Many visual analytics systems allow users to interact with machine learning models towards the goals of data exploration and insight generation on a given dataset. However, in some situations, insights may be less important than the production of an accurate predictive model for future use. In that case, users are more interested in generating of diverse and robust predictive models, verifying their performance on holdout data, and selecting the most suitable model for their usage scenario. In this paper, we consider the concept of Exploratory Model Analysis (EMA), which is defined as the process of discovering and selecting relevant models that can be used to make predictions on a data source. We delineate the differences between EMA and the well‐known term exploratory data analysis in terms of the desired outcome of the analytic process: insights into the data or a set of deployable models. The contributions of this work are a visual analytics system workflow for EMA, a user study, and two use cases validating the effectiveness of the workflow. We found that our system workflow enabled users to generate complex models, to assess them for various qualities, and to select the most relevant model for their task.

We present a framework that incorporates user-centered design (UCD) philosophy into agile software development through a three-fold integration approach: at the process life-cycle level for the selection and application of appropriate UCD methods and techniques in the right places at the right times; at the iteration level for integrating UCD concepts, roles, and activities during each agile development iteration planning; and at the development-environment level for managing and automating the sets of UCD activities through automated tools support. We also present two automated tools-UEMan and TaMUlator, which provide the realization of the development-environment level integration.

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The design of interactive systems to be used in mobile and pervasive scenarios, such as emergency management, requires novel methodologies which combine user-centred design approaches and software engineering approaches tailored for distributed architectures. In this paper, the methodology adopted in a successful research project is presented together with a case study.

In complex emergency/disaster scenarios, teams from various emergency-response organizations collaborate in order to achieve a common goal. The use of smart mobile devices and applications in these scenarios can improve this collaboration dynamically; and poses interesting challenges, such as user' mental attention, small screen size, unavailability of reliable network, reduced power, and battery consumption. So, to design and develop interactive applications to be used in mobile and pervasive scenarios requires novel methodologies which combine user-centred design approaches and software engineering approaches tailed for distributed architectures. In this paper, we outline the methodology, adopted successfully in the European WORKPAD project, and describe the work done from getting the requirements to developing the interface of the desired system

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Multi-touch gesture interaction is one of the main features that differentiate the current smart mobile era from the desktop-computing era. Heuristic evaluation is a popular usability evaluation method, mainly due to being less time-consuming, more cost effective, and applicable to different stages of the design and development phases. Researchers have provided their own sets of heuristics targeting domain specific mobile applications or some specific features (e.g., contextual behaviour). In this work, we specifically target evaluating multi-touch gestures in mobile apps through a set of 15 heuristics, which we selected after analysing previously proposed sets of heuristics. However, we adjusted these selected heuristics to make them appropriate for evaluating multi-touch gestures. We conducted a preliminary study with five evaluators in which they were able to find out more usability problems related to multi-touch gestures in the used mobile app compared to a previously proposed heuristics set for mobile apps. Heuristic evaluation. Usability evaluation. Multi-touch gestures. Mobile apps. Smart mobile devices.