Skip to main content

An Automated Patterns-Based Model-to-Model Mapping and Transformation System for Labeled Property Graphs

  • Conference paper
  • First Online:
Research Challenges in Information Science: Information Science and the Connected World (RCIS 2023)

Abstract

Due to the increasing collection of highly interconnected and complex datasets, Labeled Property Graphs are gaining importance in extracting meaningful information for decision support. In addition, UML Class Diagrams are still a commonly used modeling technique for representing the main concepts of a domain. Although there are several model-to-model transformation approaches, these are mainly focused on moving from class diagrams to relational databases. Less work has been done on transforming class diagrams into labeled property graphs. This work constitutes a step forward in filling this gap by i) using a method that defines a set of patterns to improve the transformation process from class diagrams to labeled property graphs, considering the analytical requirements of a domain, and ii) proposing a technological system as an instantiation of the method, demonstrating its feasibility and enabling the assessment of its suitability. This system is grounded in a collection of templates for specifying the domain concepts and a library of transformation rules and patterns, and was evaluated using a widely known dataset exhibiting the proposed model-to-model transformation approach.

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

Access this chapter

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 79.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 99.99
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

Similar content being viewed by others

References

  1. Abdelhedi, F., Brahim, A.A., Atigui, F., Zurfluh, G.: MDA-based approach for NOSQL databases. In: 19th International Conference on Big Data Analytics and Knowledge Discovery (DaWaK 2017), pp. 88–102 (2017)

    Google Scholar 

  2. Almasri, N., Korel, B., Tahat, L.: Toward automatically quantifying the impact of a change in systems. Softw. Qual. J. 25(10), 3833–3861 (2017)

    Google Scholar 

  3. Almasri, N., Tahat, L., Korel, B.: Verification approach for refactoring transformation rules of state-based models. IEEE Trans. Softw. Eng. 48(3), 601–640 (2022)

    Google Scholar 

  4. Angles, R., Gutierrez, C.: Survey of graph database models. ACM Comput. Surv. 40 (2008)

    Google Scholar 

  5. Billen, R.: Uml as a schema candidate for graph databases. University of Liège, Technical report (2014)

    Google Scholar 

  6. Chebotko, A., Kashlev, A., Lu, S.: A big data modeling methodology for apache cassandra. In: 2015 IEEE International Congress on Big Data, pp. 238–245. Institute of Electrical and Electronics Engineers Inc., August 2015

    Google Scholar 

  7. Cuadrado, J.S., Guerra, E., Lara, J.D.: A component model for model transformations. IEEE Trans. Softw. Eng. 40, 1042–1060 (2014)

    Article  Google Scholar 

  8. Daniel, G., Sunyé, G., Cabot, J.: UMLtoGraphDB: mapping conceptual schemas to graph databases. In: Comyn-Wattiau, I., Tanaka, K., Song, I.-Y., Yamamoto, S., Saeki, M. (eds.) ER 2016. LNCS, vol. 9974, pp. 430–444. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-46397-1_33

    Chapter  Google Scholar 

  9. Ehrlinger, L., Huszar, G., Wöß, W.: A schema readability metric for automated data quality measurement. In: Eleventh International Conference on Advances in Databases, Knowledge, and Data Applications (DBKDA), p. 12 (2019)

    Google Scholar 

  10. Favre, J.M., Nguyen, T.: Towards a megamodel to model software evolution through transformations. Electron. Notes Theoret. Comput. Sci. 127, 59–74 (2005)

    Article  Google Scholar 

  11. Kahani, N., Cordy, J.R.: Comparison and evaluation of model transformation tools. Technical report, School of Computing, Queen’s University Kingston, Ontario, December 2015

