SWEL: A domain-specific language for modeling data-intensive workflows

Salado-Cid, Rubén; Vallecillo, Antonio; Munir, Kamram; Romero, José Raúl

Abstract

Data-intensive applications aim at discovering valuable knowledge from large amounts of data coming from real-world sources. Typically, workflow languages are used to specify these applications, and their associated engines enable the execution of the specifications. However, as these applications become commonplace, new challenges arise. Existing workflow languages are normally platform-specific, which severely hinders their interoperability with other languages and execution engines. This also limits their reusability outside the platforms for which they were originally defined. Following the Design Science Research methodology, the paper presents SWEL (Scientific Workflow Execution Language). SWEL is a domain-specific modeling language for the specification of data-intensive workflows that follow the model-driven engineering principles, covering the high-level definition of tasks, information sources, platform requirements, and mappings to the target technologies. SWEL is platform-independent, enables collaboration among data scientists across multiple domains and facilitates interoperability. The evaluation results show that SWEL is suitable enough to represent the concepts and mechanisms of commonly used data-intensive workflows. Moreover, SWEL facilitates the development of related technologies such as editors, tools for exchanging knowledge assets between workflow management systems, and tools for collaborative workflow development.

• Journal Article Type: Article
• Acceptance Date: Jun 20, 2023
• Online Publication Date: Aug 6, 2023
• Publication Date: Apr 1, 2024
• Deposit Date: Aug 7, 2023
• Publicly Available Date: May 10, 2024
• Journal: Business & Information Systems Engineering
• Electronic ISSN: 1867-0202
• Publisher: Springer (part of Springer Nature)
• Peer Reviewed: Peer Reviewed
• Volume: 66
• Issue: 2
• Pages: 137-160
• DOI: https://doi.org/10.1007/s12599-023-00826-7
• Keywords: Data-driven workflows, Data science, Domain-specific modeling, Data-intensive applications, Conceptual modeling, Model-driven engineering
• Public URL: https://uwe-repository.worktribe.com/output/11012114
• Additional Information: Received: 4 April 2022; Accepted: 20 June 2023; First Online: 6 August 2023