In many application areas, analysts have to make sense of large volumes of multivariate time-series data. Explorative analysis of this kind of data is often difficult and overwhelming at the level of raw data. Temporal data abstraction reduces data complexity by deriving qualitative statements that reflect domain-specific key characteristics. Visual representations of abstractions and raw data together with appropriate interaction methods can support analysts in making their data easier to understand. Such a visualization technique that applies smooth semantic zooming has been developed in the context of patient data analysis. However, no empirical evidence on its effectiveness and efficiency is available. In this paper, we aim to fill this gap by reporting on a controlled experiment that compares this technique with another visualization method used in the well-known KNAVE-II framework. Both methods integrate quantitative data with qualitative abstractions whereas the first one uses a composite representation with color-coding to display the qualitative data and spatial position coding for the quantitative data. The second technique uses juxtaposed representations for quantitative and qualitative data with spatial position coding for both. Results show that the test persons using the composite representation were generally faster, particularly for more complex tasks that involve quantitative values as well as qualitative abstractions.

It is generally acknowledged in visualization research that it is necessary to evaluate visualization artifacts in order to provide empirical evidence on their effectiveness and efficiency as well as their usability and utility. However, the difficulties of conducting such evaluations still remain an issue. Apart from the required know-how to appropriately design and conduct user studies, the necessary implementation effort for evaluation features in visualization software is a considerable obstacle. To mitigate this, we present EvalBench, an easy-to-use, flexible, and reusable software library for visualization evaluation written in Java. We describe its design choices and basic abstractions of our conceptual architecture and demonstrate its applicability by a number of case studies. EvalBench reduces implementation effort for evaluation features and makes conducting user studies easier. It can be used and integrated with third-party visualization prototypes that need to be evaluated via loose coupling. EvalBench supports both, quantitative and qualitative evaluation methods such as controlled experiments, interaction logging, laboratory questionnaires, heuristic evaluations, and insight diaries.

In several application fields, the joint visualization of quantitative data and qualitative abstractions can help analysts make sense of complex time series data by associating precise numeric values with corresponding domain-specific interpretations, such as good, bad, high, low, normal. At the same time, the need to analyse large multivariate time-oriented datasets often calls for keeping visualizations as compact as possible. In this paper, we introduce Qualizon Graphs, a compact visualization that combines quantitative data and qualitative abstractions. It is based on the well known Horizon Graphs, but instead of a predefined number of equally sized bands, it uses as many bands as qualitative categories with corresponding different sizes. In this way, Qualizon Graphs increase the data density of visualized quantitative values and inherently integrate qualitative abstractions. A user study shows that Qualizon Graphs are as fast and accurate as Horizon Graphs for quantitative data, and are an alternative to state-of-the-art visualizations for both quantitative and qualitative data, enabling a trade-off between speed and accuracy.

Years ago car manufacturers started using reusable software components for the development of ECU applications. As communication between ECUs is not a competitive advantage, there has been a lot of standardization efforts, especially in Europe. Whereas the standards for Operating Systems and Network Managements are widely accepted and used, all major OEMs created their own versions of Communication Modules, which presents a major roadblock for OEM independent ECU development. We show how the OEM specifics can be hidden by using a tool configured middleware. PROBLEMS OF SOFTWARE DEVELOPMENT FOR MULTIPLE OEMS AUTOMOTIVE NETWORK A network consists of a physical media to transport information and several nodes which receive and transmit data via the network. To understand each other