ABSTRACT
In domains, such as agronomy or manufacturing, experts need to consider trade-offs when making decisions that involve several, often competing, objectives. Such analysis is complex and may be conducted over long periods of time, making it hard to revisit. In this paper, we consider the use of analytic provenance mechanisms to aid experts recall and keep track of trade-off analysis. We implemented VisProm, a web-based trade-off analysis system, that incorporates in-visualization provenance views, designed to help experts keep track of trade-offs and their objectives. We used VisProm as a technology probe to understand user needs and explore the potential role of provenance in this context. Through observation sessions with three groups of experts analyzing their own data, we make the following contributions. We first, identify eight high-level tasks that experts engaged in during trade-off analysis, such as locating and characterizing interest zones in the trade-off space, and show how these tasks can be supported by provenance visualization. Second, we refine findings from previous work on provenance purposes such as recall and reproduce, by identifying specific objects of these purposes related to trade-off analysis, such as interest zones, and exploration structure (e.g., exploration of alternatives and branches). Third, we discuss insights on how the identified provenance objects and our designs support these trade-off analysis tasks, both when revisiting past analysis and while actively exploring. And finally, we identify new opportunities for provenance-driven trade-off analysis, for example related to monitoring the coverage of the trade-off space, and tracking alternative trade-off scenarios.
ABSTRACT
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.
ABSTRACT
BACKGROUND: Malpositioning of the acetabular cup during total hip arthroplasty increases the risk of dislocation, edge-loading, squeaking, early wear, and loosening. We hypothesized that the use of three-dimensional (3-D) visualization tools to identify the planned cup position relative to the acetabular edge intraoperatively would increase the accuracy of cup orientation. The purpose of this study was to compare 3-D planning-assisted implantation and freehand insertion of the acetabular cup. METHODS: This was a prospective randomized controlled study of two groups of twenty-eight patients each. In the first group, cup positioning was guided by 3-D views of the cup within the acetabulum obtained during 3-D preoperative planning. In the control group, the cup was placed freehand. All of the patients were operated on by the same surgeon, through a minimally invasive direct anterior approach with the patient in the supine position. Cup anteversion and abduction angles were measured on 3-D computed tomography (CT) reconstructions. The main evaluation criterion was the percentage of outliers according to the Lewinnek safe zone. RESULTS: Operative time did not differ between the two groups. The cup anteversion was more accurate in the 3-D planning group (mean difference from the planned angle [and standard deviation], -2.7° ± 5.4°) compared with the freehand-placement group (6.6° ± 9.5°). According to the Lewinnek safe zone, overall, the percentage of outliers was lower in the 3-D planning group (21%; six patients) than in the control group (46%; thirteen patients). According to the Callanan safe zone, the percentage of outliers was also lower in the 3-D planning group (25% versus 64%). Although cup abduction was also restored with greater accuracy in the 3-D planning group, on the basis of the Lewinnek safe zone, the percentage of abduction outliers was comparable between groups, with fewer high-abduction values, but more low-abduction values, in the 3-D planning group. CONCLUSIONS: Preoperative 3-D planning increased the accuracy of anteversion restoration and reduced the percentage of outliers without increasing the operative time. In this study, the same advantage could not be demonstrated for abduction. LEVEL OF EVIDENCE: Therapeutic Level I. See Instructions for Authors for a complete description of levels of evidence.
