to an open and interconnected citation graph

Lauscher, Anne ; Eckert, Kai ; Galke, Lukas ; Scherp, Ansgar ; Rizvi, Syed Tahseen Raza ; Ahmed, Sheraz ; Dengel, Andreas ; Zumstein, Philipp ; Klein, Annette

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DOI:	https://doi.org/10.1145/3197026.3197050
URL:	https://madoc.bib.uni-mannheim.de/44470
Weitere URL:	https://dl.acm.org/citation.cfm?doid=3197026.31970...
URN:	urn:nbn:de:bsz:180-madoc-444700
Dokumenttyp:	Konferenzveröffentlichung
Erscheinungsjahr:	2018
Buchtitel:	Joint Conference on Digital Libraries 2018 : June 3-6, 2018 in Fort Worth, Texas : Proceedings of the ACM/IEEE Joint Conference on Digital Libraries (JCDL)
Seitenbereich:	109-118
Veranstaltungstitel:	JCDL 2018
Veranstaltungsort:	Fort Worth, TX
Veranstaltungsdatum:	June 3--7, 2018
Herausgeber:	Chen, Jiangping
Ort der Veröffentlichung:	New York, NY
Verlag:	ACM Press
ISBN:	978-1-4503-5178-2
Sprache der Veröffentlichung:	Englisch
Einrichtung:	Zentrale Einrichtungen > UB Universitätsbibliothek Fakultät für Wirtschaftsinformatik und Wirtschaftsmathematik > Information Systems III: Enterprise Data Analysis (Ponzetto 2016-)
Fachgebiet:	020 Bibliotheks- und Informationswissenschaft
Freie Schlagwörter (Englisch):	citation data ; library workflows ; linked open data ; editorial system ; automatic reference extraction
Abstract:	Citations play a crucial role in the scientific discourse, in information retrieval, and in bibliometrics. Many initiatives are currently promoting the idea of having free and open citation data. Creation of citation data, however, is not part of the cataloging workflow in libraries nowadays. In this paper, we present our project Linked Open Citation Database, in which we design distributed processes and a system infrastructure based on linked data technology. The goal is to show that efficiently cataloging citations in libraries using a semi-automatic approach is possible. We specifically describe the current state of the workflow and its implementation. We show that we could significantly improve the automatic reference extraction that is crucial for the subsequent data curation. We further give insights on the curation and linking process and provide evaluation results that not only direct the further development of the project, but also allow us to discuss its overall feasibility.