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Integration of scholarly communication metadata using knowledge graphs

: Sadeghi, A.; Lange, C.; Vidal, M.-E.; Auer, S.


Kamps, J.:
Research and advanced technology for digital libraries. 21st International Conference on Theory and Practice of Digital Libraries, TPDL 2017 : Thessaloniki, Greece, September 18-21, 2017; Proceedings
Cham: Springer International Publishing, 2017 (Lecture Notes in Computer Science 10450)
ISBN: 978-3-319-67007-2 (Print)
ISBN: 978-3-319-67008-9 (Online)
ISBN: 3-319-67007-7
International Conference on Theory and Practice of Digital Libraries (TPDL) <21, 2017, Thessaloniki>
Conference Paper
Fraunhofer IAIS ()

Important questions about the scientific community, e.g., what authors are the experts in a certain field, or are actively engaged in international collaborations, can be answered using publicly available datasets. However, data required to answer such questions is often scattered over multiple isolated datasets. Recently, the Knowledge Graph (KG) concept has been identified as a means for interweaving heterogeneous datasets and enhancing answer completeness and soundness. We present a pipeline for creating high quality knowledge graphs that comprise data collected from multiple isolated structured datasets. As proof of concept, we illustrate the different steps in the construction of a knowledge graph in the domain of scholarly communication metadata (SCM-KG). Particularly, we demonstrate the benefits of exploiting semantic web technology to reconcile data about authors, papers, and conferences. We conducted an experimental study on an SCM-KG that merges scientific research metadata from the DBLP bibliographic source and the Microsoft Academic Graph. The observed results provide evidence that queries are processed more effectively on top of the SCM-KG than over the isolated datasets, while execution time is not negatively affected.