视觉分析工作流程的认知任务分析:探索系统生物学中的分子相互作用网络

Barbara Mirel, Felix Eichinger, Benjamin J Keller, Matthias Kretzler
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摘要

背景:生物信息学可视化工具往往不够强大,无法支持生物医学专家进行复杂的探索性分析。这些工具需要适应科学家们针对特定转化研究问题实际执行的工作流程。为了了解这些工作流程并为其中一个流程建模,我们对生物医学专家的探索性工作流程进行了基于案例的认知任务分析:结果:通过认知任务分析,我们开发出了目标工作流程的四种互补表征。它们包括:使用场景、流程图、认知任务分类以及认知任务与以用户为中心的可视化需求之间的映射。这些表征捕捉了引导生物医学专家进行对假设至关重要的推断的认知任务流程。我们创建了可从战略上指导可视化开发的详细程度的表征,并根据用户对一小部分工作流程的要求制作了试验原型,从而证实了这一点:我们的研究结果表明,可视化应为科学用户提供 "功能组合",使其与工作流程中特定阶段有目的地执行的组合认知任务相一致。我们还强调了可视化的某些方面:(a) 需要更多的内置灵活性;(b) 对于协商意义至关重要;(c) 对于必要的元认知支持必不可少。
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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A cognitive task analysis of a visual analytic workflow: Exploring molecular interaction networks in systems biology.

Background: Bioinformatics visualization tools are often not robust enough to support biomedical specialists’ complex exploratory analyses. Tools need to accommodate the workflows that scientists actually perform for specific translational research questions. To understand and model one of these workflows, we conducted a case-based, cognitive task analysis of a biomedical specialist’s exploratory workflow for the question: What functional interactions among gene products of high throughput expression data suggest previously unknown mechanisms of a disease?

Results: From our cognitive task analysis four complementary representations of the targeted workflow were developed. They include: usage scenarios, flow diagrams, a cognitive task taxonomy, and a mapping between cognitive tasks and user-centered visualization requirements. The representations capture the flows of cognitive tasks that led a biomedical specialist to inferences critical to hypothesizing. We created representations at levels of detail that could strategically guide visualization development, and we confirmed this by making a trial prototype based on user requirements for a small portion of the workflow.

Conclusions: Our results imply that visualizations should make available to scientific users “bundles of features” consonant with the compositional cognitive tasks purposefully enacted at specific points in the workflow. We also highlight certain aspects of visualizations that: (a) need more built-in flexibility; (b) are critical for negotiating meaning; and (c) are necessary for essential metacognitive support.

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Two Similarity Metrics for Medical Subject Headings (MeSH): An Aid to Biomedical Text Mining and Author Name Disambiguation. The language of discovery. Bias associated with mining electronic health records. Literature-based Resurrection of Neglected Medical Discoveries. A cognitive task analysis of a visual analytic workflow: Exploring molecular interaction networks in systems biology.
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