VTMine for Visio: A Graphical Tool for Modeling in Process Mining
Process-aware information systems (PAISs) is a special class of information systems intended to support the tasks of initialization, end-to-end management, and completion of business processes. During their operation such systems accumulate a large amount of data that are stored in the form of event...
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| Published in | Automatic control and computer sciences Vol. 55; no. 7; pp. 847 - 865 |
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| Main Author | |
| Format | Journal Article |
| Language | English |
| Published |
Moscow
Pleiades Publishing
01.12.2021
Springer Nature B.V |
| Subjects | |
| Online Access | Get full text |
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| Abstract | Process-aware information systems (PAISs) is a special class of information systems intended to support the tasks of initialization, end-to-end management, and completion of business processes. During their operation such systems accumulate a large amount of data that are stored in the form of event logs. Event logs are a valuable source of knowledge about the actual behavior of a system. For example, they include (i) information about the discrepancy between the real and prescribed behavior of the system, (ii) information for identifying the bottlenecks and performance issues, and (iii) information for detecting the antipatterns of building a business system. These problems are studied in the discipline called process mining. The practical application of the process mining methods and practices is carried out using specialized software for data analysts. The subject area of the process analysis involves the work of an analyst with a large number of graphical models. Such work can be more efficiently with a convenient graphical modeling tool. This paper discusses the principles of designing a graphical tool VTMine for Visio for process modeling, based on the widespread application Microsoft Visio for business intelligence. The features of the architecture design of the software extension for application in the process mining area are presented along with the features of integration with existing libraries and tools for working with data. The usage of the developed tool for solving various types of tasks in modeling and analysis of processes is demonstrated on a set of experimental schemes. |
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| AbstractList | Process-aware information systems (PAISs) is a special class of information systems intended to support the tasks of initialization, end-to-end management, and completion of business processes. During their operation such systems accumulate a large amount of data that are stored in the form of event logs. Event logs are a valuable source of knowledge about the actual behavior of a system. For example, they include (i) information about the discrepancy between the real and prescribed behavior of the system, (ii) information for identifying the bottlenecks and performance issues, and (iii) information for detecting the antipatterns of building a business system. These problems are studied in the discipline called process mining. The practical application of the process mining methods and practices is carried out using specialized software for data analysts. The subject area of the process analysis involves the work of an analyst with a large number of graphical models. Such work can be more efficiently with a convenient graphical modeling tool. This paper discusses the principles of designing a graphical tool VTMine for Visio for process modeling, based on the widespread application Microsoft Visio for business intelligence. The features of the architecture design of the software extension for