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ZENODO
Dataset . 2022
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2022
Data sources: ZENODO
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2022
License: CC BY
Data sources: Datacite
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A Cross-Domain Systematic Mapping Study on Software Engineering for Digital Twins

Authors: Dalibor, Manuela; NIco Jansen; Rumpe, Bernhard; Schmalzing, David; Wachtmeister, Louis; Wimmer, Manuel; Wortmann, Andreas;

A Cross-Domain Systematic Mapping Study on Software Engineering for Digital Twins

Abstract

A Systematic Cross-Domain Mapping Study on the Software Engineering of Digital Twins Manuela Dalibor, Nico Jansen, Bernhard Rumpe, David Schmalzing, Louis Wachtmeister, Manuel Wimmer, and Andreas Wortmann Digital Twins are currently investigated as the technological backbone for providing an enhanced understanding and management of existing systems as well as for designing new systems in various domains, e.g., ranging from single manufacturing components such as sensors to large-scale systems such as smart cities. Given the diverse application domains of Digital Twins, it is not surprising that the characterization of the term Digital Twin, as well as the needs for developing and operating Digital Twins are multi-faceted. Providing a better understanding what the commonalities and differences of Digital Twins in different contexts are, may allow to build reusable support for developing, running, and managing Digital Twins by providing dedicated concepts, techniques, and tool support. In this paper, we aim to uncover the nature of Digital Twins based on a systematic mapping study which is not limited to a particular application domain or technological space. We systematically retrieved a set of 1471 unique publications of which 529 were identified as potentially relevant and of which finally 356 were selected for further investigation. In particular, we analyzed the types of research and contributions made for Digital Twins, the expected properties Digital Twins have to fulfill, how Digital Twins are realized and operated, as well as how Digital Twins are finally evaluated. Based on this analysis, we also contribute a novel feature model for Digital Twins as well as several observations to further guide future software engineering research in this area.

Keywords

Digital Twin, Systematic Mapping Study, Software Engineering, Survey

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
downloads
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0
Average
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9
3