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2nd Workshop on

Domain-Specific Modeling Methods and Tools - OMiLAB Nodes Experience & Knowledge Exchange (OMiLAB-KNOW)

September 11th, 2024
co-located with the
- 23rd International Conference on Perspectives in Business Informatics Research (https://bir2024.vse.cz/) -

Workshop Description

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The workshop aims to stimulate discussions on the requirements, use, design decisions, tooling, and evaluations regarding domain-specific conceptual modeling methods in the context of Business Informatics Research.

Discussions will be facilitated by the ongoing activities and experiences of nodes within the OMiLAB network and community of practice [1], drawing from insights and lessons learned from recent projects where modeling methods played a pivotal role, e.g. [2][3][4]. The outcomes from the network members [4][5][6][7][8][9] include modeling tools, modeling method components or extensions, model-driven artifacts, applications of domain-specific modeling, and empirical and explorative evaluation strategies. OMiLAB nodes are invited to share with the community the latest artifacts and lessons learned, along with any visions that may potentially lead to them.

Researchers and educators outside the OMiLAB network who are active in knowledge engineering, enterprise modeling, and domain-specific modeling are also encouraged to contribute to the workshop. Particularly those with an interest, in the value of conceptual models and the diversity of modeling purposes they serve. Knowledge exchanges with other modeling-centric communities are expected to drive debates and positions reflecting diverse perspectives.

Both insights from empirical experimentation [10] and design-oriented research [11] are welcome. The integration of conceptual modeling topics in curricular contents and associated teaching experiences [12] are also typical areas of interest within the workshop’s scope.

Various stages of research progress can be reported in the workshop submissions - from (short) position and vision papers to (full) research papers, tool demos, and experience reports.

References

  1. The OMiLAB Community (2022) Development of conceptual models and realization of modelling tools within the ADOxx meta-modelling environment: a living paper. In: Domain-Specific Conceptual Modeling: Concepts, Methods and ADOxx tools, Springer, pp. 25-40 https://doi.org/10.1007/978-3-030-93547-4_2
  2. DigiFoF: Digital design skills for factories of the future: https://www.digifof.eu/
  3. FAIRWork: Flexibilization of complex ecsosystems using democratic AI based decision support and recommendation systems at work: https://fairwork-project.eu/
  4. CoDEMO 5.0: Co-Creative Decision Makers for 5.0 Organizations: https://codemo-project.eu/
  5. Lantow, B., Sandkuhl, K., Stirna, J. (2022) Enterprise modeling with 4EM - perspectives and method. In Domain-Specific Conceptual Modeling: concepts, methods and ADOxx tools, Springer, pp. 95-120 https://doi.org/10.1007/978-3-030-93547-4_5
  6. Boucher X., Murillo Coba C., Lamy D. (2024) Smart PSS modelling language for value offer prototyping: A design case study in the field of heating appliance offers. Computers in Industry, 155 https://doi.org/10.1016/j.compind.2023.104041
  7. Pirola, F., Pezzotta, G., Amlashi, D.M., Cavalieri, S. (2022) Design and engineering of product-service systems (PSS): the SEEM methodology and modeling toolkit. In Domain-Specific Conceptual Modeling: concepts, methods and ADOxx tools, Springer, pp. 385-407 https://doi.org/10.1007/978-3-030-93547-4_17
  8. Richter, H.D., Lantow, B., Pröpper, T. (2022) itsVALUE - Modelling and Analysing Value Streams for IT Services. In Domain-Specific Conceptual Modeling: concepts, methods and ADOxx tools, Springer, pp. 161-183 https://doi.org/10.1007/978-3-030-93547-4_8
  9. Woitsch, R. (2020) Industrial digital environments in action: the OMiLAB innovation corner. In Proceedings of PoEM 2020, LNBIP 400, Springer, pp. 8-22 https://doi.org/10.1007/978-3-030-63479-7_2
  10. Chiș, A (2020) A modeling method for model-driven API management, Complex Systems Informatics and Modeling Quarterly, No 25, https://csimq-journals.rtu.lv/article/view/csimq.2020-25.01
  11. Gutschmidt, A., Lantow, B., Hellmanzik, B., Ramforth, B., Wiese, M. & Martins, E. (2023) Participatory modeling from a stakeholder perspective: On the influence of collaboration and revisions on psychological ownership and perceived model quality, Software and Systems Modeling 22: 13–29 https://doi.org/10.1007/s10270-022-01036-7
  12. Karagiannis, D., Buchmann, R. A., Utz, W. (2022) The OMiLAB Digital Innovation environment: Agile conceptual models to bridge business value with Digital and Physical Twins for Product-Service Systems development. Computers in Industry 138: 103631 https://doi.org/10.1016/j.compind.2022.103631
  13. Ghiran, A. M., Osman, C. C., Buchmann R. A. (2020) Advancing Conceptual Modeling Education Towards a Generalized Model Value Proposition, Advances in Information Systems Development, Selected papers from ISD 2019, LNISO 39, Springer, pp. 1-18 https://doi.org/10.1007/978-3-030-49644-9_1
  14. Völz, Alexander; Vaidian, Iulia (2024): Digital Transformation through Conceptual Modeling: The NEMO Summer School Use Case. Modellierung 2024. DOI: 10.18420/modellierung2024_014. Bonn: Gesellschaft für Informatik e.V. https://doi.org/10.18420/modellierung2024_014

Relevant Topics

  • Domain specific modeling languages for business informatics and digital innovation
  • Domain specific modeling and Artificial Intelligence
  • Domain specific modeling for low-code engineering
  • Modeling method requirements and evaluations
  • Design and deployment of conceptual modeling methods
  • Enterprise modeling for business ecosystems
  • Modeling tools and tool extensions
  • From conceptual models to digital twins and knowledge graphs
  • Model-driven engineering and model-driven artifacts
  • Enterprise architecture modeling
  • Applications, scenarios and experience reports on model use and model value
  • Empirical studies on model and modeling method qualities
  • Teaching cases and experiences with conceptual modeling
  • The future of humans, communities, and technology
  • Community-Technology Interaction in the Digital Age