application in the process mining area are presented along with the features of integration with existing libraries and tools for working with data. The usage of the developed tool for solving various types of tasks in modeling and analysis of processes is demonstrated on a set of experimental schemes. Process-aware information systems (PAISs) is a special class of information systems intended to support the tasks of initialization, end-to-end management, and completion of business processes. During their operation such systems accumulate a large amount of data that are stored in the form of event logs. Event logs are a valuable source of knowledge about the actual behavior of a system. For example, they include (i) information about the discrepancy between the real and prescribed behavior of the system, (ii) information for identifying the bottlenecks and performance issues, and (iii) information for detecting the antipatterns of building a business system. These problems are studied in the discipline called process mining. The practical application of the process mining methods and practices is carried out using specialized software for data analysts. The subject area of the process analysis involves the work of an analyst with a large number of graphical models. Such work can be more efficiently with a convenient graphical modeling tool. This paper discusses the principles of designing a graphical tool VTMine for Visio for process modeling, based on the widespread application Microsoft Visio for business intelligence. The features of the architecture design of the software extension for application in the process mining area are presented along with the features of integration with existing libraries and tools for working with data. The usage of the developed tool for solving various types of tasks in modeling and analysis of processes is demonstrated on a set of experimental schemes. |
| Author | Shershakov, S. A. |
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| Copyright | Allerton Press, Inc. 2021. ISSN 0146-4116, Automatic Control and Computer Sciences, 2021, Vol. 55, No. 7, pp. 847–865. © Allerton Press, Inc., 2021. Russian Text © The Author(s), 2020, published in Modelirovanie i Analiz Informatsionnykh Sistem, 2020, No. 2, pp. 208–231. |
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| References | Carmona, J., Cortadella, J., and Kishinevsky, M., Genet: A tool for the synthesis and mining of Petri nets, in Ninth Int. Conf. on Application of Concurrency to System Design, Augsburg, Germany, 2009, IEEE, 2009, pp. 181–185. https://doi.org/10.1109/ACSD.2009.6 ReisigW.Understanding Petri Nets: Modeling Techniques, Analysis Methods, Case Studies2013BerlinSpringer10.1007/978-3-642-33278-41278.68222 Mans, R.S., van der Aalst, W.M.P., Vanwersch, R.J.B., and Moleman, A.J., Process mining in healthcare: Data challenges when answering frequently posed questions, in Process Support and Knowledge Representation in Health Care. ProHealth 2012, KR4HC 2012, Lenz, R., Miksch, S., Peleg, M. Reichert, M., Riaño, D., and ten Teije, A., Eds., Lecture Notes in Computer Science, vol. 7738, Berlin: Springer, 2013, pp. 140–153. https://doi.org/10.1007/978-3-642-36438-9_10. Shershakov, S.A., DPMine/P: modeling and process mining language and ProM plug-ins, in Proc. 9th Central & Eastern European Software Engineering Conf. in Russia, Moscow, 2013, New York: Association for Computing Machinery, 2013, p. 2. https://doi.org/10.1145/2556610.2556622 Janssenswillen, G. and Depaire, B., bupaR: Business process analysis in R, in Proc. BPM Demo Track and BPM Dissertation Award Co-Located with 15th Int. Conf. on Business Process Management (BPM 2017), Barcelona, 2017, Clarisó, R., Leopold, H., Mendling, J., van der Aalst, W., Kumar, A., Pentland, B., and Weske, M., Eds., CEUR