W. V. Der-aalst, Process Mining: Discovery, Conformance and Enhancement of Business Processes, 2011.

M. Dumas, M. L. Rosa, J. Mendling, and H. Reijers, Fundamentals of Business Process Management, 2013.

M. Laguna and J. Marklund, Business Process Modeling, Simulation and Design, Second Edition, 2013.

C. Surajit, D. Umeshwar, and N. Vivek, An overview of business intelligence technology, Commun. ACM, vol.54, issue.8, pp.88-98, 2011.

K. Vergidis, B. , and A. T. , Business process improvement using multi-objective optimisation, BT Technology Journal, vol.45, issue.s9and10, pp.229-235, 2006.
DOI : 10.1007/s10550-006-0065-2

A. Van-der, Business Process Management: A Comprehensive Survey, ISRN Software Engineering, vol.38, issue.11, p.2013, 2013.
DOI : 10.1145/219717.219748

A. Van-der and M. Wil, Business Process Management: A Comprehensive Survey, ISRN Software Engineering, vol.38, issue.11, p.2013, 2013.
DOI : 10.1145/219717.219748

C. Ellis, Information control nets: a mathematical model of office information flow, Proceedings of the Conference on Simulation, pp.225-240, 1979.

M. Röglinger, J. Pöppelbuß, and J. Becker, Maturity models in business process management, Business Process Management Journal, vol.18, issue.2, pp.328-346, 2012.
DOI : 10.1108/14637151111122329

F. Arigliano, A. Azzini, C. Braghin, A. Caforio, P. Ceravolo et al., Knowledge and business intelligence technologies in cross-enterprise environments for italian advanced mechanical industry, Proceedings of the 3rd International Symposium on Data-driven Process Discovery and Analysis Riva del Garda (TN), CEUR-WS.org, pp.104-110, 2013.

A. Colombo, E. Damiani, F. Frati, S. Oltolina, K. Reed et al., The Use of a Meta-Model to Support Multi-Project Process Measurement, 2008 15th Asia-Pacific Software Engineering Conference, pp.503-510, 2008.
DOI : 10.1109/APSEC.2008.55

C. L. Clair, A. Cullen, and J. Keenan, Use a metrics framework to drive bpm excellence, p.82161, 2012.

A. Azzini and P. Ceravolo, Consistent Process Mining over Big Data Triple Stores, 2013 IEEE International Congress on Big Data, 2013.
DOI : 10.1109/BigData.Congress.2013.17

J. Buijs, Mapping data sources to xes in a generic way, master's thesis, 2010.

T. Baier and J. Mendling, Bridging Abstraction Layers in Process Mining by Automated Matching of Events and Activities, Lecture Notes in Computer Science, vol.8094, pp.17-32, 2013.
DOI : 10.1007/978-3-642-40176-3_4

T. Kehrer, U. Kelter, and G. Taentzer, A rule-based approach to the semantic lifting of model differences in the context of model versioning, 2011 26th IEEE/ACM International Conference on Automated Software Engineering (ASE 2011), pp.163-172, 2011.
DOI : 10.1109/ASE.2011.6100050

A. D. Nicola, T. D. Mascio, M. Lezoche, and F. Tagliano, Semantic Lifting of Business Process Models, 2008 12th Enterprise Distributed Object Computing Conference Workshops, pp.120-126, 2008.
DOI : 10.1109/EDOCW.2008.55
URL : https://hal.archives-ouvertes.fr/hal-00656690

W. V. Aalst, Process Mining: Discovery, Conformance and Enhancement of Business Processes, 2011.

M. Papazoglou and W. V. Heuvel, Business process development life cycle methodology, Communications of the ACM, vol.50, issue.10, pp.79-85, 2007.
DOI : 10.1145/1290958.1290966

F. M. Maggi, C. D. Francescomarino, M. Dumas, and C. Ghidini, Predictive Monitoring of Business Processes, CAiSE, pp.457-472, 2014.
DOI : 10.1007/978-3-319-07881-6_31

W. Van-der-aalst, M. Schonenberg, and M. Song, Time prediction based on process mining, Special Issue: Semantic Integration of Data, Multimedia, and Services, pp.450-475, 2011.
DOI : 10.1016/j.is.2010.09.001

D. Ruta and B. Majeed, Business process forecasting in telecom industry, 2011 IEEE GCC Conference and Exhibition (GCC), pp.389-392, 2011.
DOI : 10.1109/IEEEGCC.2011.5752543

B. Kang, D. Kim, and S. H. Kang, Real-time business process monitoring method for prediction of abnormal termination using KNNI-based LOF prediction, Expert Systems with Applications, vol.39, issue.5
DOI : 10.1016/j.eswa.2011.12.007

F. Folino, M. Guarascio, and L. Pontieri, Discovering Context-Aware Models for Predicting Business Process Performances, On the Move to Meaningful Internet Systems: OTM 2012, pp.287-304, 2012.
DOI : 10.1007/978-3-642-33606-5_18

S. Suriadi, C. Ouyang, W. M. Van-der-aalst, and A. H. Ter-hofstede, Root Cause Analysis with Enriched Process Logs, Business Process Management Workshops, pp.174-186, 2013.
DOI : 10.1007/978-3-642-36285-9_18

M. Li, L. Liu, L. Yin, and Y. Zhu, A process mining based approach to knowledge maintenance, Information Systems Frontiers, vol.31, issue.1, pp.371-380, 2011.
DOI : 10.1016/j.eswa.2005.09.003

P. Hayes and B. Mcbride, Resource description framework (rdf), 2004.

J. Carroll, C. Bizer, P. Hayes, and P. Stickler, Named graphs, Web Semantics: Science, Services and Agents on the World Wide Web, vol.3, issue.4, 2005.
DOI : 10.1016/j.websem.2005.09.001

P. Prud´hommeaux, E. Seaborne, and A. , Sparql query language for rdf, 2008.

M. Leida, B. Majeed, M. Colombo, and A. Chu, Lightweight rdf data model for business processes analysis. Data-Driven Process Discovery and Analysis Series, Lecture Notes in Business Information Processing, vol.116, 2012.
DOI : 10.1007/978-3-642-40919-6_1
URL : https://link.springer.com/content/pdf/10.1007%2F978-3-642-40919-6_1.pdf

D. Parmenter, Key performance indicators (KPI): developing, implementing, and using winning KPIs, 2010.
DOI : 10.1002/9781119019855

R. Richardson and C. S. Director, Csi computer crime and security survey, Computer Security Institute, 2008.

. Van-der-aalst, T. W. Wil, and L. Maruster, Workflow mining: discovering process models from event logs, IEEE Transactions on Knowledge and Data Engineering, vol.16, issue.9, pp.1128-1142, 2004.
DOI : 10.1109/TKDE.2004.47

W. Van-der-aalst and K. Van-hee, Workflow management: models, methods, and systems, 2004.

W. M. Van-der-aalst, B. F. Van-dongen, J. Herbst, L. Maruster, G. Schimm et al., Workflow mining: A survey of issues and approaches, Data & Knowledge Engineering, vol.47, issue.2, pp.237-267, 2003.
DOI : 10.1016/S0169-023X(03)00066-1

P. Smyth and R. M. Goodman, Rule induction using information theory. Knowledge discovery in databases, 1991.

M. Hert, G. Reif, and H. C. Gall, A comparison of RDB-to-RDF mapping languages, Proceedings of the 7th International Conference on Semantic Systems, I-Semantics '11, pp.25-32, 2011.
DOI : 10.1145/2063518.2063522