Skip to main content
SpringerLink
Log in

Learning Relationships Between the Business Layer and the Application Layer in ArchiMate Models

  • Conference paper
  • First Online:
Conceptual Modeling (ER 2015)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9381))

Included in the following conference series:

Abstract

Enterprise architecture provides a visualisation tool for stakeholder to manage and improve the current organization strategy to achieve its objectives. However, building an enterprise architecture is a time-consuming and often highly complex task. It involves data collection and analysis in several levels of granularity, from the physical nodes to the business execution. Existing solutions does not provide techniques to learn the relationship between the levels of granularity. In this paper, we proposed a method to correlate the business and application layers in ArchiMate notation.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
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.

    http://www.processmining.org/_media/tutorial/repairexample.zip.

  2. 2.

    http://www.bizzdesign.com/tools/bizzdesign-architect/.

  3. 3.

    http://www.troux.com/.

  4. 4.

    http://www.moodinternational.com/.

  5. 5.

    https://www.softwareag.com/corporate/products/ aris/bpa/products/sap/overview/default.asp.

References

  1. Zachman, J.A.: Enterprise architecture: the issue of the century. Database Program. Des. 10(3), 44–53 (1997)

    Google Scholar 

  2. Lankhorst, M. (ed.): Enterprise Architecture at Work: Modelling, Communication, and Analysis. Springer, Heidelberg (2005)

    Google Scholar 

  3. Kaisler, S., Armour, F., Valivullah, M.: Enterprise architecting: critical problems. In: Proceedings of the 38th Annual Hawaii International Conference on System Sciences, HICSS 2005, p. 224b, January 2005

    Google Scholar 

  4. Farwick, M., Breu, R., Hauder, M., Roth, S., Matthes, F.: Enterprise architecture documentation: empirical analysis of information sources for automation. In: 2013 46th Hawaii International Conference on System Sciences (HICSS), pp. 3868–3877, January 2013

    Google Scholar 

  5. Aier, S., Buckl, S., Franke, U., Gleichauf, B., Johnson, P., Nrman, P., Schweda, C.M., Ullberg, J., Gallen, C.-S., Mnchen, T.U.: A survival analysis of application life spans based on enterprise architecture models. In: 3rd International Workshop on Enterprise Modelling and Information Systems Architectures, pp. 141–154 (2009)

    Google Scholar 

  6. Lankhorst, M.: ArchiMate language primer, Telematica institute (2004)

    Google Scholar 

  7. van der Aalst, W., Weijters, T., Maruster, L.: Workflow mining: discovering process models from event logs. IEEE Trans. Knowl. Data Eng. 16, 1128–1142 (2004)

    Article  Google Scholar 

  8. Fdhila, W., Rinderle-Ma, S., Indiono, C.: Memetic algorithms for mining change logs in process choreographies. In: Franch, X., Ghose, A.K., Lewis, G.A., Bhiri, S. (eds.) ICSOC 2014. LNCS, vol. 8831, pp. 47–62. Springer, Heidelberg (2014)

    Chapter  Google Scholar 

  9. Wang, J., Han, J.: Bide: efficient mining of frequent closed sequences. In: Proceedings of 20th International Conference on Data Engineering, pp. 79–90, March 2004

    Google Scholar 

  10. Gomariz, A., Campos, M., Marin, R., Goethals, B.: ClaSP: an efficient algorithm for mining frequent closed sequences. In: Pei, J., Tseng, V.S., Cao, L., Motoda, H., Xu, G. (eds.) PAKDD 2013, Part I. LNCS, vol. 7818, pp. 50–61. Springer, Heidelberg (2013)

    Chapter  Google Scholar 

  11. Yan, X., Han, J., Afshar, R.: Clospan: mining closed sequential patterns in large datasets. In: SDM, pp. 166–177 (2003)

    Google Scholar 

  12. Holm, H., Buschle, M., Lagerstrm, R., Ekstedt, M.: Automatic data collection for enterprise architecture models. Softw. Syst. Model. 13(2), 825–841 (2014)

