Bridging From Goals to Tasks with Design Study Analysis Reports

Heidi Lam, Melanie Tory, and Tamara Munzner


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Abstract

Visualization researchers and practitioners engaged in generating or evaluating designs are faced with the difficult problem of transforming the questions asked and actions taken by target users from domain-specific language and context into more abstract forms. Existing abstract task classifications aim to provide support for this endeavour by providing a carefully delineated suite of actions. Our experience is that this bottom-up approach is part of the challenge: low-level actions are difficult to interpret without a higher-level context of analysis goals and the analysis process. To bridge this gap, we propose a framework based on analysis reports derived from open-coding 20 design study papers published at IEEE InfoVis 2009-2015, to build on the previous work of abstractions that collectively encompass a broad variety of domains. The framework is organized in two axes illustrated by nine analysis goals. It helps situate the analysis goals by placing each goal under axes of specificity (Explore, Describe, Explain, Confirm) and number of data populations (Single, Multiple). The single-population types are Discover Observation, Describe Observation, Identify Main Cause, and Collect Evidence. The multiple-population types are Compare Entities, Explain Differences, and Evaluate Hypothesis. Each analysis goal is scoped by an input and an output and is characterized by analysis steps reported in the design study papers. We provide examples of how we and others have used the framework in a top-down approach to abstracting domain problems: visualization designers or researchers first identify the analysis goals of each unit of analysis in an analysis stream, and then encode the individual steps using existing task classifications with the context of the goal, the level of specificity, and the number of populations involved in the analysis.

Paper

Bridging From Goals to Tasks with Design Study Analysis Reports
IEEE Transactions on Visualization and Computer Graphics (Proc. InfoVis 2017), [Best Paper Honorable Mention], in press.

Pre-Print PDF
Tableau Research paper page
IEEE Digital Library DOI link

Talk

Heidi Lam presented this paper in the Design session at 11:30 am on Wed Oct 4 2017 at IEEE InfoVis 2017.


Video


High-Resolution Figure

Fig. 1. Overview of framework creation process.

Supplementary Materials




Last modified: Sep 28, 2017.