    Google Scholar 

  12. Lano, K., Kolahdouz-Rahimi, S.: Model-transformation design patterns. IEEE Trans. Softw. Eng. 40, 1224–1259 (2014)

    Article  Google Scholar 

  13. León Palacio, A., Santos, M.Y., García, A., Casamayor, J.C., Pastor, O.: Model-to-Model Transformation: From UML Conceptual Schemas to Labeled Property Graphs. Accepted for publication, Business & Information Systems Engineering (2023)

    Google Scholar 

  14. Li, C.: Transforming relational database into Hbase: a case study. In: 2010 IEEE International Conference on Software Engineering and Service Sciences, pp. 683–687 (2010)

    Google Scholar 

  15. Mali, J., Atigui, F., Azough, A., Travers, N.: ModelDrivenGuide: an approach for implementing NoSQL schemas. In: Hartmann, S., Küng, J., Kotsis, G., Tjoa, A.M., Khalil, I. (eds.) DEXA 2020. LNCS, vol. 12391, pp. 141–151. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-59003-1_9

    Chapter  Google Scholar 

  16. Mior, M.J., Salem, K., Aboulnaga, A., Liu, R.: Nose: schema design for NOSQL applications. IEEE Trans. Knowl. Data Eng. 29, 2275–2289 (2017)

    Article  Google Scholar 

  17. OMG: Object management group model driven architecture (MDA) rev. 2.0. Technical report, The Object Management Group (2014). http://www.omg.org/mda/

  18. Peffers, K., Tuunanen, T., Rothenberger, M.A., Chatterjee, S.: A design science research methodology for information systems research. J. Manag. Inf. Syst. 24(3), 45–77 (2007)

    Article  Google Scholar 

  19. Rodrigues, M., Santos, M.Y., Bernardino, J.: Big data processing tools: an experimental performance evaluation. WIREs Data Mining Knowl. Disc. 9(2) (2019)

    Google Scholar 

  20. Di Ruscio, D., Eramo, R., Pierantonio, A.: Model transformations. In: Bernardo, M., Cortellessa, V., Pierantonio, A. (eds.) SFM 2012. LNCS, vol. 7320, pp. 91–136. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-30982-3_4

    Chapter  Google Scholar 

  21. Smajevic, M., Bork, D.: From conceptual models to knowledge graphs: a generic model transformation platform. In: 2021 ACM/IEEE International Conference on Model Driven Engineering Languages and Systems Companion (MODELS-C), pp. 610–614 (2021)

    Google Scholar 

  22. TPPC: Transaction Processing Performance Council. (2017). TPC-H Specification (Decision Support), Standard Specification, Revision 2.17.2 (2017). http://www.tpc.org/tpc_documents_current_versions/pdf/tpc-h_v2.17.2.pdf

  23. Wang, T., Truptil, S., Benaben, F.: An automatic model-to-model mapping and transformation methodology to serve model-based systems engineering. Inf. Syst. E-Bus Manage. 15 (2017)

    Google Scholar 

  24. Ziemann, P., Hölscher, K., Gogolla, M.: From UML models to graph transformation systems. Electron. Notes Theoret. Comput. Sci. 127, 17–33 (2005)

    Article  MATH  Google Scholar 

Download references

Acknowledgements

This work has been supported by FCT - Fundação para a Ciência e Tecnologia within the R &D Units Project Scope: UIDB/00319/2020, and by the Spanish Ministry of Universities and the Universitat Politècnica de València under the Margarita Salas Next Generation EU grant.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Pedro Guimarães .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2023 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

Guimarães, P., León, A., Santos, M.Y. (2023). An Automated Patterns-Based Model-to-Model Mapping and Transformation System for Labeled Property Graphs. In: Nurcan, S., Opdahl, A.L., Mouratidis, H., Tsohou, A. (eds) Research Challenges in Information Science: Information Science and the Connected World. RCIS 2023. Lecture Notes in Business Information Processing, vol 476. Springer, Cham. https://doi.org/10.1007/978-3-031-33080-3_11

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-33080-3_11

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-33079-7

  • Online ISBN: 978-3-031-33080-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics