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Enterprise knowledge graphs: A semantic approach for knowledge management in the next generation of enterprise information systems

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 provide 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.