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Integration strategies for enterprise knowledge graphs

: Galkin, M.; Auer, S.; Kim, H.; Scerri, S.


Newman, D. ; Institute of Electrical and Electronics Engineers -IEEE-; IEEE Computer Society:
IEEE Tenth International Conference on Semantic Computing, ICSC 2016. Proceedings : 3-5 February 2016, Laguna Hills, California
Los Alamitos, Calif.: IEEE Computer Society Conference Publishing Services (CPS), 2016
ISBN: 978-1-5090-0662-5 (Online)
ISBN: 978-1-5090-0661-8 (USB)
International Conference on Semantic Computing (ICSC) <10, 2016, Laguna Hills/Calif.>
Conference Paper
Fraunhofer IAIS ()

Semantic computing and enterprise Linked Data have recently gained traction in enterprises. Although the concept of Enterprise Knowledge Graphs (EKGs) has meanwhile received some attention, a formal conceptual framework for designing such graphs has not yet been developed. By EKG we refer to a semantic network of concepts, properties, individuals and links representing and referencing foundational and domain knowledge relevant for an enterprise. Through the efforts reported in this paper, we aim to bridge the gap between the increasing need for EKGs and the lack of formal methods for realising them. We present a thorough study of the key concepts of knowledge graphs design along with an analysis of the advantages and disadvantages of various design decisions. In particular, we distinguish between two polar approaches towards data fusion, i.e., the unified and the federated approach, describe their benefits and point out shortages.