Abstract
Data science is transforming business processes. Therefore, process modeling approaches must evolve to capture the entire lifecycle of data transformations. Business process modeling and notation (BPMN) offers a possible solution. However, data objects in BPMN are usually relegated to a secondary role in process flows, missing the complex interactions between data sources and pipelines. This paper presents a systematic literature review and a taxonomy of five types of modeling approaches for data objects in BPMN. The work is conducted in the context of a green and digital transformation project in ports and logistics. Data scientists and process owners may find our proposals interesting for adopting BPMN in their data-driven projects, detailing in a transparent way how (1) data inputs are obtained, (2) processed, and (3) used at a process level of analysis. Theoretically, our work contributes to BPMN literature, comparing five types of modeling approaches for data objects.
Paper Type
Full Paper
DOI
10.62036/ISD.2025.12
Data Science meets BPMN: A Taxonomy of Data Objects Modeling
Data science is transforming business processes. Therefore, process modeling approaches must evolve to capture the entire lifecycle of data transformations. Business process modeling and notation (BPMN) offers a possible solution. However, data objects in BPMN are usually relegated to a secondary role in process flows, missing the complex interactions between data sources and pipelines. This paper presents a systematic literature review and a taxonomy of five types of modeling approaches for data objects in BPMN. The work is conducted in the context of a green and digital transformation project in ports and logistics. Data scientists and process owners may find our proposals interesting for adopting BPMN in their data-driven projects, detailing in a transparent way how (1) data inputs are obtained, (2) processed, and (3) used at a process level of analysis. Theoretically, our work contributes to BPMN literature, comparing five types of modeling approaches for data objects.
Recommended Citation
Barata, I., Ribeiro, V., Barata, J. & Rupino da Cunha, P. (2025). Data Science meets BPMN: A Taxonomy of Data Objects ModelingIn I. Luković, S. Bjeladinović, B. Delibašić, D. Barać, N. Iivari, E. Insfran, M. Lang, H. Linger, & C. Schneider (Eds.), Empowering the Interdisciplinary Role of ISD in Addressing Contemporary Issues in Digital Transformation: How Data Science and Generative AI Contributes to ISD (ISD2025 Proceedings). Belgrade, Serbia: University of Gdańsk, Department of Business Informatics & University of Belgrade, Faculty of Organizational Sciences. ISBN: 978-83-972632-1-5. https://doi.org/10.62036/ISD.2025.12