Montecchiari, Devid
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Devid
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Devid Montecchiari
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Publikation Visualizing argumentation for research problem and research design(Springer, 2024) Hinkelmann, Knut; Afonina, Valeriia; Montecchiari, Devid; Mandviwalla, Munir; Söllner, Matthias; Tuunanen, TuureIdentification of a research-worthy problem, choosing the appropriate research design, and writing based on the conducted research high-quality research paper with a well-structured argumentation is a complex and multifaceted process. Therefore, employing a comprehensive approach when identifying a research problem and composing research papers is crucial to structuring the process. Design Science Research (DSR) is a commonly applied strategy in research in Information Systems. Even though this methodology has a detailed description of every research phase, for some novice researchers it is challenging to have a comprehensive overview of their research project, from the argumentation of the studied problem to the evaluation of the results. We claim that conceptual modeling can visually represent these argumentations and key elements of DSR. We provide a metamodel to represent relevant aspects of the research and the connections between them, which might be depicted as graphical elements and connectors. This approach significantly improves understanding and structuring of the research problem and design, leveraging on literature about argumentation and motivation modeling.04B - Beitrag KonferenzschriftPublikation Enhancing research clarity. Ontology-based modeling of argumentation in RPML(Springer, 2024) Hinkelmann, Knut; Afonina, Valeriia; Montecchiari, Devid; Almeida, João Paulo A.; Di Ciccio, Claudio; Kalloniatis, ChristosNavigating the research process, from problem identification to argumentation construction, challenges novice researchers. This study introduces RPML (Research Problem Modeling Language), a metamodel and ontology designed to address these challenges by visually representing key aspects of research argumentation. RPML enhances clarity and coherence in research discourse by providing researchers with a visual representation of argumentation for a research problem. RPML is represented as a specialization of the OMG Business Motivation Model and Toulmin’s argumentation model approach. This enables researchers to gain a comprehensive overview of their research projects, identify research problems, build robust argumentation, and select suitable research strategies.04B - Beitrag KonferenzschriftPublikation Enriching enterprise architecture models with healthcare domain knowledge(Springer, 2023) Afonina, Valeriia; Hinkelmann, Knut; Montecchiari, DevidEnterprise architecture (EA) modeling gives an opportunity to have an overview of the enterprise architecture supporting business-IT alignment within the rapidly changing environment. Visual representation of enterprise architecture models is appropriate for interpretation by humans. Machines, however, cannot interpret labels associated with the model element, as well as its domain-specific concepts. To make EA models machine-interpretable, a graphical representation of models shall be connected to domain knowledge. This research demonstrates an approach to enriching the EA model of a medical institution with healthcare domain knowledge. Evaluation of the developed solution proves that a human and a machine could equally understand the ontology-based EA model.04B - Beitrag KonferenzschriftPublikation Supporting reuse of business process models by semantic annotation(Springer, 2023) Baumann, Fabian; Hinkelmann, Knut; Montecchiari, DevidBusiness Process Management (BPM) is a widely applied discipline in many organizations. Creating and maintaining business process models is a task that still requires much human work and is costly and cumbersome. The reuse of business process models is a solution to minimize human effort and increase quality. For reuse, appropriate process models must be discovered in a repository. Enrichment of the models with semantic annotations from domain ontologies can leverage better results for of discovering reusable process models. Although using semantically annotated business process models for the case of reuse has been mentioned and proposed in the literature, the exact requirements and implementation have yet to be analyzed in detail. This paper closes this research gap with an artifact in the form of a methodology to discover business process models. This includes a list of relevant criteria, a base ontology, possible automated annotation techniques, and a query form.04B - Beitrag KonferenzschriftPublikation Towards ontology-based validation of EA principles(2022) Montecchiari, Devid; Hinkelmann, Knut; Barn, Balbir S.; Sandkuhl, Kurt04B - Beitrag KonferenzschriftPublikation Ontology-based validation of enterprise architecture principles in enterprise models(2021) Montecchiari, DevidEnterprises use Enterprise Architecture Principles as a guiding set of rules to provide a basis for decision making. These principles are described using natural language and are not machine-interpretable. The validation of these principles in models is a complex and time-consuming task. The goal of this research is to help humans in this review. Annotating enterprise architecture models with an enterprise ontology and representing architecture principles as rules, it is possible to automatically check architecture principles. The proposed approach is to combine both the domain knowledge and the modeling language knowledge to reason about models, allowing the automatic check of architecture principles.04B - Beitrag KonferenzschriftPublikation Hybrid conversational AI for intelligent tutoring systems(Sun SITE, Informatik V, RWTH Aachen, 2021) Pande, Charuta; Witschel, Hans Friedrich; Martin, Andreas; Montecchiari, Devid; Martin, Andreas; Hinkelmann, Knut; Fill, Hans-Georg; Gerber, Aurona; Lenat, Dough; Stolle, Reinhard; Harmelen, Frank vanWe present an approach to improve individual and self-regulated learning in group assignments. We focus on supporting individual reflection by providing feedback through a conversational system. Our approach leverages machine learning techniques to recognize concepts in student utterances and combines them with knowledge representation to infer the student’s understanding of an assignment’s cognitive requirements. The conversational agent conducts end-to-end conversations with the students and prompts them to reflect and improve their understanding of an assignment. The conversational agent not only triggers reflection but also encourages explanations for partial solutions.04B - Beitrag KonferenzschriftPublikation Ontology-based visualization for business model design(Springer, 2020) Peter, Marco; Montecchiari, Devid; Hinkelmann, Knut; Gatziu Grivas, Stella; Grabis, Jānis; Bork, DominikThe goal of this paper is to demonstrate the feasibility of combining visualization and reasoning for business model design by combining the machine-interpretability of ontologies with a further development of the widely accepted business modeling tool, the Business Model Canvas (BMC). Since ontologies are a machine-interpretable representation of enterprise knowledge and thus, not very adequate for human interpretation, we present a tool that combines the graphical and human interpretable representation of BMC with a business model ontology. The tool connects a business model with reusable data and interoperability to other intelligent business information systems so that additional functionalities are made possible, such as a comparison between business models. This research follows the design science strategy with a qualitative approach by applying literature research, expert interviews, and desk research. The developed AOAME4BMC tool consists of the frontend, a graphical web-based representation of an enhanced BMC, a web service for the data exchange with the backend, and a speci c ontology for the machine-interpretable representation of a business model. The results suggest that the developed tool AOAME4BMC supports the suitability of an ontology-based representation for business model design.04B - Beitrag KonferenzschriftPublikation Agile visualization in design thinking(Springer, 2020) Laurenzi, Emanuele; Hinkelmann, Knut; Montecchiari, Devid; Goel, Mini; Dornberger, RolfThis chapter presents an agile visualization approach that supports one of the most widespread innovation processes: Design Thinking. The approach integrates the pre-defined graphical elements of SAP Scenes to sketch digital scenes for storyboards. Unforeseen scenarios can be created by accommodating new graphical elements and related domain-specific aspects on-the-fly. This fosters problem understanding and ideation, which otherwise would be hindered by the lack of elements. The symbolic artificial intelligence (AI)-based approach ensures the machineinterpretability of the sketched scenes. In turn, the plausibility check of the scenes is automated to help designers creating meaningful storyboards. The plausibility check includes the use of a domain ontology, which is supplied with semantic constraints. The approach is implemented in the prototype AOAME4Scenes, which is used for evaluation.04A - Beitrag SammelbandPublikation 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, BranMany 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