Skip to main content
SpringerLink
Log in

Model-to-Model Transformation

From UML Class Diagrams to Labeled Property Graphs

  • Research Paper
  • Published:
Business & Information Systems Engineering Aims and scope Submit manuscript

Abstract

Conceptual schemas are the basis to build well-grounded Information Systems, by representing the main concepts of a domain of knowledge, as well as the relationships among them. Since conceptual schemas focus on the concepts, they are independent of the specific technological platform used to implement them. This allows a single conceptual schema to be transformed into different platform-specific models according to the implementation requirements. This is a non-trivial process that is crucial for the performance and maintainability of the system, as well as for the accomplishment of the domain data requirements. Much research has been done on transforming conceptual schemas into relational data models. Nevertheless, less work has been done on transforming conceptual schemas into property graphs, a data structure indispensable to building appropriate and efficient systems based on graph databases. The work proposes a systematic approach to transform conceptual schemas, represented as UML class diagrams, into property graphs by using a set of transformation rules and patterns applied in a systematic way. Besides a practical example used to help the presentation of the proposed approach, the evaluation has been done by measuring different quality dimensions such as semantic equivalence, readability, maintainability, complexity, size, and performance.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17
Fig. 18
Fig. 19
Fig. 20
Fig. 21
Fig. 22
Fig. 23
Fig. 24
Fig. 25
Fig. 26
Fig. 27
Fig. 28
Fig. 29
Fig. 30
Fig. 31
Fig. 32

Similar content being viewed by others

References

  • Abdelhedi F, Brahim AA, Atigui F, Zurfluh G (2017) UMLtoNoSQL: automatic transformation of conceptual schema to nosql databases. In: 2017 IEEE/ACS 14th international conference on computer systems and applications (AICCSA), pp 272–279. https://doi.org/10.1109/AICCSA.2017.76

  • Akid H, Frey G, Ayed MB, Lachiche N (2022) Performance of NoSQL graph implementations of star vs. snowflake schemas. IEEE Access 10:48,603-48,614. https://doi.org/10.1109/ACCESS.2022.3171256

    Article  Google Scholar 

  • Albdaiwi B, Noack R, Thalheim B (2014) Pattern-based conceptual data modelling. In: Thalheim B, Jaakkola H, Kiyok Y, Yoshida N (eds) Information modelling and knowledge bases XXVI, p 21

  • Almasri N, Korel B, Tahat L (2017) Toward automatically quantifying the impact of a change in systems. Softw Qual J 25(10):3833–3861. https://doi.org/10.1109/TSE.2021.3106589

    Article  Google Scholar 

  • Almasri N, Tahat L, Korel B (2022) Verification approach for refactoring transformation rules of state-based models. IEEE Transact Softw Eng 48(3):601–640. https://doi.org/10.1007/s11219-016-9316-8

    Article  Google Scholar 

  • Blaha M (2010) Patterns of data modeling. CRC Press Inc, Boca Raton

    Book  Google Scholar 

  • Burzynski P, Karagiannis D (2020) Bee-up—a teaching tool for fundamental conceptual modelling. In: Joint proceedings of Modellierung 2020 short, workshop and tools and demo papers

  • Castelltort A, Laurent A (2014) NoSQL graph-based OLAP analysis. In: Proceedings of the international conference on knowledge discovery and information retrieval, SCITEPRESS—science and and technology publications, pp 217–224. https://doi.org/10.5220/0005072902170224

  • Daniel G, Sunyé G, Cabot J (2016) UMLtoGraphDB: mapping conceptual schemas to graph databases. Springer, Heidelberg, pp 430–444. https://doi.org/10.1007/978-3-319-46397-1_33

    Book  Google Scholar 

  • De Virgilio R, Maccioni A, Torlone R (2014) Model-driven design of graph databases. Springer, Heidelberg, pp 172–185. https://doi.org/10.1007/978-3-319-12206-9_14

    Book  Google Scholar 

  • Ehrlinger L, Huszar G, Wöß W (2019) A schema readability metric for automated data quality measurement. DBKDA, p 12

  • El Alami A, Bahaj M (2018) The migration of a (conceptual object model com conceptual data model cdm, unified modeling language uml class diagram...) to the object relational database ordb. MAGNT Res Rep 2(4):318–32

    Google Scholar 

  • Galvão J, Leon A, Costa C, Santos MY, Pastor O (2020) Towards designing conceptual data models for big data warehouses: the genomics case. In: Themistocleous M, Papadaki M, Kamal MM (eds) Information systems. Springer, New York, pp 3–19

