Abstract
Providing data for data analysis projects is one core task of automation technology, however, it still has to be done with a lot of manual effort. One challenge is to keep the meaning of data remain interpretable within or across multiple software environments so that provider and user of data share a common understanding of the transferred data. It is acknowledged that machine interpretable metadata is one crucial building block for reaching this goal. However, in industrial automation and information systems today, exporting and utilizing data coupled with metadata is still not a common practice. Therefore, we propose a general concept for extracting metadata and utilizing it in data analytics applications, which may help with system design in the future. The concept is prototypically implemented regarding the structural metadata for tabular data.
Zusammenfassung
Die Bereitstellung von Daten für Datenanalyseprojekte ist eine Kernaufgabe der Automatisierungstechnik, die jedoch immer noch mit viel manuellem Aufwand verbunden ist. Eine Herausforderung besteht darin, die Bedeutung der Daten innerhalb oder über mehrere Softwareumgebungen hinweg interpretierbar zu halten, so dass Anbieter und Nutzer von Daten ein gemeinsames Verständnis der übertragenen Daten haben. Es ist anerkannt, dass maschineninterpretierbare Metadaten ein entscheidender Baustein zur Erreichung dieses Ziels sind. In industriellen Automatisierungs-und Informationssystemen sind der Export und die Nutzung von Daten, die mit Metadaten gekoppelt sind, heute jedoch noch nicht üblich. Daher schlagen wir ein allgemeines Konzept zur Extraktion von Metadaten und deren Nutzung in Datenanalyse-Applikationen vor, das in Zukunft bei der Systemgestaltung helfen kann. Das Konzept wird prototypisch für strukturelle Metadaten für tabellarische Daten umgesetzt.
About the authors
Wan Li, M. Sc. RWTH (born 1990) is a research associate at the Chair of Information and Automation Systems for Process and Material Technology at RWTH Aachen University since 2019. His research focuses on data contextualization, semantic annotation and metadata-based data mining with emphasis on applications in industrial areas.
Prof. Dr.-Ing. Tobias Kleinert (born 1971) graduated in Mechanical Engineering in 1999 at RWTH Aachen University and completed his PhD in 2005 at the Chair of Automation and Computer Control of Prof. Jan Lunze at Ruhr-Universität Bochum. His career led him to BASF SE where he worked in the areas of Advanced Process Control, Production Technology Propylene Oxide, Regulated Automation Solutions, Digital Control Systems, Manufacturing Execution Solutions and Smart Manufacturing. As senior manager automation and digitalization he had assignments at the BASF sites in Ludwigshafen/D, Antwerp/B and Schwarzheide/D. Since 2020, he leads the Chair of Information and Automation Systems for Process and Material Technology at RWTH Aachen University with a focus on information processing, automation and digitalization.
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Author contribution: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.
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Research funding: None declared.
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Conflict of interest statement: The authors declare no conflicts of interest regarding this article.
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