Ali Nour Eldin , Jonathan Baudot , Benjamin Dalmas , Walid Gaaloul
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Moreover, communication gaps and differing interpretations of process requirements frequently arise between developers and business analysts, leading to errors and delays in process implementation and execution.</div><div>To address these limitations, this paper introduces an extension of BPMN, termed the Business Process and Data Modeling Language (BPDML). BPDML is a low-code modeling language specifically designed to capture, model, and execute data-driven business processes. By adopting a low-code approach, BPDML bridges the gap between business analysts and developers, facilitating faster development and delivery of business applications with reduced effort and minimal manual coding. In addition, a specialized modeling tool has been developed to support the creation, validation, and execution of models using BPDML. Both quantitative and qualitative evaluations demonstrate that BPDML significantly enhances the clarity, efficiency, and overall effectiveness of business process modeling and implementation compared to traditional BPMN.</div></div>","PeriodicalId":50363,"journal":{"name":"Information Systems","volume":"135 ","pages":"Article 102577"},"PeriodicalIF":3.4000,"publicationDate":"2025-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Low-code solutions for business process dataflows: From modeling to execution\",\"authors\":\"Ali Nour Eldin , Jonathan Baudot , Benjamin Dalmas , Walid Gaaloul\",\"doi\":\"10.1016/j.is.2025.102577\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Business Process Modeling and Notation (BPMN) is a widely adopted standard for modeling business workflows. However, the increasing complexity and integration of data within business processes demand a modeling language capable of clearly expressing both process and data perspectives. While BPMN effectively represents process control flows, it inadequately addresses critical data-related aspects such as data flow, data dependencies, and data transformations. Moreover, communication gaps and differing interpretations of process requirements frequently arise between developers and business analysts, leading to errors and delays in process implementation and execution.</div><div>To address these limitations, this paper introduces an extension of BPMN, termed the Business Process and Data Modeling Language (BPDML). BPDML is a low-code modeling language specifically designed to capture, model, and execute data-driven business processes. By adopting a low-code approach, BPDML bridges the gap between business analysts and developers, facilitating faster development and delivery of business applications with reduced effort and minimal manual coding. In addition, a specialized modeling tool has been developed to support the creation, validation, and execution of models using BPDML. Both quantitative and qualitative evaluations demonstrate that BPDML significantly enhances the clarity, efficiency, and overall effectiveness of business process modeling and implementation compared to traditional BPMN.</div></div>\",\"PeriodicalId\":50363,\"journal\":{\"name\":\"Information Systems\",\"volume\":\"135 \",\"pages\":\"Article 102577\"},\"PeriodicalIF\":3.4000,\"publicationDate\":\"2025-07-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Information Systems\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0306437925000614\",\"RegionNum\":2,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Information Systems","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0306437925000614","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
Low-code solutions for business process dataflows: From modeling to execution
Business Process Modeling and Notation (BPMN) is a widely adopted standard for modeling business workflows. However, the increasing complexity and integration of data within business processes demand a modeling language capable of clearly expressing both process and data perspectives. While BPMN effectively represents process control flows, it inadequately addresses critical data-related aspects such as data flow, data dependencies, and data transformations. Moreover, communication gaps and differing interpretations of process requirements frequently arise between developers and business analysts, leading to errors and delays in process implementation and execution.
To address these limitations, this paper introduces an extension of BPMN, termed the Business Process and Data Modeling Language (BPDML). BPDML is a low-code modeling language specifically designed to capture, model, and execute data-driven business processes. By adopting a low-code approach, BPDML bridges the gap between business analysts and developers, facilitating faster development and delivery of business applications with reduced effort and minimal manual coding. In addition, a specialized modeling tool has been developed to support the creation, validation, and execution of models using BPDML. Both quantitative and qualitative evaluations demonstrate that BPDML significantly enhances the clarity, efficiency, and overall effectiveness of business process modeling and implementation compared to traditional BPMN.
期刊介绍:
Information systems are the software and hardware systems that support data-intensive applications. The journal Information Systems publishes articles concerning the design and implementation of languages, data models, process models, algorithms, software and hardware for information systems.
Subject areas include data management issues as presented in the principal international database conferences (e.g., ACM SIGMOD/PODS, VLDB, ICDE and ICDT/EDBT) as well as data-related issues from the fields of data mining/machine learning, information retrieval coordinated with structured data, internet and cloud data management, business process management, web semantics, visual and audio information systems, scientific computing, and data science. Implementation papers having to do with massively parallel data management, fault tolerance in practice, and special purpose hardware for data-intensive systems are also welcome. Manuscripts from application domains, such as urban informatics, social and natural science, and Internet of Things, are also welcome. All papers should highlight innovative solutions to data management problems such as new data models, performance enhancements, and show how those innovations contribute to the goals of the application.