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Astract: With the emergence of Cyber-Physical Systems (CPS), several sophisticated runtime monitoring solutions havebeen proposed in order to deal with extensive execution logs. One promising development in this respect is the integration oftime series databases that support the storage of massive amounts of historical data as well as to provide fast query capabilitiesto reason about runtime properties of such CPS.In this paper, we discuss how conceptual modeling can benefit from time series databases, and vice versa. In particular,we present how metamodels and their instances, i.e., models, can be partially mapped to time series databases. Thus, thetraceability between design and simulation/runtime activities can be ensured by retrieving and accessing runtime information,i.e., time series data, in design models. On this basis, the contribution of this paper is four-fold. First, a dedicated profilefor annotating design models for time series databases is presented. Second, a mapping for integrating the metamodelingframework EMF with InfluxDB is introduced as a technology backbone enabling two distinct mapping strategies for modelinformation. Third, we demonstrate how continuous time series queries can be combined with the Object Constraint Language(OCL) for navigation through models, now enriched with derived runtime properties. Finally, we also present an initial evaluationof the different mapping strategies with respect to data storage and query performance. Our initial results show the efficiency ofapplying derived runtime properties as time series queries also for large model histories.

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Astract: Among the plethora of industrial standards available in the context of smart manufacturing, one series of standards is consistently being mentioned for dealing with manufacturing operations management: IEC 62264. Its second part provides a conceptual model for the description of production systems and their capabilities, including runtime information such as concrete maintenance schedules or achieved production goals. In this work, we present a concrete graphical syntax and toolkit for the creation and presentation of IEC 62264-2 compliant models, using techniques from model-driven (software) engineering. We have evaluated our tool by conducting a user study for assessing its usability and effectiveness.

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Astract: Es gibt zahlreiche Publikationen, die die digitale Transformation im Tief- und Tunnelbau propagieren. Als Lösungsansatz wird dabei immer wieder Building Information Modeling (BIM) genannt und die Umsetzung der digitalen Transformation basierend auf dieser Methodik gefordert. Der prototypische Charakter eines Tunnelbauprojekts erschwert jedoch eine standardisierte Vorgehensweise. Hinzu kommt, dass die beteiligten Fachdisziplinen für unterschiedliche Gewerke individuelle Softwaretools mit proprietären (nicht standardisierten) Datenformaten nutzen. Durch diese in sich geschlossenen Datenmodelle ist eine offene BIM Arbeitsweise (Open BIM) nur schwer zu realisieren. Das hat der Lehrstuhl für Subsurface Engineering an der Montanuniversität Leoben zum Anlass genommen und zwei anwendungsorientierte Forschungsprojekte zur digitalen Transformation im Tief- und Tunnelbau lanciert, deren Inhalte in diesem Artikel kurz vorgestellt werden. Das „Zentrum am Berg (ZaB)“ dient in beiden Projekten als zentrale Infrastruktur zu Evaluierungszwecken.

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Astract: Legacy systems and their associated data models often evolve into large, monolithic artifacts. This threatens comprehensibility and maintainability by human beings. Breaking down a monolith into a modular structure is an established technique in software engineering. Several previous works aimed to adapt modularization also for conceptual data models. However, we currently see a research gap manifested in the absence of: (i) a flexible and extensible modularization concept for Entity Relationship (ER) models; (ii) of openly available tool support; and (iii) empirical evaluation. With this paper, we introduce a generic encoding of a modularization concept for ER models which enables the use of meta-heuristic search approaches. For the efficient application we introduce the ModulER tool. Eventually, we report on a twofold evaluation: First, we demonstrate feasibility and performance of the approach by two demonstration cases. Second, we report on an initial empirical experiment and a survey we conducted with modelers to compare automated modularizations with manually created ones and to better understand how humans approach ER modularization.

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Astract: Variability is crucial in the design of many advanced goods and it is also receiving increasing attention in production systems engineering. Since OPC Unified Architecture plays an important role when it comes to standardized information exchange in modern production systems, it can be a melting pot for information from various engineering domains, such as product design and production engineering - thus, it is an ideal place to hold variability information of products and production systems alike. Based on an initial variability information model we propose additional concepts for the persisting of configurations.

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Astract: Although Model-Based Software Engineering (MBE) is a widely accepted Software Engineering (SE) discipline, no agreed-upon core set of concepts and practices (i.e., a Body of Knowledge) has been defined for it yet. With the goals of characterizing the contents of the MBE discipline, promoting a global consistent view of it, clarifying its scope with regard to other SE disciplines, and defining a foundation for the development of educational curricula on MBE, this paper proposes the contents for a Body of Knowledge for MBE. We also describe the methodology that we have used to come up with the proposed list of contents, as well as the results of a survey study that we conducted to sound out the opinion of the community on the importance of the proposed topics and their level of coverage in the existing SE curricula.

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Astract: Model-driven engineering (MDE) provides tools and methods for the manipulation of formal models. In this letter, we leverage MDE for the transformation of production system models into flat files that are understood by general purpose planning tools and that enable the computation of "plans", i.e., sequences of production steps that are required to reach certain production goals. These plans are then merged back into the production system model, thus enriching the formalized production system knowledge.

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Astract: The CPS/IoT Ecosystem project aims to build an IoT infrastructure that will be used as a platform for research and education in multiple disciplines related to CPS and IoT. The main objective is to provide a real-world infrastructure, and allow students and researchers explore its capabilities on actual use cases.