Anforderungen an ein Daten-Backend-System zur Unterstützung industrieller Datenanalyse-Anwendungen in digitalen Engineering-Prozessen dynamischer Wertschöpfungsnetzwerke
Editor: Dieter Krause; Kristin Paetzold; Sandro Wartzack
Author: Eiden, Andreas; Gries, Jonas; Eickhoff, Thomas; Göbel, Jens C.
Institution: Institute of Virtual Product Engineering; University of Kaiserslautern
Section: Digital Engineering
DOI number: https://doi.org/10.35199/dfx2020.9
Industrial data analytics needs well-structured and linked data from different data sources. The increasing mass of data, scattered IT-structures and a lack of knowledge, especially in small and medium-sized companies (SMEs) are factors that hinder the usage of data analytics. The goal of the research project AKKORD is to build a toolkit for companies to facilitate distributed and integrated industrial data analytics inside value-adding networks. A core part of this toolkit is a data backend system, which collects and links data from different source systems together in a single meta-model. This paper describes the requirements analysis of the data backend system by conducting structured interviews and workshops.