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2022 | OriginalPaper | Buchkapitel

Model-Based Construction of Enterprise Architecture Knowledge Graphs

verfasst von : Philipp-Lorenz Glaser, Syed Juned Ali, Emanuel Sallinger, Dominik Bork

Erschienen in: Enterprise Design, Operations, and Computing

Verlag: Springer International Publishing

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Abstract

Enterprise Architecture offers guidelines for the coherent, model-based design and management of enterprises. EA models provide a layered, integrated, and cohesive representation of the enterprise, enabling communication, analysis, and decision making. With the increasing size of EA models, automated analysis becomes essential. However, advanced model analysis is neither incorporated in current EA methods like ArchiMate nor supported by existing EA tools like Archi. Knowledge Graphs (KGs) can effectively organize and represent knowledge and enable reasoning to utilize this knowledge, e.g., for decision support. This paper introduces a model-based Enterprise Architecture Knowledge Graph (EAKG) construction method and shows how starting from ArchiMate models, an initially derived EAKG can be further enriched by EA-specific and graph characteristics-based knowledge. The introduced EAKG entails new representation and reasoning methods applicable to EA knowledge. As a proof of concept, we present the results of a first Design Science Research Cycle aiming to realize an Archi plugin for the EAKG that enables analysis of EA Smells within ArchiMate models.

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Vorheriges Kapitel Security Ontologies: A Systematic Literature Review

Nächstes Kapitel Enterprise Architecture Management Support for Digital Transformation Projects in Very Large Enterprises: A Case Study at a European Mobility Provider

https://www.archimatetool.com/, last accessed: 15.08.2022.

https://swc-public.pages.rwth-aachen.de/smells/ea-smells/, accessed: 11.05.2022.

EAKG Github repository: https://github.com/borkdominik/archi-kganalysis-plugin.

Archi plugins: https://www.archimatetool.com/plugins/, accessed 02.05.2022.

Ahlemann, F., Stettiner, E., Messerschmidt, M., Legner, C.: Strategic Enterprise Architecture Management: Challenges, Best Practices, and Future Developments. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-24223-6CrossRef

Auer, S., Bizer, C., Kobilarov, G., Lehmann, J., Cyganiak, R., Ives, Z.: DBpedia: a nucleus for a web of open data. In: Aberer, K., et al. (eds.) ASWC/ISWC -2007. LNCS, vol. 4825, pp. 722–735. Springer, Heidelberg (2007). https://doi.org/10.1007/978-3-540-76298-0_52CrossRef

Bakhshadeh, M., Morais, A., Caetano, A., Borbinha, J.: Ontology transformation of enterprise architecture models. In: Camarinha-Matos, L.M., Barrento, N.S., Mendonça, R. (eds.) DoCEIS 2014. IAICT, vol. 423, pp. 55–62. Springer, Heidelberg (2014). https://doi.org/10.1007/978-3-642-54734-8_7CrossRef

Barbosa, A., Santana, A., Hacks, S., Stein, N.V.: A taxonomy for enterprise architecture analysis research. In: 21st International Conference on Enterprise Information Systems, vol. 2, pp. 493–504. SciTePress (2019)

Bellomarini, L., Fakhoury, D., Gottlob, G., Sallinger, E.: Knowledge graphs and enterprise AI: the promise of an enabling technology. In: 35th IEEE International Conference on Data Engineering, pp. 26–37. IEEE (2019)

Bellomarini, L., Sallinger, E., Vahdati, S.: Chapter 2 Knowledge graphs: the layered perspective. In: Janev, V., Graux, D., Jabeen, H., Sallinger, E. (eds.) Knowledge Graphs and Big Data Processing. LNCS, vol. 12072, pp. 20–34. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-53199-7_2CrossRef

Bernasconi, A., Canakoglu, A., Ceri, S.: From a conceptual model to a knowledge graph for genomic datasets. In: Laender, A.H.F., Pernici, B., Lim, E.-P., de Oliveira, J.P.M. (eds.) ER 2019. LNCS, vol. 11788, pp. 352–360. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-33223-5_29CrossRef

Bork, D., et al.: Requirements engineering for model-based enterprise architecture management with ArchiMate. In: Pergl, R., Babkin, E., Lock, R., Malyzhenkov, P., Merunka, V. (eds.) EOMAS 2018. LNBIP, vol. 332, pp. 16–30. Springer, Cham (2018). https://doi.org/10.1007/978-3-030-00787-4_2CrossRef

Bork, D., Karagiannis, D., Pittl, B.: A survey of modeling language specification techniques. Inf. Syst. 87, 101425 (2020). https://doi.org/10.1016/j.is.2019.101425

10.

Buckl, S., Matthes, F., Schweda, C.M.: Classifying enterprise architecture analysis approaches. In: Poler, R., van Sinderen, M., Sanchis, R. (eds.) IWEI 2009. LNBIP, vol. 38, pp. 66–79. Springer, Heidelberg (2009). https://doi.org/10.1007/978-3-642-04750-3_6CrossRef

11.

Burgueño, L., Kessentini, M., Wimmer, M., Zschaler, S.: 3rd workshop on artificial intelligence and model-driven engineering. In: International Conference on Model Driven Engineering Languages and Systems Companion, pp. 148–149 (2021)

12.

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). https://doi.org/10.1007/978-3-642-29749-6_1CrossRef

13.

Buschle, M., Johnson, P., Shahzad, K.: The enterprise architecture analysis tool - support for the predictive, probabilistic architecture modeling framework, pp. 3350–3364 (2013)

14.

Caetano, A., et al.: Representation and analysis of enterprise models with semantic techniques: an application to archimate, e3value and business model canvas. Knowl. Inf. Syst. 50(1), 315–346 (2017)CrossRef

15.

Chen, X., Jia, S., Xiang, Y.: A review: knowledge reasoning over knowledge graph. Expert Syst. Appl. 141, 112948 (2020)

16.

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_33CrossRef

17.

Dehmer, M., Emmert-Streib, F., Shi, Y.: Quantitative graph theory: a new branch of graph theory and network science. Inf. Sci. 418–419, 575–580 (2017)CrossRef

18.

Di Rocco, J., Di Sipio, C., Di Ruscio, D., Nguyen, P.T.: A GNN-based recommender system to assist the specification of metamodels and models. In: International Conference on Model Driven Engineering Languages and Systems (MODELS), pp. 70–81 (2021)

19.

Florez, H., Sánchez, M., Villalobos, J.: A catalog of automated analysis methods for enterprise models. Springerplus 5(1), 1–24 (2016). https://doi.org/10.1186/s40064-016-2032-9CrossRef

20.

Fowler, M.: Refactoring: Improving the Design of Existing Code. Addison-Wesley Professional, Boston (2018)

21.

Frank, U., Strecker, S., Fettke, P., vom Brocke, J., Becker, J., Sinz, E.J.: The research field “modeling business information systems’’ - current challenges and elements of a future research agenda. Bus. Inf. Syst. Eng. 6(1), 39–43 (2014)CrossRef

22.

Franke, U., Holschke, O., Buschle, M., Narman, P., Rake-Revelant, J.: It consolidation: an optimization approach. In: International Enterprise Distributed Object Computing Conference Workshops, pp. 21–26 (2010)

23.

Giakoumakis, V., Krob, D., Liberti, L., Roda, F.: Technological architecture evolutions of information systems: trade-off and optimization. Concurr. Eng. 20(2), 127–147 (2012)CrossRef

24.

Glaser, P.L., Ali, S.J., Sallinger, E., Bork, D.: Exploring enterprise architecture knowledge graphs in Archi: the EAKG toolkit (2022). Under review

25.

Hacks, S., Höfert, H., Salentin, J., Yeong, Y.C., Lichter, H.: Towards the definition of enterprise architecture debts. In: 2019 IEEE 23rd International Enterprise Distributed Object Computing Workshop (EDOCW), pp. 9–16. IEEE (2019)

26.

Hacks, S., Lichter, H.: A probabilistic enterprise architecture model evolution. In: International Enterprise Distributed Object Computing Conference, pp. 51–57 (2018)

27.

Hevner, A.R., March, S.T., Park, J., Ram, S.: Design science in information systems research. MIS Q. 28(1), 75–105 (2004)CrossRef

28.

Höfferer, P.: Achieving business process model interoperability using metamodels and ontologies. In: Österle, H., Schelp, J., Winter, R. (eds.) European Conference on Information Systems, ECIS 2007, pp. 1620–1631 (2007)

29.

Holschke, O., Närman, P., Flores, W.R., Eriksson, E., Schönherr, M.: Using enterprise architecture models and Bayesian belief networks for failure impact analysis. In: Feuerlicht, G., Lamersdorf, W. (eds.) ICSOC 2008. LNCS, vol. 5472, pp. 339–350. Springer, Heidelberg (2009). https://doi.org/10.1007/978-3-642-01247-1_35CrossRef

30.

Jonkers, H., Band, I., Quartel, D.: The ArchiSurance case study. The Open Group, pp. 1–32 (2012)

31.

Karagiannis, D., Buchmann, R.A.: Linked open models: extending linked open data with conceptual model information. Inf. Syst. 56, 174–197 (2016)CrossRef

32.

Lankhorst, M.M.: Enterprise Architecture at Work - Modelling, Communication and Analysis. The Enterprise Engineering Series, 2nd edn. Springer, Heidelberg (2009)

33.

Lantow, B., Jugel, D., Wißotzki, M., Lehmann, B., Zimmermann, O., Sandkuhl, K.: Towards a classification framework for approaches to enterprise architecture analysis. In: Horkoff, J., Jeusfeld, M.A., Persson, A. (eds.) PoEM 2016. LNBIP, vol. 267, pp. 335–343. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-48393-1_25CrossRef

34.

Maass, W., Storey, V.C.: Pairing conceptual modeling with machine learning. Data Knowl. Eng. 134, 101909 (2021)

35.

Maccormack, A.D., Lagerstrom, R., Baldwin, C.Y.: A methodology for operationalizing enterprise architecture and evaluating enterprise it flexibility. Harvard Business School Working Paper Series# 15-060 (2015)

36.

Medvedev, D., Shani, U., Dori, D.: Gaining insights into conceptual models: a graph-theoretic querying approach. Appl. Sci. 11(2), 765 (2021)CrossRef

37.

Naranjo, D., Sánchez, M., Villalobos, J.: PRIMROSe: a graph-based approach for enterprise architecture analysis. In: Cordeiro, J., Hammoudi, S., Maciaszek, L., Camp, O., Filipe, J. (eds.) ICEIS 2014. LNBIP, vol. 227, pp. 434–452. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-22348-3_24CrossRef

38.

Närman, P., Buschle, M., Ekstedt, M.: An enterprise architecture framework for multi-attribute information systems analysis. Softw. Syst. Model. 13(3), 1085–1116 (2012). https://doi.org/10.1007/s10270-012-0288-2CrossRef

39.

OMG: ArchiMate® 3.1 Specification. The Open Group (2019). https://pubs.opengroup.org/architecture/archimate3-doc/

40.

Pan, J.Z., Vetere, G., Gómez-Pérez, J.M., Wu, H. (eds.): Exploiting Linked Data and Knowledge Graphs in Large Organisations. Springer, Heidelberg (2017). https://doi.org/10.1007/978-3-319-45654-6CrossRef

41.

Pittl, B., Bork, D.: Modeling digital enterprise ecosystems with ArchiMate: a mobility provision case study. In: ICServ 2017. LNCS, vol. 10371, pp. 178–189. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-61240-9_17CrossRef

42.

Pittl, B., Fill, H.: Transforming enterprise models to linked data via semantic annotations. In: Schaefer, I., Karagiannis, D., Vogelsang, A., Méndez, D., Seidl, C. (eds.) Modellierung 2018. LNI, pp. 55–70. Gesellschaft für Informatik (2018)

43.

Plataniotis, G., de Kinderen, S., Proper, H.A.: Relating decisions in enterprise architecture using decision design graphs. In: 2013 17th IEEE International Enterprise Distributed Object Computing Conference, pp. 139–146. IEEE (2013)

44.

Reimer, U., Bork, D., Fettke, P., Tropmann-Frick, M.: Preface of the first workshop models in AI. In: Companion Proceedings of Modellierung 2020 Short, Workshop and Tools & Demo Papers, pp. 128–129. CEUR Workshop Proceedings (2020)

45.

Salentin, J., Hacks, S.: Towards a catalog of enterprise architecture smells. In: Gronau, N., Heine, M., Krasnova, H., Poustcchi, K. (eds.) Internationalen Tagung Wirtschaftsinformatik, Community Tracks, pp. 276–290. GITO Verlag (2020)

46.

Santana, A., Fischbach, K., de Moura, H.P.: Enterprise architecture analysis and network thinking: a literature review. In: Bui, T.X., Jr., R.H.S. (eds.) 49th Hawaii International Conference on System Sciences, pp. 4566–4575. IEEE (2016)

47.

Santana, A., Simon, D., Fischbach, K., de Moura, H.: Combining network measures and expert knowledge to analyze enterprise architecture at the component level. In: 2016 IEEE EDOC Conference, pp. 1–10. IEEE (2016)

48.

Simsek, U., et al.: Knowledge graph lifecycle: building and maintaining knowledge graphs (2021)

49.

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

50.

Smajevic, M., Bork, D.: Towards graph-based analysis of enterprise architecture models. In: Ghose, A., Horkoff, J., Silva Souza, V.E., Parsons, J., Evermann, J. (eds.) ER 2021. LNCS, vol. 13011, pp. 199–209. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-89022-3_17CrossRef

51.

Smajevic, M., Hacks, S., Bork, D.: Using knowledge graphs to detect enterprise architecture smells. In: Serral, E., Stirna, J., Ralyté, J., Grabis, J. (eds.) PoEM 2021. LNBIP, vol. 432, pp. 48–63. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-91279-6_4CrossRef

52.

Tong, Q., Zhang, F., Cheng, J.: Construction of RDF (S) from UML class diagrams. J. Comput. Inf. Technol. 22(4), 237–250 (2014)CrossRef

53.

Zhou, J., et al.: Graph neural networks: a review of methods and applications. AI Open 1, 57–81 (2020)CrossRef

54.

Zou, X.: A survey on application of knowledge graph. In: Journal of Physics: Conference Series, vol. 1487, p. 012016. IOP Publishing (2020)

Titel: Model-Based Construction of Enterprise Architecture Knowledge Graphs
verfasst von: Philipp-Lorenz Glaser
Syed Juned Ali
Emanuel Sallinger
Dominik Bork
Verlag: Springer International Publishing
Buch: Enterprise Design, Operations, and Computing
Print ISBN: 978-3-031-17603-6

Electronic ISBN: 978-3-031-17604-3

Copyright-Jahr: 2022
DOI: https://doi.org/10.1007/978-3-031-17604-3_4

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