New challenges for advanced web search interfaces and visualization tools arise as user needs shift from traditional lookup tasks towards more open ended search activities collectively described as exploratory search. Exploratory search opens new possibilities for employing social aspects for effective information retrieval. We facilitate exploratory search by providing users with an integrated search and navigation interface combining three search paradigms – full text search, view-based (faceted) search and content-based (queryby-example) search. Full text search is used for both domain data and metadata lookup, view-based search allows users to further refine/filter the respective result set, while content-based search orders or biases the results based on their similarity to a given set of sample results.

Abstract. Growing need for information retrieval, information processing, and the associated need for navigation in existing information spaces resulted in several approaches that aim to improve efficiency of the respective user tasks. However, problems related to user navigation and orientation in large open information spaces still persist possibly due to increasing demands and the imperfections of individual approaches. We propose an integrated search and navigation solution that takes advantage of the faceted browsing paradigm and visual navigation in graphs both extended with support for automatic personalization based on user context also taking advantage of a user’s social network. The proposed solution is primarily evaluated in the domain of scientific publications, i.e. digital libraries, with possible extensions to other application domains. 1

Due to complexity, modern visualization techniques for large data volumes and complex interrelationships are difficult to understand for non-expert users and even for expert users the visualization result may be difficult to interpret. Often the limited screen space and the risk of occlusion hinders a meaningful explanation of techniques or datasets by additional visual elements. This paper presents a novel way how views from information visualization can be adapted by the use of the well-known illustrative technique ”exploded view”, to successfully face the problems described above. The application of exploded views gains screen space for an explanation in a smart way and acts explanatory itself. With our approach of illustrating visual representations, the understanding of complex visualization techniques is eased and new comprehensible views on data are given. 1.

Abstract — The necessity of incorporating experts from various domains in order to understand and draw meaningful conclusions from complex and massive amounts of data is an undisputed fact. In order to create and effectively use such a collaborative information workspace it is vital to understand the interaction processes involved. Established, high-level interaction patterns work well for single user, single data source scenarios. However, they cannot simply be applied to the collaborative analysis of heterogeneous data. In this paper we propose a Multi-User Multi-Level Interaction concept which differentiates between operations in view and data domain while considering the relations and transitions between data on different levels of granularity. Hence, the users ’ interaction can be formalized as a seamless path of navigation. This in turn helps to gain a deeper understanding of the interaction process and allows to efficiently steer it to accelerate data analysis. We demonstrate the applicability and benefits of our concept by means of a clinical use case scenario which aims at finding the best treatment for cancer patients. Index Terms—Interaction, Information Seeking Mantra, visual analysis, collaboration, multi-display environment. 1

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