A Mixed-Initiative Visual Analytics Approach for Qualitative Causal Modeling

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 a...

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Bibliographic Details
Published inarXiv.org
Main Authors Husain, Fahd, Proulx, Pascale, Meng-Wei, Chang, Romero-Gomez, Rosa, Vasquez, Holland
Format Paper Journal Article
LanguageEnglish
Published Ithaca Cornell University Library, arXiv.org 08.09.2021
Subjects
Complex systems
Computer Science - Human-Computer Interaction
Domains
Modelling
Qualitative analysis
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Summary: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.
ISSN:2331-8422
DOI:10.48550/arxiv.2109.03669