    Article  Google Scholar 

  13. Buschle, M., Holm, H., Sommestad, T., Ekstedt, M., Shahzad, K.: A tool for automatic enterprise architecture modeling. In: Nurcan, S. (ed.) CAiSE Forum 2011. LNBIP, vol. 107, pp. 1–15. Springer, Heidelberg (2012)

    Chapter  Google Scholar 

  14. Wen, L., Wang, J., van der Aalst, W.M.P., Huang, B., Sun, J.: A novel approach for process mining based on event types. J. Intell. Inf. Syst. 32, 163–190 (2009)

    Article  Google Scholar 

  15. Lankhorst, M., Proper, H., Jonkers, H.: The anatomy of the ArchiMate language. Int. J. Inf. Syst. Model. Des. 1(1), 1–32 (2010)

    Article  Google Scholar 

  16. Wierda, G.: ArchiMate 2.0 understanding the basics, White paper, The Open Group, February 2013

    Google Scholar 

  17. Jonkers, H., Band, I., Quartel, D.: The archisurance case study, White paper, The Open Group, Spring (2012)

    Google Scholar 

  18. Pei, J., Han, J., Mortazavi-Asl, B., Wang, J., Pinto, H., Chen, Q., Dayal, U., Hsu, M.-C.: Mining sequential patterns by pattern-growth: the prefixspan approach. IEEE Trans. Knowl. Data Eng. 16, 1424–1440 (2004)

    Article  Google Scholar 

  19. Zhang, M., Kao, B., Yip, C.-L., Cheung, D.: A GSP-based efficient algorithm for mining frequent sequences. In: Proceedings of IC-AI, pp. 497–503 (2001)

    Google Scholar 

  20. Zaki, M.J.: Spade: an efficient algorithm for mining frequent sequences. Mach. Learn. 42(1–2), 31–60 (2001)

    Article  MATH  Google Scholar 

  21. Viger, P.F., Gomariz, A., Gueniche, T., Soltani, A., Wu, C.-W., Tseng, V.S.: SPMF: a java open-source pattern mining library. J. Mach. Learn. Res. 15, 3389–3393 (2014)

    MATH  Google Scholar 

  22. van Dongen, B.F., de Medeiros, A.K.A., Verbeek, H.M.W.E., Weijters, A.J.M.M.T., van der Aalst, W.M.P.: The ProM framework: a new era in process mining tool support. In: Ciardo, G., Darondeau, P. (eds.) ICATPN 2005. LNCS, vol. 3536, pp. 444–454. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Decision Systems Laboratory, School of Computer Science and Software Engineering, University of Wollongong, Wollongong, NSW, 2522, Australia

    Ayu Saraswati, Aditya Ghose & Hoa Khanh Dam

  2. Centre for Oncology Informatics, University of Wollongong, Wollongong, NSW, 2522, Australia

    Chee-Fon Chang

Authors
  1. Ayu Saraswati
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Chee-Fon Chang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Aditya Ghose
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Hoa Khanh Dam
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ayu Saraswati .

Editor information

Editors and Affiliations

  1. Stockholm University, Kista, Sweden

    Paul Johannesson

  2. National University of Singapore, Singapore, Singapore

    Mong Li Lee

  3. Brigham Young University, Provo, Utah, USA

    Stephen W. Liddle

  4. University of Bergen, Bergen, Norway

    Andreas L. Opdahl

  5. Universidad Politécnica de Valencia, Valencia, Spain

    Óscar Pastor López

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer International Publishing Switzerland

About this paper

Cite this paper

Saraswati, A., Chang, CF., Ghose, A., Dam, H.K. (2015). Learning Relationships Between the Business Layer and the Application Layer in ArchiMate Models. In: Johannesson, P., Lee, M., Liddle, S., Opdahl, A., Pastor López, Ó. (eds) Conceptual Modeling. ER 2015. Lecture Notes in Computer Science(), vol 9381. Springer, Cham. https://doi.org/10.1007/978-3-319-25264-3_37

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-25264-3_37

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-25263-6

  • Online ISBN: 978-3-319-25264-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation