loading
Documents

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Mikhail Galkin 1 ; Sören Auer 2 ; Maria-Esther Vidal 3 and Simon Scerri 2

Affiliations: 1 University of Bonn & Fraunhofer IAIS and ITMO University, Germany ; 2 University of Bonn & Fraunhofer IAIS, Germany ; 3 University of Bonn & Fraunhofer IAIS and Universidad Simón Bolívar, Germany

ISBN: 978-989-758-248-6

ISSN: 2184-4992

Keyword(s): Enterprise Information Systems, Linked Enterprise Data, Enterprise Knowledge Graphs, Semantic Web Technologies.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Biomedical Engineering ; Coupling and Integrating Heterogeneous Data Sources ; Data Engineering ; Databases and Information Systems Integration ; Enterprise Information Systems ; Health Information Systems ; Information Systems Analysis and Specification ; Knowledge Engineering and Ontology Development ; Knowledge Management ; Knowledge-Based Systems ; Ontologies and the Semantic Web ; Ontology Engineering ; Society, e-Business and e-Government ; Symbolic Systems ; Web Information Systems and Technologies

Abstract: In enterprises, Semantic Web technologies have recently received increasing attention from both the research and industrial side. The concept of Linked Enterprise Data (LED) describes a framework to incorporate benefits of Semantic Web technologies into enterprise IT environments. However, LED still remains an abstract idea lacking a point of origin, i.e., station zero from which it comes to existence. We devise Enterprise Knowledge Graphs (EKGs) as a formal model to represent and manage corporate information at a semantic level. EKGs are presented and formally defined, as well as positioned in Enterprise Information Systems (EISs) architectures. Furthermore, according to the main features of EKGs, existing EISs are analyzed and compared using a new unified assessment framework. We conduct an evaluation study, where cluster analysis allows for identifying and visualizing groups of EISs that share the same EKG features. More importantly, we put our observed results in perspective and p rovide evidences that existing approaches do not implement all the EKG features, being therefore, a challenge the development of these features in the next generation of EISs. (More)

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 18.207.108.182

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Galkin, M.; Auer, S.; Vidal, M. and Scerri, S. (2017). Enterprise Knowledge Graphs: A Semantic Approach for Knowledge Management in the Next Generation of Enterprise Information Systems.In Proceedings of the 19th International Conference on Enterprise Information Systems - Volume 2: ICEIS, ISBN 978-989-758-248-6, ISSN 2184-4992, pages 88-98. DOI: 10.5220/0006325200880098

@conference{iceis17,
author={Mikhail Galkin. and Sören Auer. and Maria{-}Esther Vidal. and Simon Scerri.},
title={Enterprise Knowledge Graphs: A Semantic Approach for Knowledge Management in the Next Generation of Enterprise Information Systems},
booktitle={Proceedings of the 19th International Conference on Enterprise Information Systems - Volume 2: ICEIS,},
year={2017},
pages={88-98},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006325200880098},
isbn={978-989-758-248-6},
}

TY - CONF

JO - Proceedings of the 19th International Conference on Enterprise Information Systems - Volume 2: ICEIS,
TI - Enterprise Knowledge Graphs: A Semantic Approach for Knowledge Management in the Next Generation of Enterprise Information Systems
SN - 978-989-758-248-6
AU - Galkin, M.
AU - Auer, S.
AU - Vidal, M.
AU - Scerri, S.
PY - 2017
SP - 88
EP - 98
DO - 10.5220/0006325200880098

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.