Data Abstraction Elephants: The Initial Diversity of Data Representations and Mental Models
Data Abstraction Elephants: The Initial Diversity of Data Representations and Mental Models
复制标题
数据抽象大象:数据表示和心理模型的初始多样性
DOI:
10.1145/3544548.3580669
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发表时间:
2023
期刊:
影响因子:
--
通讯作者:
Isaacs, Katherine E.
中科院分区:
文献类型:
--
作者:
Williams, Katy;Bigelow, Alex;Isaacs, Katherine E.
Two people looking at the same dataset will create different mental models, prioritize different attributes, and connect with different visualizations. We seek to understand the space of data abstractions associated with mental models and how well people communicate their mental models when sketching. Data abstractions have a profound influence on the visualization design, yet it’s unclear how universal they may be when not initially influenced by a representation. We conducted a study about how people create their mental models from a dataset. Rather than presenting tabular data, we presented each participant with one of three datasets in paragraph form, to avoid biasing the data abstraction and mental model. We observed various mental models, data abstractions, and depictions from the same dataset, and how these concepts are influenced by communication and purpose-seeking. Our results have implications for visualization design, especially during the discovery and data collection phase.
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