Cambria

Kolarić, Siniša; Woodbury, Robert; Erhan, Halil

doi:10.1145/2598784.2602788

Cited by 6 publications

(1 citation statement)

References 6 publications

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“…From the design domain, Kolarić et al's CAMBRIA [26] displays alternatives in a grid or in a user-defined layout, with "pass variable" and "pass value" operations to make it easier to manipulate alternatives. Zaman et al's GEM-NI and MACE [46] support creating and managing alternatives in generative design.…”

Section: Tools To Support Alternativesmentioning

confidence: 99%

Understanding the Role of Alternatives in Data Analysis Practices

Liu

Boukhelifa

Eagan

2019

IEEE Trans. Visual. Comput. Graphics

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Data workers are people who perform data analysis activities as a part of their daily work but do not formally identify as data scientists. They come from various domains and often need to explore diverse sets of hypotheses and theories, a variety of data sources, algorithms, methods, tools, and visual designs. Taken together, we call these alternatives. To better understand and characterize the role of alternatives in their analyses, we conducted semi-structured interviews with 12 data workers with different types of expertise. We conducted four types of analyses to understand 1) why data workers explore alternatives; 2) the different notions of alternatives and how they fit into the sensemaking process; 3) the high-level processes around alternatives; and 4) their strategies to generate, explore, and manage those alternatives. We find that participants' diverse levels of domain and computational expertise, experience with different tools, and collaboration within their broader context play an important role in how they explore these alternatives. These findings call out the need for more attention towards a deeper understanding of alternatives and the need for better tools to facilitate the exploration, interpretation, and management of alternatives. Drawing upon these analyses and findings, we present a framework based on participants' 1) degree of attention, 2) abstraction level, and 3) analytic processes. We show how this framework can help understand how data workers consider such alternatives in their analyses and how tool designers might create tools to better support them.

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Section: Tools To Support Alternativesmentioning

confidence: 99%

Understanding the Role of Alternatives in Data Analysis Practices

Liu

Boukhelifa

Eagan

2019

IEEE Trans. Visual. Comput. Graphics

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Encoding Design Process Using Interactive Data Visualization

Shireen

Erhan

Woodbury

2019

Communications in Computer and Information Science

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On the Hierarchical Levels of Design Knowledge

Kolarić

Beck

Stolterman

2020

Proc. Des. Soc.: Des. Conf.

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Hierarchies of knowledge represent a popular formalism for conceptualizing beliefs, justifications, and truth statements. To capitalize on the opportunity for formulating effective maps of design knowledge, this article introduces the hierarchical context–design development–high-level (CDH) model that stratifies different bodies of design-specific knowledge into ranked levels. We compare it with existing hierarchical models of knowledge, and describe its unique uses and benefits for both design research and design practice.

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Cambria

Cited by 6 publications

References 6 publications

Understanding the Role of Alternatives in Data Analysis Practices

Understanding the Role of Alternatives in Data Analysis Practices

Encoding Design Process Using Interactive Data Visualization

On the Hierarchical Levels of Design Knowledge

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