Workshop Proceedings, 2017, vol. 1920. CortadellaJ.KishinevskyM.LavagnoL.YakovlevA.Deriving Petri nets from finite transition systemsIEEE Trans. Comput.199847859882164538610.1109/12.7075871392.68291 Shershakov, S.A., Multi-perspective process mining with embedding configurations into DB-based event logs, in Tools and Methods of Program Analysis. TMPA 2019, Kalenkova, A., Lozano, J.A., and Yavorskiy, R., Eds., Communications in Computer and Information Science, vol. 1288, Cham: Springer, 2021, pp. 68–80. https://doi.org/10.1007/978-3-030-71472-7_5 Van der AalstW.M.P.Process Mining: Discovery, Conformance and Enhancement of Business Processes2011BerlinSpringer-Verlag10.1007/978-3-642-19345-31216.68016 Rubin, V., Lomazova, I., and van der Aalst, W.M.P., Agile development with software process mining, in Proc. 2014 Int. Conf. on Software and System Process, Nanjing, China, 2014, New York: Association for Computing Machinery, 2014, pp. 70–74. https://doi.org/10.1145/2600821.2600842 ÇelikU.AkçetinE.Process mining tools comparisonOnline Acad. J. Inf. Technol.201899710410.5824/1309-1581.2018.4.007.x Celonis. www.celonis.com. DPModel official website. https://prj.xiart.ru/projects/dpmodel. Kebede, M., Comparative evaluation of process mining tools, Master’s Thesis, Tartu: Univ. of Tartu, 2015. Cortadella, J., Kishinevsky, M., Kondratyev, A., and Lavagno, L., Introduction to asynchronous circuitdesign: specification and synthesis (tutorial), in Proc. 6th Int. Symp. on Advanced Research in Asynchronous Circuits and Systems, Eilat, Israel, 2000. Van der AalstW.M.P.RubinV.VerbeekH.M.W.van DongenB.F.KindlerE.GüntherC.W.Process mining: a two-step approach to balance between underfitting and overfittingSoftware Syst. Mod.201098710.1007/s10270-008-0106-z DijkstraE.W.Cooperating Sequential Processes1965EindhovenTechnological Univ. Fluxicon. http://.uxicon.com/disco. ShershakovS.A.Enhancing efficiency of process mining algorithms with a tailored library design principles and performance assessment: Technical report2018MoscowHSE Univ.10.13140/RG.2.2.18320.46084 Solé, M. and Carmona, J., Rbminer: A tool for discovering Petri nets from transition systems, in Automated Technology for Verification and Analysis. ATVA 2010, Boujjani, A. and Chin, W.N., Eds., Lecture Notes in Computer Science, vol. 6252, Berlin: Springer, 2010. https://doi.org/10.1007/978-3-642-15643-4_33 Visio documentation. https://docs.microsoft.com/en-us/office/dev/add-ins/visio/. Rubin, V.A., Mitsyuk, A.A., Lomazova, I.A., and van der Aalst, W.M.P., Process Mining can be applied to software too!, Proc. 8th ACM/IEEE Int. Symp. on Empirical Software Engineering and Measurement, Torino, Italy, 2014, New York: Association for Computing Machinery, 2014, p. 57. https://doi.org/10.1145/2652524.2652583 ShershakovS.A.DPMine graphical language for automation of experiments in process miningAutom. Control Comput. Sci.20165047748510.3103/S014641161607018X Berti, A., van Zelst, S.J., and van der Aalst, W., Process mining for python (PM4Py): Bridging the gap between process- and data science, 2019. arXiv:1905.06169 [cs.SE] VerbeekH.BuijsJ.van DongenB.van der AalstW.ProM 6: The process mining toolkit, in Proc. BPM Demonstation TrackCEUR Workshop Proc.20106153439 Minit. www.minit.io. Mistyuk, A., Kalenkova, A., Shershakov, S., and van der Aalst, W., Using process mining for the analysis of an e-trade system: A case study, Biznes-Inf., 2014, no. 3, pp. 15–27. KimP.BulanovO.ShershakovS.Proc. 8th Spring/Summer Young Researchers’ Colloquium on Software Engineering, SYRCoSE2014MoscowIvannikov Inst. Sist. Program., Russ. Acad. Sci Carmona Vargas, J. and Solé, M., PMLAB: An scripting environment for process mining, Proc. BPM Demo Sessions 2014: Co-Located with the 12th Int. Conf. on Business Process Management (BPM 