Elastic Stack and GRAPHYP Knowledge Graph of Web Usage: A Win–Win Workflow for Semantic Interoperability in Decision Making
Otmane Azeroual (),
Renaud Fabre,
Uta Störl and
Ruidong Qi
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Otmane Azeroual: German Centre for Higher Education Research and Science Studies (DZHW), 10117 Berlin, Germany
Renaud Fabre: Dionysian Economics Lab (LED), University Paris 8, 93200 Saint-Denis, France
Uta Störl: Chair of Databases and Information Systems, University of Hagen, 58097 Hagen, Germany
Ruidong Qi: College of Computer Science, Inner Mongolia University, Hohhot 010031, China
Future Internet, 2023, vol. 15, issue 6, 1-19
Abstract:
The use of Elastic Stack (ELK) solutions and Knowledge Graphs (KGs) has attracted a lot of attention lately, with promises of vastly improving business performance based on new business insights and better decisions. This allows organizations not only to reap the ultimate benefits of data governance but also to consider the widest possible range of relevant information when deciding their next steps. In this paper, we examine how data management and data visualization are used in organizations that use ELK solutions to collect integrated data from different sources in one place and visualize and analyze them in near-real time. We also present some interpretable Knowledge Graphs, GRAPHYP, which are innovative by processing an analytical information geometry and can be used together with an ELK to improve data quality and visualize the data to make informed decisions in organizations. Good decisions are the backbone of successful organizations. Ultimately, this research is about integrating a combined solution between ELK and SKG GRAPHYP and showing users the advantages in this area.
Keywords: data management; databases and information systems; IoT; knowledge graph (KG); scientific knowledge graph (SKG); GRAPHYP; elastic stack (ELK); visualization; data quality (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2023
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