Workflows Científicos com Apoio de Bases de Conhecimento em Tempo Real

Victor S. Bursztyn, J. Dias, M. Mattoso
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Abstract

One major challenge in large-scale experiments is the analytical capacity to contrast ongoing results with domain knowledge. We approach this challenge by constructing a domain-specific knowledge base, which is queried during workflow execution. We introduce K-Chiron, an integrated solution that combines a state-of-the-art automatic knowledge base construction (KBC) system to Chiron, a well-established workflow engine. In this work we experiment in the context of Political Sciences to show how KBC may be used to improve human-in-the-loop (HIL) support in scientific experiments. While HIL in traditional domain expert supervision is done offline, in K-Chiron it is done online, i.e. at runtime. We achieve results in less laborious ways, to the point of enabling a breed of experiments that could be unfeasible with traditional HIL. Finally, we show how provenance data could be leveraged with KBC to enable further experimentation in more dynamic settings.
具有实时知识库支持的科学工作流程
大规模实验的一个主要挑战是将正在进行的结果与领域知识进行对比的分析能力。我们通过构建一个特定于领域的知识库来解决这个问题,该知识库在工作流执行期间进行查询。我们推出了K-Chiron,这是一个集成解决方案,将最先进的自动知识库构建(KBC)系统与Chiron(一个完善的工作流引擎)相结合。在这项工作中,我们在政治学的背景下进行实验,以展示如何使用KBC来改善科学实验中的人在环(HIL)支持。传统领域专家监督中的HIL是离线完成的,而在K-Chiron中是在线完成的,即在运行时完成。我们以更省力的方式获得结果,从而实现了传统HIL无法实现的一系列实验。最后,我们展示了如何将来源数据与KBC结合起来,以便在更动态的环境中进行进一步的实验。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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