分类： 计算机科学 >> 计算机科学的集成理论 提交时间： 2022-11-28 合作期刊: 《数据智能（英文）》
摘要： The investigation proposes the application of an ontological semantic approach to describing workflow control patterns, research workflow step patterns, and the meaning of the workflows in terms of domain knowledge. The approach can provide wide opportunities for semantic refinement, reuse, and composition of workflows. Automatic reasoning allows verifying those compositions and implementations and provides machine-actionable workflow manipulation and problem-solving using workflows. The described approach can take into account the implementation of workflows in different workflow management systems, the organization of workflows collections in data infrastructures and the search for them, the semantic approach to the selection of workflows and resources in the research domain, the creation of research step patterns and their implementation reusing fragments of existing workflows, the possibility of automation of problem#2; solving based on the reuse of workflows. The application of the approach to CWFR conceptions is proposed.
分类： 计算机科学 >> 计算机科学的集成理论 提交时间： 2022-11-28 合作期刊: 《数据智能（英文）》
Peter, Wittenburg
Alex, Hardisty
Yann, Le Franc
Amirpasha, Mozaffari
Limor, Peer
Nikolay, A. Skvortsov
Zhiming, Zhao
Alessandro, Spinuso
摘要： The FAIR principles have been accepted globally as guidelines for improving data-driven science and data management practices, yet the incentives for researchers to change their practices are presently weak. In addition, data-driven science has been slow to embrace workflow technology despite clear evidence of recurring practices. To overcome these challenges, the Canonical Workflow Frameworks for Research (CWFR) initiative suggests a large-scale introduction of self-documenting workflow scripts to automate recurring processes or fragments thereof. This standardised approach, with FAIR Digital Objects as anchors, will be a significant milestone in the transition to FAIR data without adding additional load onto the researchers who stand to benefit most from it. This paper describes the CWFR approach and the activities of the CWFR initiative over the course of the last year or so, highlights several projects that hold promise for the CWFR approaches, including Galaxy, Jupyter Notebook, and RO Crate, and concludes with an assessment of the state of the field and the challenges ahead.
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