Skip to main content

Quality Evaluation of a DSML Supporting Model-Driven IoT Development for Air Conditioning Facilities

  • Conference paper
  • First Online:
Advances in Enterprise Engineering XVII (EDEWC 2023)

Abstract

Model-Driven Development (MDD) is considered an effective technique for Internet of Things (IoT) application development. Our observation is that existing model-based approaches for IoT solutions focus on the software and systems perspective and show a need for more integration with organizational and business model aspects. Therefore, we developed a method and tool support for developing IoT applications in the field of air conditioning facilities. In this work, we applied quality criteria to evaluate the included Domain-Specific Modeling Language (DSML). To practically validate the modeling language as such and also the way it can be used and supported by the tool, we performed a real-world use case. The main contributions of this paper are a quality evaluation of the DSML and the tool support and lessons learned from both.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 119.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    https://www.omilab.org/MIoTA/.

  2. 2.

    https://www.adoxx.org/.

References

  1. Boren, T., Ramey, J.: Thinking aloud: reconciling theory and practice. IEEE Trans. Prof. Commun. 43(3), 261–278 (2000)

    Article  Google Scholar 

  2. Bork, D.: Metamodel-based analysis of domain-specific conceptual modeling methods. In: Buchmann, R.A., Karagiannis, D., Kirikova, M. (eds.) PoEM 2018. LNBIP, vol. 335, pp. 172–187. Springer, Cham (2018). https://doi.org/10.1007/978-3-030-02302-7_11

    Chapter  Google Scholar 

  3. Brambilla, M., Cabot, J., Wimmer, M.: Model-driven software engineering in practice. Synth. Lect. Softw. Eng. 3(1), 1–207 (2017)

    Article  Google Scholar 

  4. Ciccozzi, F., Spalazzese, R.: MDE4IoT: supporting the internet of things with model-driven engineering. In: IDC 2016. SCI, vol. 678, pp. 67–76. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-48829-5_7

    Chapter  Google Scholar 

  5. Döring, N., Bortz, J.: Forschungsmethoden und Evaluation in den Sozial- und Humanwissenschaften. Springer, Berlin (2016). https://doi.org/10.1007/978-3-642-41089-5

    Book  Google Scholar 

  6. Frank, U.: Domain-specific modeling languages: Requirements analysis and design guidelines. In: Reinhartz-Berger, I., Sturm, A., Clark, T., Cohen, S., Bettin, J. (eds.) Domain Engineering: Product Lines, Languages, and Conceptual Models, pp. 133–157. Springer, Berlin, Heidelberg (2013). https://doi.org/10.1007/978-3-642-36654-3_6

  7. Karagiannis, D., Kühn, H.: Metamodelling platforms. In: Bauknecht, K., Tjoa, A.M., Quirchmayr, G. (eds.) EC-Web 2002. LNCS, vol. 2455, pp. 182–182. Springer, Heidelberg (2002). https://doi.org/10.1007/3-540-45705-4_19

    Chapter  Google Scholar 

  8. Kim, W., Katipamula, S.: A review of fault detection and diagnostics methods for building systems. Sci. Technol. Built Environ. 24(1), 3–21 (2018)

    Article  Google Scholar 

  9. Krogstie, J.: Quality of Business Process Models. Springer, Heidelberg (2016). https://doi.org/10.1007/978-3-319-42512-2

    Book  Google Scholar 

  10. Lindland, O.I., Sindre, G., Sølvberg, A.: Understanding quality in conceptual modeling. IEEE Softw. 11(2), 42–49 (1994)

    Article  Google Scholar 

  11. Maes, A., Poels, G.: Evaluating quality of conceptual modelling scripts based on user perceptions. Data Knowl. Eng. 63(3), 701–724 (2007)

    Article  Google Scholar 

  12. Melgaard, S., Andersen, K., Marszal-Pomianowska, A., Jensen, R., Heiselberg, P.: Fault detection and diagnosis encyclopedia for building systems: a systematic review. Energies 15(12), 4366 (2022)

    Article  Google Scholar 

  13. Moody, D.: The “physics’’ of notations: toward a scientific basis for constructing visual notations in software engineering. IEEE Trans. Software Eng. 35(6), 756–779 (2009)

    Article  Google Scholar 

  14. Nast, B., Sandkuhl, K.: Meta-model and tool support for the organizational aspects of internet-of-things development methods: organizational aspects of IoT development methods. In: Proceedings of the 3rd International Conference on Advanced Information Science and System, pp. 1–6 (2021)

    Google Scholar 

  15. Nast., B., Sandkuhl., K.: Methods for model-driven development of IoT applications: requirements from industrial practice. In: Proceedings of the 18th International Conference on Evaluation of Novel Approaches to Software Engineering (ENASE 2023), pp. 170–181 (2023)

    Google Scholar 

  16. Nast, B., Sandkuhl, K., Paulus, S., Schiller, H.: MIoTA: modeling IoT applications for air conditioning facilities with ADOxx. In: BIR 2023 Workshops and Doctoral Consortium, 22nd International Conference on Perspectives in Business Informatics Research (BIR 2023), pp. 158–168 (2023)

    Google Scholar 

  17. Nelson, H.J., Poels, G., Genero, M., Piattini, M.: A conceptual modeling quality framework. Software Qual. J. 20, 201–228 (2012)

    Article  Google Scholar 

  18. OMiLAB: the ADOxx metamodelling platform. https://www.adoxx.org/live/home. Accessed 11 Oct 2023

  19. Poels, G., Maes, A., Gailly, F., Paemeleire, R.: Measuring the perceived semantic quality of information models. In: Akoka, J., et al. (eds.) ER 2005. LNCS, vol. 3770, pp. 376–385. Springer, Heidelberg (2005). https://doi.org/10.1007/11568346_41

    Chapter  Google Scholar 

  20. Sandkuhl, K., Seigerroth, U.: Method engineering in information systems analysis and design: a balanced scorecard approach for method improvement. Softw. Syst. Model. 18, 1833–1857 (2019)

    Article  Google Scholar 

  21. Sosa-Reyna, C.M., Tello-Leal, E., Lara-Alabazares, D.: Methodology for the model-driven development of service oriented IoT applications. J. Syst. Architect. 90, 15–22 (2018)

    Article  Google Scholar 

  22. Wand, Y., Weber, R.: An ontological model of an information system. IEEE Trans. Software Eng. 16(11), 1282–1292 (1990)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Benjamin Nast .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2024 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Nast, B., Sandkuhl, K. (2024). Quality Evaluation of a DSML Supporting Model-Driven IoT Development for Air Conditioning Facilities. In: Malinova Mandelburger, M., Guerreiro, S., Griffo, C., Aveiro, D., Proper, H.A., Schnellmann, M. (eds) Advances in Enterprise Engineering XVII. EDEWC 2023. Lecture Notes in Business Information Processing, vol 510. Springer, Cham. https://doi.org/10.1007/978-3-031-58935-5_4

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-58935-5_4

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-58934-8

  • Online ISBN: 978-3-031-58935-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics