Background: There has been a dramatic increase in the amount of quantitative data derived from the measurement of changes at different levels of biological complexity during the post-genomic era. However, there are a number of issues associated with the use of computational tools employed for the analysis of such data. For example, computational tools such as R and MATLAB require prior knowledge of their programming languages in order to implement statistical analyses on data. Combining two or more tools in an analysis may also be problematic since data may have to be manually copied and pasted between separate user interfaces for each tool. Furthermore, this transfer of data may require a reconciliation step in order for there to be interoperability between computational tools.

Abstract-Life science workflow systems are developed to help life scientists to conveniently connect various programs and web services. In practice however, much time is spent on data conversion, because web services provided by different organisations use different data formats. We have analysed all the Taverna workflows available at the myExperiment web site on December 11, 2008. Our analysis of the tasks in these workflows shows several noticeable aspects: their number ranges from 1 to 70 tasks per workflow; 18% of the workflows consist of a single task.Of the tasks used are 22% web services; local services, i.e. tasks executed by the workflow system itself, are very popular and cover 57% of tasks; tasks implemented by the workflow designer, scripting tasks, are is also used often (14%). Our analysis shows that over 30% of tasks are related to data conversion.

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Humans have remarkable perceptual capabilities. These capabilities are heavily underestimated in current visualizations [759]. Often, this is due to the lack of an in-depth user study to set the requirements for optimal visualizations. The designer does not understand what kind of information should be visualized, how it should be presented or what kind of interactions should be supported. The key elements of successful information visualization are the correct data using the best visualization technique and the best interaction techniques with respect to users. If one of these elements is ignored, people might interpret the data in the wrong way and thus might not understand the underlying information or a pattern.In order to design effective interactive visualizations, it is important to take into account the limitations of human perception, context of use, and the goals and activities that are to be performed to reach these goals. In order to obtain a usable application, developers have to pay attention to the user's working environment and tasks; this focus-on-user idea is comprised in the human-centered concept.The next section discusses usability (the property of being usable) from the human-centered point of view. Usability has application in many areas, but our focus is on the human-centered approach to design of interactive systems, also called user-centered , in order to inform the reader on how to design visualizations according to human cognitive and perceptual abilities, specific to the context of use and goals of potential users. Then, the usability concept is explained in the "Usability in Human-Centered Design" section. The next Section "User Aims and Requirements" discusses how to define a user group, establish user goals and requirements. Finally, an overview of the different evaluation methods and current evaluation practices, including the practical issues of experiment design that can help to improve the effectiveness of visualizations is presented in the "Evaluation of Visualizations Environments" and "User Studies and a Science of Visualization" sections. Stone et al. [798] describe a human-centered design giving the following definition: Human-Centered Approach