Abstract
The widespread adoption of Information Technology systems and their capability to trace data about process executions has made available Information Technology data for the analysis of process executions. Meanwhile, at business level, static and procedural knowledge, which can be exploited to analyze and reason on data, is often available. In this paper we aim at providing an approach that, combining static and procedural aspects, business and data levels and exploiting semantic-based techniques allows business analysts to infer knowledge and use it to analyze system executions. The proposed solution has been implemented using current scalable Semantic Web technologies, that offer the possibility to keep the advantages of semantic-based reasoning with non-trivial quantities of data.
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
This work is supported by “ProMo - A Collaborative Agile Approach to Model and Monitor Service-Based Business Processes”, funded by the Operational Programme “Fondo Europeo di Sviluppo Regionale (FESR) 2007-2013 of the Province of Trento, Italy.
Download to read the full chapter text
Chapter PDF
References
Weber, I., Hoffmann, J., Mendling, J.: Semantic business process validation. In: Proc. of Semantic Business Process and Product Lifecycle Management workshop (SBPM) (2008)
Wong, P.Y., Gibbons, J.: A relative timed semantics for BPMN. Electronic Notes in Theoretical Computer Science 229(2), 59–75 (2009); Proc. of 7th Int. Workshop on the Foundations of Coordination Languages and Software Architectures (FOCLASA 2008)
Koschmider, A., Oberweis, A.: Ontology based business process description. In: Proceedings of the CAiSE 2005 Workshops. LNCS, pp. 321–333. Springer (2005)
Dimitrov, M., Simov, A., Stein, S., Konstantinov, M.: A BPMO based semantic business process modelling environment. In: Proc. of SBPLM at ESWC. CEUR-WS (2007)
Thomas, O., Fellmann, M.: Semantic EPC: Enhancing process modeling using ontology languages. In: Proc. of Semantic Business Process and Product Lifecycle Management workshop (SBPM), pp. 64–75 (2007)
Di Francescomarino, C., Ghidini, C., Rospocher, M., Serafini, L., Tonella, P.: Reasoning on semantically annotated processes. In: Bouguettaya, A., Krueger, I., Margaria, T. (eds.) ICSOC 2008. LNCS, vol. 5364, pp. 132–146. Springer, Heidelberg (2008)
Tomasi, A., Marchetto, A., Di Francescomarino, C., Susi, A.: reBPMN: Recovering and reducing business processes. In: ICSM, pp. 666–669 (2012)
Pedrinaci, C., Lambert, D., Wetzstein, B., van Lessen, T., Cekov, L., Dimitrov, M.: SENTINEL: A semantic business process monitoring tool. In: Proc. of Ontology-supported Business Intelligence (OBI), pp. 1:1–1:12. ACM (2008)
Di Francescomarino, C., Ghidini, C., Rospocher, M., Serafini, L., Tonella, P.: Semantically-aided business process modeling. In: Bernstein, A., Karger, D.R., Heath, T., Feigenbaum, L., Maynard, D., Motta, E., Thirunarayan, K. (eds.) ISWC 2009. LNCS, vol. 5823, pp. 114–129. Springer, Heidelberg (2009)
Object Management Group (OMG): Business process model and notation (BPMN) version 2.0. Standard (2011)
Bertoli, P., Kazhamiakin, R., Nori, M., Pistore, M.: SMART: Modeling and monitoring support for business process coordination in dynamic environments. In: Abramowicz, W., Domingue, J., Węcel, K. (eds.) BIS Workshops 2012. LNBIP, vol. 127, pp. 243–254. Springer, Heidelberg (2012)
de Leoni, M., Maggi, F.M., van der Aalst, W.M.P.: Aligning event logs and declarative process models for conformance checking. In: Barros, A., Gal, A., Kindler, E. (eds.) BPM 2012. LNCS, vol. 7481, pp. 82–97. Springer, Heidelberg (2012)
Business Process Management Initiative (BPMI): Business process modeling notation: Specification (2006), http://www.bpmn.org
Seaborne, A., Harris, S.: SPARQL 1.1 Query Language. Recommendation, W3C (2013)
Hepp, M., Roman, D.: An ontology framework for semantic business process management. In: Wirtschaftsinformatik (1), Universitaetsverlag Karlsruhe, pp. 423–440 (2007)
Pedrinaci, C., Domingue, J., Alves de Medeiros, A.K.: A core ontology for business process analysis. In: Bechhofer, S., Hauswirth, M., Hoffmann, J., Koubarakis, M. (eds.) ESWC 2008. LNCS, vol. 5021, pp. 49–64. Springer, Heidelberg (2008)
Sahoo, S., Lebo, T., McGuinness, D.: PROV-O: The PROV ontology. Recommendation, W3C (2013)
Calvanese, D., De Giacomo, G., Lembo, D., Lenzerini, M., Poggi, A., Rodriguez-Muro, M., Rosati, R., Ruzzi, M., Savo, D.F.: The MASTRO system for ontology-based data access. Semant. Web 2(1), 43–53 (2011)
Calvanese, D., De Giacomo, G., Lembo, D., Lenzerini, M., Rosati, R.: Conceptual modeling for data integration. In: Borgida, A.T., Chaudhri, V.K., Giorgini, P., Yu, E.S. (eds.) Mylopoulos Festschrift. LNCS, vol. 5600, pp. 173–197. Springer, Heidelberg (2009)
Rodriguez-Muro, M., Calvanese, D.: Quest, an OWL 2 QL reasoner for ontology-based data access. In: OWLED, vol. 849. CEUR-WS.org (2012)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Di Francescomarino, C. et al. (2014). Semantic-Based Process Analysis. In: Mika, P., et al. The Semantic Web – ISWC 2014. ISWC 2014. Lecture Notes in Computer Science, vol 8797. Springer, Cham. https://doi.org/10.1007/978-3-319-11915-1_15
Download citation
DOI: https://doi.org/10.1007/978-3-319-11915-1_15
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-11914-4
Online ISBN: 978-3-319-11915-1
eBook Packages: Computer ScienceComputer Science (R0)