Developing an Ontology for Business Process Management Techniques and Tools

Document Type : Original Article

Authors

1 Masters of Information Technology Management, Faculty of Social Sciences and Economics, Alzahra University, Tehran, Iran

2 Associate professor, Department of Management, Faculty of Social Sciences and Economics, Alzahra University, Tehran, Iran

3 Assistant Professor, Department of Computer Engineering and IT, Faculty of Computer Engineering, K.N.Toosi University of Technology, Tehran, Iran

4 Department of IT Management, Faculty of Management, Tehran University, Tehran, Iran

Abstract

In line with increasing attention to the scope of Business Process Management (BPM) over the past two decades, many techniques and tools have been introduced. Finding the proper technique and tool in each phase of the business process management life cycle takes time and effort. This study aims to design and develop an ontology to facilitate the selection of suitable techniques and tools at each step of the BPM life cycle. This ontology provides a common understanding of concepts of this domain for computers. The study results showed that two taxonomies for techniques and software tools for business process management were created based on BPM life cycle steps. Then, an ontology was developed for them. Noy & McGuinness methodology was applied to implement this ontology, and Protégé 5.2 and owl language were used. Also, the quality criteria-based approach was used for the evaluation of ontology. All the main concepts in the domain of BPM techniques and tools were extracted from previous studies. There are 298 terms. 58 of them are domain concepts or classes, 2 are about taxonomic relations, 2 are related to data property, and 224 are instances. This research used these terms, and the deployed ontology with the quality criteria-based approach was evaluated.

