Spahic, Maja

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Maja
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Spahic, Maja

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2020 - 20235
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  • Vorschaubild
    Publikation
    A new approach for teaching programming: model-based agile programming (MBAD)
    (ACM, 2023) Telesko, Rainer; Spahic, Maja; Hinkelmann, Knut; Pande, Charuta [in: ICIEI 2023. Proceedings of 2023 The 8th International Conference on Information and Education Innovations]
    Designing courses for introductory programming courses with a heterogeneous audience (business and IT background as well) is a challenging task. In an internal project of the School of Business at the FHNW University of Applied Sciences and Arts Northwestern Switzerland (FHNW) a group of lecturers developed a concept entitled “Model-based agile development” (MBAD) which supports the learning of elementary programming concepts in an agile environment and builds the basis for advanced courses. MBAD will be used as a basic learning module for various Bachelor programs at the FHNW.
    04B - Beitrag Konferenzschrift
  • Vorschaubild
    Publikation
    Ontology-driven enhancement of process mining with domain knowledge
    (Sun SITE, Informatik V, RWTH Aachen, 2023) Eichele, Simon; Hinkelmann, Knut; Spahic, Maja; Martin, Andreas; Fill, Hans-Georg; Gerber, Aurona; Hinkelmann, Knut; Lenat, Doug; Stolle, Reinhard; Harmelen, Frank van [in: Proceedings of the AAAI 2023 Spring Symposium on Challenges Requiring the Combination of Machine Learning and Knowledge Engineering (AAAI-MAKE 2023)]
    Process mining is a technique used to analyze and understand business processes. It uses as input the event log, a type of data used to represent the sequence of activities occurring within a business process. An event log typically contains information such as the case ID, the performed activity’s name, the activity’s timestamp, and other data associated with the activity. By analyzing event logs, organizations can gain a deeper understanding of their business processes, identify areas for improvement, and make data-driven decisions to optimize their operations. However, as the event logs contain data collected from different systems involved in the process, such as ERP, CRM, or WfMS systems, they often lack the necessary context and knowledge to analyze and fully comprehend business processes. By extending the event logs with domain knowledge, organizations can gain a more complete and accurate insight into their business processes and make more informed decisions about optimizing them. This paper presents an approach for enhancing process mining with domain knowledge preserved in domain-specific OWL ontologies. Event logs are typically stored in structured form in relational databases. This approach first converts the process data into an event log which is then mapped with ontology concepts. The ontology contains classes and individuals representing background knowledge of the domain, which supports the understanding of the data. A class for the specific activities forms the link between the event log and the ontology. In this manner, it is possible to map the domain knowledge to a particular case and activity. This allows to determine conditions that must be satisfied for executing tasks and to prune discovered process models if they are too complex. This approach is demonstrated using data from the student admission process at FHNW and has been implemented in Protégé.
    04B - Beitrag Konferenzschrift
  • Vorschaubild nicht verfügbar
    Publikation
    Enterprise maps: zooming in and out of enterprise models
    (SciTePress, 2022) Spahic, Maja; Hinkelmann, Knut; Filipe, Joaquim; Smialek, Michal; Brodsky, Alexander; Hammoudi, Slimane [in: Proceedings of the 24th International Conference on Enterprise Information Systems]
    A company’s architecture can be represented by domain-specific models, which are defined by domain-specific modeling language. Since not all stakeholders are interested in the same models, dedicated views can be created to support navigation through the enterprise models. These views offer a snippet of the entire company and cover stakeholder-specific concerns. The relationships between the different views and models remain hidden and can be unveiled with much effort. The developed concept of the zoomability principle offers the ability to change the degree of detail using zoom in and out of the enterprise model. The different models and modeling languages used to express an enterprise are considered, and a form of navigation is established similar to an online map. The concept is based on two pillars,”Zoom Within” and”Zoom into Complements”. For this purpose, a metamodel was developed, which formalizes the elements used in the concept and their relationships. Developing the artifact, rules were defined that contribute to a generic approach allowing an application to another case. Furthermore, a prototype was developed, representing the zoomability principle and offering the possibility to perform zooming behavior. The artifact was evaluated through a demonstration. An additional prototype was created to demonstrate that the developed concept can be applied to a predefined set of situations.
    04B - Beitrag Konferenzschrift
  • Vorschaubild nicht verfügbar
    Publikation
    ArchiMEO: A standardized enterprise ontology based on the ArchiMate conceptual model
    (2020) Hinkelmann, Knut; Laurenzi, Emanuele; Martin, Andreas; Montecchiari, Devid; Spahic, Maja; Thönssen, Barbara; Hammoudi, Slimane; Ferreira Pires, Luis; Selić, Bran [in: Proceedings of the 8th International Conference on Model-Driven Engineering and Software Development]
    Many enterprises face the increasing challenge of sharing and exchanging data from multiple heterogeneous sources. Enterprise Ontologies can be used to effectively address such challenge. In this paper, we present an Enterprise Ontology called ArchiMEO, which is based on an ontological representation of the ArchiMate standard for modeling Enterprise Architectures. ArchiMEO has been extended to cover various application domains such as supply risk management, experience management, workplace learning and business process as a service. Such extensions have successfully proven that our Enterprise Ontology is beneficial for enterprise applications integration purposes.
    04B - Beitrag Konferenzschrift
  • Vorschaubild nicht verfügbar
    Publikation
    Comparison of swarm and graph algorithms for solving travelling salesman problems
    (2020) Eggenschwiler, Stefan; Spahic, Maja; Hanne, Thomas; Dornberger, Rolf [in: 2020 7th Intl. Conference on Soft Computing Machine Intelligence (ISCMI 2020). November 14-15, 2020, Stockholm, Sweden]
    04B - Beitrag Konferenzschrift