2014), Eindhoven, The Netherlands, 2014, Haifa: CEUR-WS.org, 2014, pp. 16–20. http://hdl.handle.net/2117/26167. CortadellaJ.KishinevskyM.KondratyevA.LavagnoL.YakovlevA.Petrify: a tool for manipulating concurrent specifications and synthesis of asynchronous controllersIEICE Trans. Inf. Syst.1997E80-D315325 Visio website. https://products.office.com/en-us/visio/flowchart-software. Mans, R.S., van der Aalst, W.M.P., and Verbeek, H.M.W., Supporting process mining workflows with RapidProM, Proc. BPM Demo Sessions,2014, 2014, vol. 56. Mans, R.S., Schonenberg, M.H., Song, M., van der Aalst, W.M.P., and Bakker, P.J.M., Application of process mining in healthcare – A case study in a Dutch hospital, in Biomedical Engineering Systems and Technologies. BIOSTEC 2008, Fred, A., Filipe, J., and Gamboa, H., Eds., Communication in Computer and Information Science, vol. 25, Berlin: Springer, 2009, pp. 425–438. https://doi.org/10.1007/978-3-540-92219-3_32 LDOPA official website. https://prj.xiart.ru/projects/ldopa. ShershakovA.A.KalenkovaA.A.LomazovaI.A.Transactions on Petri Nets and Other Models of Concurrency XII2017BerlinSpringer10.1007/978-3-662-55862-1_6 7411_CR2 7411_CR3 7411_CR29 7411_CR4 7411_CR5 7411_CR6 7411_CR7 7411_CR8 7411_CR21 7411_CR22 J. Cortadella (7411_CR16) 1997; E80-D 7411_CR28 7411_CR25 J. Cortadella (7411_CR33) 1998; 47 7411_CR20 S.A. Shershakov (7411_CR26) 2016; 50 S.A. Shershakov (7411_CR31) 2018 U. Çelik (7411_CR9) 2018; 9 7411_CR18 W.M.P. Van der Aalst (7411_CR1) 2011 7411_CR19 7411_CR12 E.W. Dijkstra (7411_CR23) 1965 7411_CR13 7411_CR11 7411_CR17 7411_CR14 7411_CR15 7411_CR30 A.A. Shershakov (7411_CR32) 2017 W.M.P. Van der Aalst (7411_CR34) 2010; 9 P. Kim (7411_CR27) 2014 W. Reisig (7411_CR24) 2013 H. Verbeek (7411_CR10) 2010; 615 |
| References_xml | – reference: ReisigW.Understanding Petri Nets: Modeling Techniques, Analysis Methods, Case Studies2013BerlinSpringer10.1007/978-3-642-33278-41278.68222 – reference: Van der AalstW.M.P.RubinV.VerbeekH.M.W.van DongenB.F.KindlerE.GüntherC.W.Process mining: a two-step approach to balance between underfitting and overfittingSoftware Syst. Mod.201098710.1007/s10270-008-0106-z – reference: VerbeekH.BuijsJ.van DongenB.van der AalstW.ProM 6: The process mining toolkit, in Proc. BPM Demonstation TrackCEUR Workshop Proc.20106153439 – reference: Celonis. www.celonis.com. – reference: Berti, A., van Zelst, S.J., and van der Aalst, W., Process mining for python (PM4Py): Bridging the gap between process- and data science, 2019. arXiv:1905.06169 [cs.SE] – reference: Carmona Vargas, J. and Solé, M., PMLAB: An scripting environment for process mining, Proc. BPM Demo Sessions 2014: Co-Located with the 12th Int. Conf. on Business Process Management (BPM 2014), Eindhoven, The Netherlands, 2014, Haifa: CEUR-WS.org, 2014, pp. 16–20. http://hdl.handle.net/2117/26167. – reference: Mans, R.S., van der Aalst, W.M.P., Vanwersch, R.J.B., and Moleman, A.J., Process mining in healthcare: Data challenges when answering frequently posed questions, in Process Support and Knowledge Representation in Health Care. ProHealth 2012, KR4HC 2012, Lenz, R., Miksch, S., Peleg, M. Reichert, M., Riaño, D., and ten Teije, A., Eds., Lecture Notes in Computer Science, vol. 7738, Berlin: Springer, 2013, pp. 140–153. https://doi.org/10.1007/978-3-642-36438-9_10. – reference: CortadellaJ.KishinevskyM.KondratyevA.LavagnoL.YakovlevA.Petrify: a tool for manipulating concurrent specifications and synthesis of asynchronous controllersIEICE Trans. Inf. Syst.1997E80-D315325 – reference: ShershakovS.A.Enhancing efficiency of process mining algorithms with a tailored library design principles and performance assessment: Technical report2018MoscowHSE Univ.10.13140/RG.2.2.18320.46084 – reference: LDOPA official website. https://prj.xiart.ru/projects/ldopa. – reference: