Dipl.-Inform. Jan Novacek (Kopie 2)

Research Scientist

Werdegang

Jan Novacek hat von 2007 bis 2014 am Karlsruher Institut für Technologie (KIT) Informatik studiert und mit einem Diplom abgeschlossen.

Seine Vertiefungsfächer waren Softwaretechnik und Anthropomatik.

Seit Februar 2015 ist er am FZI als Gastwissenschaftler im Forschungsbereich ISPE in der Abteilung SiM und seit Februar 2016 als wissenschaftlicher Mitarbeiter.

Publications

Articles (1)

1. Reasoning-Supported Robustness Validation of Automotive E/E ComponentsInfoDetails

   Jan Novacek, Alexander Viehl, Oliver Bringmann, Wolfgang Rosenstiel, 2017

   This article presents an ontology-supported approach to tackle the complexity of the Robustness Validation (RV) process of automotive electrical/electronic (E/E) components. The approach uses formalized knowledge from the RV process and stress, operating, and load profiles, so-called Mission Profiles (MPs). In contrast to the error-prone industrially established manual procedure, we show how component characteristics are formalized in OWL in order to form the foundation of an efficient automated analysis selection and decision support during the RV process. Additionally, a rule-based transformation of component characteristics upon propagation via SWRL is described. The proposed approach is based on the idea of mapping MPs to an OWL representation in order to allow to execute semantic queries against MP data to improve their integration into the RV process. The resulting ontology-supported application framework has been applied to an industrial use-case from automotive power electronics. A generalization of the approach is described and demonstrated by applying it to stress test selection within the AEC Q100 standard. We present experimental results showing that the RV process can be significantly improved in terms of reduced design time and increased exhaustiveness by automating the analyses selection step and the provisioning of all the relevant data to be used.

Conference Proceedings (5)

1. LEMONS: Leveraging Model-Based Techniques to Enable Non-Intrusive Semantic Enrichment in Wireless Sensor NetworksInfoDetails

   Jan Novacek, Arthur Kühlwein, Sebastian Reiter, Alexander Viehl, Oliver Bringmann, Wolfgang Rosenstiel, 2020

   The paper presents an efficient approach to the semantic enrichment of measured sensor data in Wireless Sensor Networks (WSNs), by bridging techniques from Model-driven Software Development (MDSD) and Semantic Web Technology (SWT). Our approach reinforces data interoperability, fostering data sharing and reuse, by utilizing SWT. Model-based and type-agnostic configuration reduces the overall effort for WSN setup and maintenance, which are traditionally complex and time-consuming tasks. The presented approach addresses the problem of large-scale WSN management through the application of SWT in WSN configuration and management without requiring expert knowledge. Additionally, we present a generic architecture and an implementation which is also supplemented by hands-on descriptions of an illustrative use case. Our experimental results demonstrate that our model-based approach provides non-intrusive semantic enrichment with sub-millisecond computational overhead, as well as partially automated configuration of WSNs.

2. Ontology-based Requirements TransformationInfoDetails

   Jan Novacek, Alexander Viehl, Oliver Bringmann, Wolfgang Rosenstiel, 2019

   This paper presents an ontology-based approach to the supply chain-aware transformation of functional and environmental load requirements given by so-called Mission Profiles (MPs). The approach aims at improving the efficiency of the engineering process through supporting the transformation process and enabling a better integration of the transformation into existing Model-based Systems Engineering (MBSE) processes. We propose a methodology and a supporting system which aids in the transformation process while the latter feature is obtained by constructing and working on models. Consequent utilization of the standardized language OWL to express model representations further enables better knowledge integration and transfer among heterogeneous systems. In addition to that, this favors knowledge reuse across projects which can reduce overall costs. Moreover, the system enables stripping off irrelevant information from MPs, thus improving protection of intellectual property.

3. CTEF: Collaborative Technology Evaluation Framework Details

   Ali Ahari, Jan Novacek, Alexander Viehl, Oliver Bringmann, Wolfgang Rosenstiel , 2018

4. Ontology-Supported Design Parameter Management for Change Impact AnalysisInfoDetails

   J. Novacek and A. Ahari and A. Cornaglia and F. Haxel and A. Viehl and O. Bringmann and W. Rosenstiel, 2018

   This paper presents an ontology-supported approach to the management of design parameters in engineering. This approach aims specifically at enabling Change Impact Analysis through Requirements Traceability and acquainted expert knowledge of design parameters. The approach is suitable for both software and hardware designs. The activities and features are mainly obtained by (1) the application of an ontology-based universal system modeling procedure proposal for model integration, (2) the utilization of a knowledge base for capturing expert knowledge and (3) a semantic Mission Profile Aware Design platform. OWL is used to represent information and the underlying data model can improve knowledge transfer among heterogeneous systems which are common in complex engineering projects. At the same time, effort to perform reasoning on such models can be reduced. A demonstration and hands-on description of two illustrative use cases complements the paper.

5. Reasoning-Supported Robustness Validation of Automotive E/E ComponentsInfoDetails

   Jan Novacek, Alexander Viehl, Oliver Bringmann, Wolfgang Rosenstiel, 2017

   This paper presents an ontology-supported approach to tackle the complexity of the Robustness Validation (RV) process of automotive electrical/electronic (E/E) components. The approach uses formalized knowledge from the RV process and stress, operating, and load profiles, so-called Mission Profiles (MPs). In contrast to the error-prone industrially established manual procedure, we show how component characteristics are formalized in OWL in order to form the foundation of an efficient automated analysis selection and decision support during the RV process. The proposed approach is based on the idea of mapping MPs to an OWL representation so to allow to perform semantic queries against MP data to improve their integration into the RV process. The resulting ontology-supported application framework has been applied to an industrial use-case from automotive power electronics. We present experimental results showing that the RV process can be significantly improved in terms of reduced design time and increased exhaustiveness by automating the analyses selection step and the provisioning of all the relevant data to be used.

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Kontakt

Telefon: +49 721 9654-424
E-Mail: novacek@dont-want-spam.fzi.de

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