Charlotte Verbruggen, Alexandre Goossens, Johannes De Smedt, Jan Vanthienen, Monique Snoeck
{"title":"iDOCEM","authors":"Charlotte Verbruggen, Alexandre Goossens, Johannes De Smedt, Jan Vanthienen, Monique Snoeck","doi":"10.1007/s10270-024-01191-z","DOIUrl":null,"url":null,"abstract":"<p>In the business process lifecycle, models can be approached from two perspectives: on the one hand, models are used to create systems in the design phase, and on the other hand, systems in use produce (event) logs that are used to discover the models representing the structure of the systems. These discovered models can be the starting point of a new cycle of analysis, redesign, implementation, etc. Therefore, proper logging of implemented processes in line with system design is a critical element for process discovery. Recently, the consideration of the integration of data and process aspects has seen a surge in interest in both the model-for-design domain as in the automated-model-discovery domain. However, it seems that these domains use different conceptualizations of data/object-aware systems. A definition of how the captured event logs are related to the structure of the global system they are extracted from or are trying to discover is still missing. Especially the concept of an event needs to be aligned, as this is the main concept that the domains have in common. This paper investigates the concepts and terminology used in the different phases of the business process lifecycle: the design phase, the implementation phase (including the implementation of logging) and the discovery phase. The paper contains an extensive running example that is used to illustrate five misalignment issues. The main contribution of this paper is a meta-model that presents a unified terminology for modelling both domains and is demonstrated using the running example. The paper also shows how the concepts of iDOCEM relate to the concepts of a conceptual modelling approach and several event logging formats. iDOCEM is validated with the implementation of a log generator for the running case, demonstrating the feasibility of generating DOCEL-compliant logs from an application.</p>","PeriodicalId":49507,"journal":{"name":"Software and Systems Modeling","volume":"66 1","pages":""},"PeriodicalIF":2.0000,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"iDOCEM\",\"authors\":\"Charlotte Verbruggen, Alexandre Goossens, Johannes De Smedt, Jan Vanthienen, Monique Snoeck\",\"doi\":\"10.1007/s10270-024-01191-z\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>In the business process lifecycle, models can be approached from two perspectives: on the one hand, models are used to create systems in the design phase, and on the other hand, systems in use produce (event) logs that are used to discover the models representing the structure of the systems. These discovered models can be the starting point of a new cycle of analysis, redesign, implementation, etc. Therefore, proper logging of implemented processes in line with system design is a critical element for process discovery. Recently, the consideration of the integration of data and process aspects has seen a surge in interest in both the model-for-design domain as in the automated-model-discovery domain. However, it seems that these domains use different conceptualizations of data/object-aware systems. A definition of how the captured event logs are related to the structure of the global system they are extracted from or are trying to discover is still missing. Especially the concept of an event needs to be aligned, as this is the main concept that the domains have in common. This paper investigates the concepts and terminology used in the different phases of the business process lifecycle: the design phase, the implementation phase (including the implementation of logging) and the discovery phase. The paper contains an extensive running example that is used to illustrate five misalignment issues. The main contribution of this paper is a meta-model that presents a unified terminology for modelling both domains and is demonstrated using the running example. The paper also shows how the concepts of iDOCEM relate to the concepts of a conceptual modelling approach and several event logging formats. iDOCEM is validated with the implementation of a log generator for the running case, demonstrating the feasibility of generating DOCEL-compliant logs from an application.</p>\",\"PeriodicalId\":49507,\"journal\":{\"name\":\"Software and Systems Modeling\",\"volume\":\"66 1\",\"pages\":\"\"},\"PeriodicalIF\":2.0000,\"publicationDate\":\"2024-07-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Software and Systems Modeling\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.1007/s10270-024-01191-z\",\"RegionNum\":3,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"COMPUTER SCIENCE, SOFTWARE ENGINEERING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Software and Systems Modeling","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1007/s10270-024-01191-z","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, SOFTWARE ENGINEERING","Score":null,"Total":0}
In the business process lifecycle, models can be approached from two perspectives: on the one hand, models are used to create systems in the design phase, and on the other hand, systems in use produce (event) logs that are used to discover the models representing the structure of the systems. These discovered models can be the starting point of a new cycle of analysis, redesign, implementation, etc. Therefore, proper logging of implemented processes in line with system design is a critical element for process discovery. Recently, the consideration of the integration of data and process aspects has seen a surge in interest in both the model-for-design domain as in the automated-model-discovery domain. However, it seems that these domains use different conceptualizations of data/object-aware systems. A definition of how the captured event logs are related to the structure of the global system they are extracted from or are trying to discover is still missing. Especially the concept of an event needs to be aligned, as this is the main concept that the domains have in common. This paper investigates the concepts and terminology used in the different phases of the business process lifecycle: the design phase, the implementation phase (including the implementation of logging) and the discovery phase. The paper contains an extensive running example that is used to illustrate five misalignment issues. The main contribution of this paper is a meta-model that presents a unified terminology for modelling both domains and is demonstrated using the running example. The paper also shows how the concepts of iDOCEM relate to the concepts of a conceptual modelling approach and several event logging formats. iDOCEM is validated with the implementation of a log generator for the running case, demonstrating the feasibility of generating DOCEL-compliant logs from an application.
期刊介绍:
We invite authors to submit papers that discuss and analyze research challenges and experiences pertaining to software and system modeling languages, techniques, tools, practices and other facets. The following are some of the topic areas that are of special interest, but the journal publishes on a wide range of software and systems modeling concerns:
Domain-specific models and modeling standards;
Model-based testing techniques;
Model-based simulation techniques;
Formal syntax and semantics of modeling languages such as the UML;
Rigorous model-based analysis;
Model composition, refinement and transformation;
Software Language Engineering;
Modeling Languages in Science and Engineering;
Language Adaptation and Composition;
Metamodeling techniques;
Measuring quality of models and languages;
Ontological approaches to model engineering;
Generating test and code artifacts from models;
Model synthesis;
Methodology;
Model development tool environments;
Modeling Cyberphysical Systems;
Data intensive modeling;
Derivation of explicit models from data;
Case studies and experience reports with significant modeling lessons learned;
Comparative analyses of modeling languages and techniques;
Scientific assessment of modeling practices