Next Article in Journal
Design of U-Shaped Frequency Tunable Microwave Filters in MEMS Technology
Next Article in Special Issue
DSF Core: Integrated Decision Support for Optimal Scheduling of Lifetime Extension Strategies for Industrial Equipment
Previous Article in Journal
Stable and Accurate Estimation of SOC Using eXogenous Kalman Filter for Lithium-Ion Batteries
Previous Article in Special Issue
Enhanced Frequency Stability of SAW Yarn Tension Sensor by Using the Dual Differential Channel Surface Acoustic Wave Oscillator
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Sensors
Volume 23
Issue 1
10.3390/s23010468
sensors-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Establishing Reliable Research Data Management by Integrating Measurement Devices Utilizing Intelligent Digital Twins

by
Joel Lehmann
*,
Stefan Schorz
,
Alessa Rache
,
Tim Häußermann
,
Matthias Rädle
and
Julian Reichwald
Center for Mass Spectrometry and Optical Spectroscopy, Mannheim University of Applied Sciences, Paul-Wittsack-Straße 10, 68163 Mannheim, Germany
*
Author to whom correspondence should be addressed.
Sensors 2023, 23(1), 468; https://doi.org/10.3390/s23010468
Submission received: 12 December 2022 / Revised: 28 December 2022 / Accepted: 28 December 2022 / Published: 1 January 2023
(This article belongs to the Special Issue Advanced Sensing Technology and Data Analytics in Smart Manufacturing)
Browse Figures
Versions Notes

Abstract

One of the main topics within research activities is the management of research data. Large amounts of data acquired by heterogeneous scientific devices, sensor systems, measuring equipment, and experimental setups have to be processed and ideally be managed by Findable, Accessible, Interoperable, and Reusable (FAIR) data management approaches in order to preserve their intrinsic value to researchers throughout the entire data lifecycle. The symbiosis of heterogeneous measuring devices, FAIR principles, and digital twin technologies is considered to be ideally suited to realize the foundation of reliable, sustainable, and open research data management. This paper contributes a novel architectural approach for gathering and managing research data aligned with the FAIR principles. A reference implementation as well as a subsequent proof of concept is given, leveraging the utilization of digital twins to overcome common data management issues at equipment-intense research institutes. To facilitate implementation, a top-level knowledge graph has been developed to convey metadata from research devices along with the produced data. In addition, a reactive digital twin implementation of a specific measurement device was devised to facilitate reconfigurability and minimized design effort.
Keywords: cyber–physical system; sensor data; research data management; FAIR; digital twin; research 4.0; knowledge graph; ontology cyber–physical system; sensor data; research data management; FAIR; digital twin; research 4.0; knowledge graph; ontology

Share and Cite

MDPI and ACS Style

Lehmann, J.; Schorz, S.; Rache, A.; Häußermann, T.; Rädle, M.; Reichwald, J. Establishing Reliable Research Data Management by Integrating Measurement Devices Utilizing Intelligent Digital Twins. Sensors 2023, 23, 468. https://doi.org/10.3390/s23010468

AMA Style

Lehmann J, Schorz S, Rache A, Häußermann T, Rädle M, Reichwald J. Establishing Reliable Research Data Management by Integrating Measurement Devices Utilizing Intelligent Digital Twins. Sensors. 2023; 23(1):468. https://doi.org/10.3390/s23010468

Chicago/Turabian Style

Lehmann, Joel, Stefan Schorz, Alessa Rache, Tim Häußermann, Matthias Rädle, and Julian Reichwald. 2023. "Establishing Reliable Research Data Management by Integrating Measurement Devices Utilizing Intelligent Digital Twins" Sensors 23, no. 1: 468. https://doi.org/10.3390/s23010468

APA Style

Lehmann, J., Schorz, S., Rache, A., Häußermann, T., Rädle, M., & Reichwald, J. (2023). Establishing Reliable Research Data Management by Integrating Measurement Devices Utilizing Intelligent Digital Twins. Sensors, 23(1), 468. https://doi.org/10.3390/s23010468

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop