Abstract
To tackle the problem of low-efficiency integration of heterogeneous data from various legacy ERP systems, a data integration approach based on ontology learning are presented. Considering the unavailability of database interface and diversity of DBMS and naming conventions of legacy information systems, a data integration framework for legacy ERP systems based on ontology learning from structured query language (SQL) scripts (RDB) are proposed. The key steps and technicality of the proposed framework and the process of ontology-based semantic integration are depicted.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Lenart, A.: ERP in the cloud – benefits and challenges. In: Wrycza, S. (ed.) SIGSAND/PLAIS 2011. LNBIP, vol. 93, pp. 39–50. Springer, Heidelberg (2011). https://doi.org/10.1007/978-3-642-25676-9_4
Nofal, M.I., Zawiyah, M.Y.: Integration of business intelligence and enterprise resource planning within organizations. Procedia Technol. 11, 658–665 (2013). https://doi.org/10.1016/j.protcy.2013.12.242
Serrano, N., Hernantes, J., Gallardo, G.: Service-oriented architecture and legacy systems. IEEE Softw. 31(5), 15–19 (2014). https://doi.org/10.1109/MS.2014.125
Ahmad, M.M., Ruben, P.C.: Critical success factors for ERP implementation in SMEs. Robot. Comput. Integr. Manuf. 29(3), 104–111 (2013). https://doi.org/10.1016/j.ijinfomgt.2009.03.001
Malhotra, R., Cecilia, T.: Critical Decisions for ERP Integration: small business issues. Int. J. Inf. Manage. 30(1), 28–37 (2010)
Singh, R., Singh, K.: A descriptive classification of causes of data quality problems in data warehousing. Int. J. Comput. Sci. Issues 7(3), 41–50 (2010)
Pérez-Castillo, R., De Guzman, I.G.R., Piattini, M.: Knowledge discovery metamodel-ISO/IEC 19506: a standard to modernize legacy systems. Comput. Stand. Interfaces 33(6), 519–532 (2011). https://doi.org/10.1016/j.csi.2011.02.007
Millham, R., Yang, H.: Industrial report: data reengineering of COBOL sequential legacy systems. In: Proceedings of 33rd Annual IEEE International Computer Software and Applications Conference, vol. 1, pp. 646–647. IEEE, Seattle (2009)
Calvanese, D., Kalayci, T.E., Montali, M., Tinella, S.: Ontology-based data access for extracting event logs from legacy data: the onprom tool and methodology. In: Abramowicz, W. (ed.) BIS 2017. LNBIP, vol. 288, pp. 220–236. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-59336-4_16
Yano, K., Matsuo, A.: Data access visualization for legacy application maintenance. In: Proceedings of 24th IEEE International Conference on Software Analysis, pp. 546–550. IEEE, Klagenfurt (2017). https://doi.org/10.1109/SANER.2017.7884671
Ilya, S., Dmitry, M.: Semi-automated integration of legacy systems using linked data. In: Proceedings of 4th International Conference on Analysis of Images, Social Networks and Texts, pp. 166–171. Ural Federal University, Yekaterinburg (2015)
Kalsing, A.C., do Nascimento, G.S., Iochpe, C., et al.: An incremental process mining approach to extract knowledge from legacy systems. In: Proceedings of 14th IEEE International Enterprise Distributed Object Computing Conference, pp. 79–88. IEEE, Vitoria (2010). https://doi.org/10.1109/EDOC.2010.13
Pérez-Castillo, R., Weber, B., de Guzman, et al.: Process mining through dynamic analysis for modernising legacy systems. IET Softw. 5(3), 304–319 (2011). https://doi.org/10.1049/iet-sen.2010.0103
Sartipi, K., Safyallah, H.: Dynamic knowledge extraction from software systems using sequential pattern mining. Int. J. Softw. Eng. Knowl. Eng. 20(6), 761–782 (2010). https://doi.org/10.1142/S021819401000492X
Santoso, H.A., Haw, S.C., Abdul-Mehdi, Z.T.: Ontology extraction from relational database: concept hierarchy as background knowledge. Knowl. Based Syst. 24(3), 457–464 (2011). https://doi.org/10.1016/j.knosys.2010.11.003
Gardner, S.P.: Ontologies and semantic data integration. Drug Discov. Today 10(14), 1001–1007 (2005)
Calhau, R.F., De Almeida Falbo, R.: An ontology-based approach for semantic integration. In: Proceedings of 14th IEEE International Enterprise Distributed Object Computing Workshop, pp. 111–120. IEEE, Vitoria (2010). https://doi.org/10.1109/EDOC.2010.32
Yaguinuma, C.A., Afonso, G.F., Ferraz, V., Borges, S., et al.: A fuzzy ontology-based semantic data integration system. J. Inf. Knowl. Manag. 10(3), 285–299 (2011). https://doi.org/10.1109/IRI.2010.5558938
Correndo, G., Salvadores, M., Millard, I., Glaser, H.: SPARQL query rewriting for implementing data integration over linked data. In: Proceedings of 2010 EDBT/Workshops, pp. 1–11. ACM, Lausanne. https://doi.org/10.1145/1754239.1754244
Li, Y.F., Kennedy, G., Ngoran, F., et al.: An ontology-centric architecture for extensible scientific data management systems. Future Gener. Comput. Syst. 29(2), 641–653 (2013). https://doi.org/10.1016/j.future.2011.06.007
Acknowledgment
This work was supported by grants of the European Union co-financed by the European Social Fund (EFOP-3.6.3-VEKOP-16-2017-00002) and the China Scholarship Council (201808610145).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Ma, C. (2019). Data Integration of Legacy ERP System Based on Ontology Learning from SQL Scripts. In: Welzer, T., et al. New Trends in Databases and Information Systems. ADBIS 2019. Communications in Computer and Information Science, vol 1064. Springer, Cham. https://doi.org/10.1007/978-3-030-30278-8_52
Download citation
DOI: https://doi.org/10.1007/978-3-030-30278-8_52
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-30277-1
Online ISBN: 978-3-030-30278-8
eBook Packages: Computer ScienceComputer Science (R0)