The elegance of using virtual interactive lenses to provide alternative visual representations for selected regions of interest is highly valued, especially in the realm of visualization. Today, more than 50 lens techniques are known in the closer context of visualization, far more in related fields. In this paper, we extend our previous survey on interactive lenses for visualization. We propose a definition and a conceptual model of lenses as extensions of the classic visualization pipeline. An extensive review of the literature covers lens techniques for different types of data and different user tasks and also includes the technologies employed to display lenses and to interact with them. We introduce a taxonomy of lenses for visualization and illustrate its utility by dissecting in detail a multi-touch lens for exploring large graph layouts. As a conclusion of our review, we identify challenges and unsolved problems to be addressed in future research.

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Usually visualization is applied to gain insight into data. Yet consuming the data in form of visual representation is not always enough. Instead, users need to edit the data, preferably through the same means used to visualize them. In this work, we present a semi‐automatic approach to visual editing of graphs. The key idea is to use an interactive EditLens that defines where an edit operation affects an already customized and established graph layout. Locally optimal node positions within the lens and edge routes to connected nodes are calculated according to different criteria. This spares the user much manual work, but still provides sufficient freedom to accommodate application‐dependent layout constraints. Our approach utilizes the advantages of multi‐touch gestures, and is also compatible with classic mouse and keyboard interaction. Preliminary user tests have been conducted with researchers from bio‐informatics who need to manually maintain a slowly, but constantly growing molecular network. As the user feedback indicates, our solution significantly improves the editing procedure applied so far.

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There are many expressive visualization techniques for analyzing graphs. Yet, there is only little research on how existing visual representations can be employed to support data editing. An increasingly relevant task when working with graphs is the editing of node attributes. We propose an integrated visualize-and-edit approach to editing attribute values via direct interaction with the visual representation. The visualize part is based on node-link diagrams paired with attribute-dependent layouts. The edit part is as easy as moving nodes via drag-and-drop gestures. We present dedicated interaction techniques for editing quantitative as well as qualitative attribute data values. The benefit of our novel integrated approach is that one can directly edit the data while the visualization constantly provides feedback on the implications of the data modifications. Preliminary user feedback indicates that our integrated approach can be a useful complement to standard non-visual editing via external tools.