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Knowledge Annotations in Scientific Workflows: An Implementation in Kepler

机译:科学工作流中的知识注释:开普勒的实现

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Scientific research products are the result of long-term collaborations between teams. Scientific workflows are capable of helping scientists in many ways including collecting information about how research was conducted (e.g., scientific workflow tools often collect and manage information about datasets used and data transformations). However, knowledge about why data was collected is rarely documented in scientific workflows. In this paper we describe a prototype system built to support the collection of scientific expertise that influences scientific analysis. Through evaluating a scientific research effort underway at the Pacific Northwest National Laboratory, we identified features that would most benefit PNNL scientists in documenting how and why they conduct their research, making this information available to the entire team. The prototype system was built by enhancing the Kepler Scientific Workflow System to create knowledge-annotated scientific workflows and to publish them as semantic annotations.
机译:科研产品是团队之间长期合作的结果。科学工作流程能够以多种方式帮助科学家,包括收集有关研究进行方式的信息(例如,科学工作流程工具通常会收集和管理有关使用的数据集和数据转换的信息)。但是,关于为什么收集数据的知识很少记录在科学工作流程中。在本文中,我们描述了一个原型系统,该系统旨在支持影响科学分析的科学专业知识的收集。通过评估太平洋西北国家实验室正在进行的科学研究工作,我们确定了最能使PNNL科学家受益的特征,这些特征记录了他们进行研究的方式和原因,并将这些信息提供给整个团队。通过增强开普勒科学工作流程系统来构建原型系统,以创建带有知识注释的科学工作流程并将其发布为语义注释。

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