    Chapter  Google Scholar 

  • Glaser PL, Ali SJ, Sallinger E, Bork D (2022) Model-based construction of enterprise architecture knowledge graphs. In: Almeida JPA, Karastoyanova D, Guizzardi G, Montali M, Maggi FM, Fonseca CM (eds) Enterprise design, operations, and computing, vol 13585, Springer International Publishing, New York, pp 57–73, doi: https://doi.org/10.1007/978-3-031-17604-3_4

  • Groger C, Schwarz H, Mitschang B (2014) The deep data warehouse: link-based integration and enrichment of warehouse data and unstructured content. In: 2014 IEEE 18th international enterprise distributed object computing conference. IEEE, pp 210–217. https://doi.org/10.1109/EDOC.2014.36

  • Gómez L, Kuijpers B, Vaisman A (2020) Online analytical processsing on graph data. Intell Data Anal 24(3):515–541. https://doi.org/10.3233/IDA-194576

    Article  Google Scholar 

  • Hevner M, Park R (2004) Design science in information systems research. MIS Q 28(1):75. https://doi.org/10.2307/25148625

    Article  Google Scholar 

  • Huang L, Duan Y, Sun X, Lin Z, Zhu C (2016) Enhancing uml class diagram abstraction with knowledge graph. In: Yin H, Gao Y, Li B, Zhang D, Yang M, Li Y, Klawonn F, Tallón-Ballesteros AJ (eds) Intelligent data engineering and automated learning—ideal 2016. Springer, pp 606–616

  • Jacobson L, Booch JRG (2021) The unified modeling language reference manual

  • Karagiannis D, Buchmann RA (2018) A proposal for deploying hybrid knowledge bases: the ADOxx-to-GraphDB interoperability case. In: Proceedings of the 51st Hawaii international conference on system sciences

  • Pastor O, Molina JC (2007) Model-driven architecture in practice: a software production environment based on conceptual modeling, vol 1. Springer, Heidelberg

    Google Scholar 

  • Pastor O, España S, Panach JI, Aquino N (2008) Model-driven development. Inform Spektr 31(5):394–407

    Article  Google Scholar 

  • Peffers K, Tuunanen T, Rothenberger MA, Chatterjee S (2007) A design science research methodology for information systems research. J Manag Inf Syst 24(3):45–77. https://doi.org/10.2753/MIS0742-1222240302

    Article  Google Scholar 

  • Rahayu J, Chang E, Dillon T, Taniar D (2000) A methodology for transforming inheritance relationships in an object-oriented conceptual model to relational tables. Inf Softw Technol 42(8):571–592. https://doi.org/10.1016/S0950-5849(00)00103-8

    Article  Google Scholar 

  • Robinson I, Webber J, Eifrem E (2015) Graph databases: new opportunities for connected data. O’Reilly, Sebastopol

    Google Scholar 

  • Santos MY, Costa C (2020) Big data: concepts. Warehousing and analytics. River Publishers, Gistrup

    Google Scholar 

  • Sellami A, Nabli A, Gargouri F (2020) Transformation of data warehouse schema to NoSQL graph data base. In: Abraham A, Cherukuri AK, Melin P, Gandhi N (eds) Intelligent systems design and applications, vol 941. Springer, New York, pp 410–420

    Chapter  Google Scholar 

  • Smajevic M, Hacks S, Bork D (2021) Using knowledge graphs to detect enterprise architecture smells. In: Serral E, Stirna J, Ralyté J, Grabis J (eds) The practice of enterprise modeling, vol 432. Springer, New York, pp 48–63. https://doi.org/10.1007/978-3-030-91279-6_4

  • Sparks G (2001) Database modelling in UML. Method Tools 9(1):10–23

    Google Scholar 

  • Ziemann P, Hölscher K, Gogolla M (2005) From UML models to graph transformation systems. Electron Notes Theor Comput Sci 127(4):17–33. https://doi.org/10.1016/j.entcs.2004.10.025

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Universitat Politècnica de València, Camí de Vera S/N, 46022, Valencia, Spain

    Ana León, Alberto García, Juan Carlos Casamayor & Oscar Pastor

  2. Centro ALGORITMI, Universidade do Minho, Campus de Azurém, 4800-058, Guimarães, Portugal

    Maribel Yasmina Santos

Authors
  1. Ana León
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Maribel Yasmina Santos
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Alberto García
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Juan Carlos Casamayor
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Oscar Pastor
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ana León.

Additional information

Accepted after 2 revisions by Christof Weinhardt.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

León, A., Santos, M.Y., García, A. et al. Model-to-Model Transformation. Bus Inf Syst Eng 66, 85–110 (2024). https://doi.org/10.1007/s12599-023-00824-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12599-023-00824-9

Keywords

Search

Navigation