Modeling complex systems is a time-consuming, difficult and fragmented task, often requiring the analyst to work with disparate data, a variety of models, and expert knowledge across a diverse set of domains. Applying a user-centered design process, we developed a mixed-initiative visual analytics approach, a subset of the Causemos platform, that allows analysts to rapidly assemble qualitative causal models of complex socio-natural systems. Our approach facilitates the construction, exploration, and curation of qualitative models bringing together data across disparate domains. Referencing a recent user evaluation, we demonstrate our approach's ability to interactively enrich user mental models and accelerate qualitative model building.

中文翻译：

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用于定性因果建模的混合初始可视化分析方法

对复杂系统建模是一项耗时、困难且分散的任务，通常需要分析师处理不同领域的不同数据、各种模型和专家知识。应用以用户为中心的设计流程，我们开发了一种混合主动可视化分析方法，这是 Causemos 平台的一个子集，它允许分析师快速组装复杂社会自然系统的定性因果模型。我们的方法促进了定性模型的构建、探索和管理，将不同领域的数据整合在一起。参考最近的用户评估，我们展示了我们的方法以交互方式丰富用户心智模型和加速定性模型构建的能力。