Shershakov, S.A., Multi-perspective process mining with embedding configurations into DB-based event logs, in Tools and Methods of Program Analysis. TMPA 2019, Kalenkova, A., Lozano, J.A., and Yavorskiy, R., Eds., Communications in Computer and Information Science, vol. 1288, Cham: Springer, 2021, pp. 68–80. https://doi.org/10.1007/978-3-030-71472-7_5 – reference: CortadellaJ.KishinevskyM.LavagnoL.YakovlevA.Deriving Petri nets from finite transition systemsIEEE Trans. Comput.199847859882164538610.1109/12.7075871392.68291 – reference: DijkstraE.W.Cooperating Sequential Processes1965EindhovenTechnological Univ. – reference: Mistyuk, A., Kalenkova, A., Shershakov, S., and van der Aalst, W., Using process mining for the analysis of an e-trade system: A case study, Biznes-Inf., 2014, no. 3, pp. 15–27. – reference: Solé, M. and Carmona, J., Rbminer: A tool for discovering Petri nets from transition systems, in Automated Technology for Verification and Analysis. ATVA 2010, Boujjani, A. and Chin, W.N., Eds., Lecture Notes in Computer Science, vol. 6252, Berlin: Springer, 2010. https://doi.org/10.1007/978-3-642-15643-4_33 – reference: Shershakov, S.A., DPMine/P: modeling and process mining language and ProM plug-ins, in Proc. 9th Central & Eastern European Software Engineering Conf. in Russia, Moscow, 2013, New York: Association for Computing Machinery, 2013, p. 2. https://doi.org/10.1145/2556610.2556622 – reference: Fluxicon. http://.uxicon.com/disco. – reference: Cortadella, J., Kishinevsky, M., Kondratyev, A., and Lavagno, L., Introduction to asynchronous circuitdesign: specification and synthesis (tutorial), in Proc. 6th Int. Symp. on Advanced Research in Asynchronous Circuits and Systems, Eilat, Israel, 2000. – reference: Van der AalstW.M.P.Process Mining: Discovery, Conformance and Enhancement of Business Processes2011BerlinSpringer-Verlag10.1007/978-3-642-19345-31216.68016 – reference: ShershakovA.A.KalenkovaA.A.LomazovaI.A.Transactions on Petri Nets and Other Models of Concurrency XII2017BerlinSpringer10.1007/978-3-662-55862-1_6 – reference: Mans, R.S., Schonenberg, M.H., Song, M., van der Aalst, W.M.P., and Bakker, P.J.M., Application of process mining in healthcare – A case study in a Dutch hospital, in Biomedical Engineering Systems and Technologies. BIOSTEC 2008, Fred, A., Filipe, J., and Gamboa, H., Eds., Communication in Computer and Information Science, vol. 25, Berlin: Springer, 2009, pp. 425–438. https://doi.org/10.1007/978-3-540-92219-3_32 – reference: KimP.BulanovO.ShershakovS.Proc. 8th Spring/Summer Young Researchers’ Colloquium on Software Engineering, SYRCoSE2014MoscowIvannikov Inst. Sist. Program., Russ. Acad. Sci – reference: Mans, R.S., van der Aalst, W.M.P., and Verbeek, H.M.W., Supporting process mining workflows with RapidProM, Proc. BPM Demo Sessions,2014, 2014, vol. 56. – reference: Minit. www.minit.io. – reference: ShershakovS.A.DPMine graphical language for automation of experiments in process miningAutom. Control Comput. Sci.20165047748510.3103/S014641161607018X – reference: Visio website. https://products.office.com/en-us/visio/flowchart-software. – reference: Janssenswillen, G. and Depaire, B., bupaR: Business process analysis in R, in Proc. BPM Demo Track and BPM Dissertation Award Co-Located with 15th Int. Conf. on Business Process Management (BPM 2017), Barcelona, 2017, Clarisó, R., Leopold, H., Mendling, J., van der Aalst, W., Kumar, A., Pentland, B., and Weske, M., Eds., CEUR Workshop Proceedings, 2017, vol. 1920. – reference: Rubin, V., Lomazova, I., and van der Aalst, W.M.P., Agile development with software process mining, in Proc. 2014 Int. 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| Title | VTMine for Visio: A Graphical Tool for Modeling in Process Mining |
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