Context: Critical software systems developed for the government continue to be of lower quality than expected, despite extensive literature describing best practices in software engineering. Goal: We wanted to better understand the extent of certain issues in the field and the relationship to software quality. Method: We surveyed fifty software development professionals and asked about practices and barriers in the field and the resulting software quality. Results: There is evidence of certain problematic issues for developers and specific quality characteristics that seem to be affected. Conclusions: This motivates future work to address the most problematic barriers and issues impacting software quality.

Large, dynamic, and ad-hoc organizations must frequently initiate data integration and sharing efforts with insufficient awareness of how organizational data sources are related. Decision makers need to reason about data model interactions much as they do about data instance interactions in OLAP: at multiple levels of granularity. We demonstrate an integrated environment for exploring schema similarity across multiple resolutions. Users visualize and interact with clusters of related schemas using a tool named Affinity. Within any cluster, users may drill-down to examine the extent and content of schema overlap. Further drill down enables users to explore fine-grained element-level correspondences between between two selected schemas.

As display technology continues to improve, there will be an increasing diversity in the available display form factors and scales. Empirical evaluation of how display attributes affect user perceptions and performance can help designers understand the strengths and weaknesses of different display forms, provide guidance for effectively designing multiple display environments, and offer initial evidence for developing theories of ubiquitous display. Although previous research has shown user performance benefits when tiling multiple monitors to increase the number of pixels, little research has analyzed the performance and behavioral impacts of the form factors of much larger, high-resolution displays. This article presents two experiments in which user performance was evaluated on a high-resolution (96 DPI), high pixel-count (approximately 32 million pixels) display for single-user scenarios in both flat and curved forms. We show that for geospatial visual analytics tasks there is a benefit to larger displays, and a distinct advantage to curving the display to make all portions of the display more accessible to the user. In addition, we found that changing the form factor of the display does have an impact on user perceptions that will have to be considered as new display environments are developed.

The scalability of information visualizations has typically been limited by the number of available display pixels. As displays become larger, the scalability limit may shift away from the number of pixels and toward human perceptual abilities. This work explores the effect of using large, high resolution displays to scale up information visualizations beyond potential visual acuity limitations. Displays that are beyond visual acuity require physical navigation to see all of the pixels. Participants performed various information visualization tasks using display sizes with a sufficient number of pixels to be within, equal to, or beyond visual acuity. Results showed that performance on most tasks was more efficient and sometimes more accurate because of the additional data that could be displayed, despite the physical navigation that was required. Visualization design issues on large displays are also discussed.

Larger, higher resolution displays can be used to increase the scalability of information visualizations. But just how much can scalability increase using larger displays before hitting human perceptual or cognitive limits? Are the same visualization techniques that are good on a single monitor also the techniques that are best when they are scaled up using large, high-resolution displays? To answer these questions we performed a controlled experiment on user performance time, accuracy, and subjective workload when scaling up data quantity with different space-time-attribute visualizations using a large, tiled display. Twelve college students used small multiples, embedded bar matrices, and embedded time-series graphs either on a 2 megapixel (Mp) display or with data scaled up using a 32 Mp tiled display. Participants performed various overview and detail tasks on geospatially-referenced multidimensional time-series data. Results showed that current designs are perceptually scalable because they result in a decrease in task completion time when normalized per number of data attributes along with no decrease in accuracy. It appears that, for the visualizations selected for this study, the relative comparison between designs is generally consistent between display sizes. However, results also suggest that encoding is more important on a smaller display while spatial grouping is more important on a larger display. Some suggestions for designers are provided based on our experience designing visualizations for large displays.