IEEE VIS 2024 Content: Preliminary Guidelines For Combining Data Integration and Visual Data Analysis

Preliminary Guidelines For Combining Data Integration and Visual Data Analysis

Adam Coscia -

Ashley Suh -

Remco Chang -

Alex Endert -

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DOI: 10.1109/TVCG.2023.3334513

Room: Bayshore II

2024-10-16T13:18:00ZGMT-0600Change your timezone on the schedule page
2024-10-16T13:18:00Z
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We studied differences in sensemaking during visual data analysis between manually integrating data with Excel versus automatic integration built-in to a visual analytics interface. We discovered unique analysis strategies with automatic integration, as well as negative effects on tracking insights, satisficing and biased behaviors. We contribute open questions and design guidelines for building future tools that integrate data throughout the visual analytics process. Our data, analysis, and results are all open-source and available at: https://github.com/AdamCoscia/Integration-Guidelines-VA. To read about them, check out our paper!
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Keywords

Visual analytics, Data integration, User interface design, Integration strategies, Analytical behaviors.

Abstract

Data integration is often performed to consolidate information from multiple disparate data sources during visual data analysis. However, integration operations are usually separate from visual analytics operations such as encode and filter in both interface design and empirical research. We conducted a preliminary user study to investigate whether and how data integration should be incorporated directly into the visual analytics process. We used two interface alternatives featuring contrasting approaches to the data preparation and analysis workflow: manual file-based ex-situ integration as a separate step from visual analytics operations; and automatic UI-based in-situ integration merged with visual analytics operations. Participants were asked to complete specific and free-form tasks with each interface, browsing for patterns, generating insights, and summarizing relationships between attributes distributed across multiple files. Analyzing participants' interactions and feedback, we found both task completion time and total interactions to be similar across interfaces and tasks, as well as unique integration strategies between interfaces and emergent behaviors related to satisficing and cognitive bias. Participants' time spent and interactions revealed that in-situ integration enabled users to spend more time on analysis tasks compared with ex-situ integration. Participants' integration strategies and analytical behaviors revealed differences in interface usage for generating and tracking hypotheses and insights. With these results, we synthesized preliminary guidelines for designing future visual analytics interfaces that can support integrating attributes throughout an active analysis process.