Keywords

Main Subjects


  • B. Lenat, and R. V. Guha, Building large knowledge-based systems; representation and inference in the Cyc project, Addison-Wesley Longman Publishing Co., Menlo Park, CA, 1989.
  • V.Brocke, M. and Rosemann, Handbook on business process management 1: Introduction, methods, and information systems, Springer, Heidelberg, 2015.
  • Fensel , Ontologies: Silver Bullet for Knowledge Management and Electronic Commerce, Berlin: Springer, 2001.
  • Dumas, M. La Rosa, J. Mendling, and H. A. Reijers, Fundamentals of Business Process Management, 2th ed, Berlin, Heidelberg: Springer, 2018. https://doi.org/10.1007/978-3-642-33143-5.
  • J. Kettinger, J. T. Teng, and S. Guha, "Business process change: a study of methodologies, techniques, and tools", MIS quarterly, vol. 21 no. 1, pp. 55–80, 1997. https://doi.org/10.2307/249742.
  • Harmon, and B. P. Trends, Business Process Change:A guide for business managers and BPM and Six Sigma professionals ,2th ed, Morgan Kaufmann, Burlington, MA, 2010.
  • Bozev, and S. Ivanov, CONTEMPORARY METHODS OF BUSINESS PROCESS MANAGEMENT (BPM), 2020. https://www.researchgate.net/profile/Sotir-Ivanov/publication/364843948.
  • Romero, W. Guédria, H. Panetto, and B. Barafort, A hybrid deep learning and ontology-driven approach to perform business process capability assessment. Journal of Industrial Information Integration, vol. 30, p. 100409, 2022. https://doi.org/10.1016/j.jii.2022.100409.
  • I. D. De Pádua, R. B. Junior, and E. L.Aredes, Contributions of business process management promotion techniques to knowledge management: Empirical evidence. Brazilian Journal of Operations & Production Management, vol. 17. no. 3, pp.1-13, 2020. https://doi.org/10.14488/10.14488/BJOPM.2020.034.
  • De Ramon Fernandez, D. Ruiz Fernandez, and Y. Sabuco Garcia, Business Process Management for optimizing clinical processes: A systematic literature review. Health informatics journal, vol. 26, no. 2, pp. 1305-1320, 2020. https://doi.org/10.1177/1460458219877092.
  • Corcho, A. and Gómez-Pérez "A Roadmap to Ontology Specification Languages", in Dieng R., Corby O. (Eds.), Knowledge Engineering and Knowledge Management Methods, Models, and Tools, EKAW 2000, Springer, Berlin, Heidelberg, 2000, pp.80–96. https://doi.org/10.1007/3-540-39967-4_7.
  • H. Thuan, H. A. Phuong, M. George, M. Nkhoma, and P. Antunes, Toward an Ontology for Improving Process Flexibility. In Future Data and Security Engineering: 7th International Conference, FDSE 2020, Quy Nhon, Vietnam, November 25–27, 2020, Proceedings 7. Springer International Publishing, 2020, pp. 411-428. https://doi.org/10.1007/978-3-030-63924-2_24.
  • Annane, N., Aussenac-Gilles, and M. Kamel, BBO: BPMN 2.0 based ontology for business process representation. In 20th European Conference on Knowledge Management (ECKM 2019), 2019, vol. 1, pp. 49-59. https://doi.org/10.34190/KM.19.113.
  • Studer, V. R., Benjamins, and D. Fensel, "Knowledge engineering: principles and methods", Data & knowledge engineering, vol. 25, no. 1-2, pp. 161-197, 1998. https://doi.org/10.1016/S0169-023X(97)00056-6.
  • Uschold, "Finding and Avoiding Bugs in Enterprise Ontologies", in Paulheim H., Lehmann J., Sv ́atek V., Knoblock C., Horridge M., Lambrix P., and Parsia B., (Eds), KNOW@ LOD/CoDeS @ ESWC, May 2016, pp.30, 2016.
  • Bartolini, A. Calabró, and E. Marchetti, Enhancing Business Process Modelling with Data Protection Compliance: An Ontology-based Proposal. In ICISSP, 2019, pp. 421-428. https://doi.org/10.5220/0007392304210428.
  • Adams, A. V. Hense, and A. H. T. Hofstede, Extensible ontology-based views for business process models. Knowledge and Information Systems, vol. 63, pp. 2763-2789, 2021. https://doi.org/10.1007/s10115-021-01604-1.
  • Lila Rao and Kweku-Muata Osei-Bryson. 2007. Towards defining dimensions of knowledge systems quality. Expert Systems with Applications 33, 2 , 368–378
  • F. López, A. Gómez-Pérez, J. P. Sierra, and A. P. Sierra, "Building a chemical ontology using methontology and the ontology design environment". IEEE Intelligent Systems and their applications, vol. 14, no.1, pp. 37-46, 1999. https://doi.org/10.1109/5254.747904.
  • Song, J. Vanthienen, W. Cui, Y. Wang, and L. Huang, Context-aware BPM using IoT-integrated context ontologies and IoT-enhanced decision models. In 2019 IEEE 21st Conference on Business Informatics (CBI), vol. 1, pp. 541-550, IEEE, 2019. https://doi.org/10.1109/CBI.2019.00069.
  • Von Rosing, W. Laurier, and S. Polovina, "The BPM ontology", in The complete business process handbook, Elsevier, Waltham, 2015, pp. 101–121.
  • Macedo de Morais, S. Kazan, S. Inês Dallavalle de Pádua, and A. Lucirton Costa, "An analysis of BPM lifecycles: from a literature review to a framework proposal", Business Process Management Journal, vol. 20 no. 3, pp. 412-432, 2014. https://doi.org/10.1108/BPMJ-03-2013-0035.
  • Synak M. Dabrowski and S. R. Kruk "Semantic Web and Ontologies", in: Kruk S.R. and McDaniel B. (Eds) Semantic Digital Libraries. Springer, Berlin, Heidelberg, 2009, pp. 41-54.
  • Horridge, S. Jupp, G. Moulton, A. Rector, R. Stevens, and C. Wroe, "A Practical Guide to Building OWL Ontologies Using Protégé 4 and CO-ODE Tools Edition 1.2", The university of Manchester, 107, 2009. https://2018.aulaweb.unige.it/pluginfile.php/109811/mod_label/intro/ProtegeOWLTutorialP4_v1_3.pdf.
  • Palvia, and J. T. Nosek, "A field examination of system life cycle techniques and methodologies", Information & Management, vol. 25 no. 2, pp. 73-84, 1993. https://doi.org/10.1016/0378-7206(93)90049-Y.
  • Brank, M., Grobelnik, and D. Mladenic, "A survey of ontology evaluation techniques", in Proceedings of the conference on data mining and data warehouses (SiKDD 2005), Citeseer Ljubljana, Slovenia. October 2005, pp. 166-170.
  • Zuhaira, and N. Ahmad, Business process modeling, implementation, analysis, and management: the case of business process management tools. Business Process Management Journal, vol. 27, no. 1, pp. 145-183, 2021. https://doi.org/10.1108/BPMJ-06-2018-0168.
  • Lila Rao and Kweku-Muata Osei-Bryson. 2007. Towards defining dimensions of knowledge systems quality. Expert Systems with Applications 33, 2 , 368–378
  • McDaniel, M., & Storey, V. C. (2019). Evaluating domain ontologies: clarification, classification, and challenges. ACM Computing Surveys (CSUR), 52(4), 1-44.
  • Bucher, and R. Winter, “Taxonomy of business process management approaches”,in vom Brocke, J. and Rosemann, M. (Eds), Handbook on Business Process Management,Vol. 2, Springer, New York, NY, 2010. https://doi.org/10.1007/978-3-642-01982-1_5.
  • Giaglis, "A taxonomy of business process modeling and information systems modeling techniques", International Journal of Flexible Manufacturing, vol, 13, no. 2, pp. 209–228, 2001. https://doi.org/10.1023/A:1011139719773.
  • Hashemi, P., Khadivar, A., & Shamizanjani, M. (2018). Developing a domain ontology for knowledge management technologies. Online Information Review, 42(1), 28-44.
  • Hashemi, P., khadivar, A., & ShamiZanjani, M. (2018). Developing Process-based Ontology for Knowledge Management Technologies. Iranian Journal of Information Processing and Management, 33(3), 1141-1164. doi: 10.35050/JIPM010.2018.044

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