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

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.

Digital Twins' Maturity: The Need for Interoperability

“…Despite reservations about data sharing, recent research indicates that the value of data increases when it is shared and reused, and thus data sharing is increasingly recognized as an important driver in the digital economy [80]. A major contribution facilitating data exchange and usage is the Findable, accessible, interoperable, and reusable (FAIR) principles [81], according to which data should be FAIR throughout the data lifecycle, which are intended to serve as a guide for those seeking to improve the capacity of computational systems to find, access, interoperate, and reuse data with none or minimal human intervention [82]. The FAIR principles can thus help to establish and maintain trust among DTs by ensuring the security, integrity, transparency, and traceability of the data they share.…”

Comparing Avatar and Face-to-Face Collaboration in VR Education: Concept and Preliminary Insights

“…However, the application of DT systems is not limited to the industrial environment. Lehmann et al [13] demonstrated that such cyber-physical systems can also be used in a scientific context to organize research data. Furthermore, these technological approaches can also be used for knowledge transfer for students and teachers to their advantage.…”

Digital Twin-Based Concept for Reliable Research Data Management

“…In the preliminary work [14], [15] we proposed an RDM infrastructure offering extensive capabilities for storing and preserving research data in accordance with FAIR criteria utilizing DTs as well as agent-based DTs. The Physical Twin Space holds physical devices such as mass spectrometers (P T 1 -P T n ), each of having a unique DT (DT 1 -DT n ) which is provided using the existing infrastructure in the Digital Twin Space.…”