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Data Networking for Industrial Data Analysis Based on a Data Backbone System

Published online by Cambridge University Press:  26 May 2022

A. Eiden ,
T. Eickhoff ,
J. C. Göbel ,
C. Apostolov ,
P. Savarino  and
T. Dickopf
A. Eiden*
Affiliation:
Technische Universität Kaiserslautern, Germany
T. Eickhoff
Affiliation:
Technische Universität Kaiserslautern, Germany
J. C. Göbel
Affiliation:
Technische Universität Kaiserslautern, Germany
C. Apostolov
Affiliation:
CONTACT Software GmbH, Germany
P. Savarino
Affiliation:
CONTACT Software GmbH, Germany
T. Dickopf
Affiliation:
CONTACT Software GmbH, Germany
*
eiden@mv.uni-kl.de

Abstract

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Industrial Data Analytics needs access to huge amounts of data, which is scattered across different IT systems. As part of an integrated reference kit for Industrial Data Analytics, there is a need for a data backend system that provides access to data. This system needs to have solutions for the extraction of data, the management of data and an analysis pipeline for those data. This paper presents an approach for this data backend system.

Keywords

data miningbig data analysisproduct lifecycle management (PLM)data aggregationdata integration
Type
Article
Information
Proceedings of the Design Society , Volume 2: DESIGN2022 , May 2022 , pp. 693 - 702
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
The Author(s), 2022.

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