When presenting complex, multidimensional data to users, emphasis of relevant information plays an important role. Especially when data is arranged according to several criteria, the simultaneous use of multiple visualization metaphors frequently results in information overload and unintuitive visualizations. In this paper, we present a comparison of preattentive visual features specifically for highlighting relevance of data extracted from electronic documents in an information-rich virtual environment. Several visual cues were evaluated with regard to their effectivity, comprehensibility and influence on other visualized features. At the same time we introduce two innovative data handling techniques to achieve practical applicability of our system: An intuitive way to reduce visual cluttering of information by filtering information based on its visual depth and a way to efficiently utilize visualizations of different dimensions - dimensional congruence
In terms of software maintenance and comprehension, the fields of software engineering and software visualization have produced several methods and tools. However, they are typically separate tools in practice. In this paper, we present a novel methodology of combining software analysis and software visualization tools via an interactive visual workflow modeling approach. Standard software analysis tools are also limited in that they support only well-known metrics or are too complicated to use for generating custom software metrics. To address these shortcomings, our approach focuses on visual elements, their configurations, and interconnectivity rather than a data ontology and querying language. In order to test and validate our methodology, we developed a prototype tool called VIMETRIK (Visual Specification of Metrics). Our preliminary evaluation study illustrates the intuitiveness and ease-of-use of our approach with regard to understanding software measurement and analysis data
Many software development organizations still lack support for obtaining intellectual control over their software development processes and for determining the performance of their processes and the quality of the produced products. Systematic support for detecting and reacting to critical process and product states in order to achieve planned goals is usually missing. One means to institutionalize measurement on the basis of explicit models is the development and establishment of a so-called Software Project Control Center (SPCC) for systematic quality assurance and management support. An SPCC is comparable to a control room, which is a well known term in the mechanical production domain. One crucial task of an SPCC is the systematic visualization of measurement data in order to provide context-, purpose-, and role-oriented information for all stakeholders (e.g., project managers, quality assurance managers, developers) during the execution of a software development project. The article will present an overview of SPCC concepts, a concrete instantiation that supports goal-oriented data visualization, as well as examples and experiences from practical applications.
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