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Interactive visualizations for exploring and retrieval have not yet become an integral part of digital libraries and information retrieval systems. We have integrated a set of interactive graphics in a real world social science digital library. These visualizations support the exploration of search queries, results and authors, can filter search results, show trends in the database and can support the creation of new search queries. The use of weighted brushing supports the identification of related metadata for search facets. We discuss some use cases of the combination of IR systems and interactive graphics. In a user study we verify that users can gain insights from statistical graphics intuitively and can adopt interaction techniques.An upcoming discipline is the research field of human-computer information retrieval (HCIR), which brings together different aspects of IR and human-computerinteraction to enrich studies and design of IR systems [10]. Actively involving humans into the search process would bring more human intelligence and control into the search process. From the HCIR viewpoint humans should be a central part in the design of IR systems that allow a continuous human control with highly interactive and user-friendly environments. This is associated with retrieval supporting techniques like interactive query expansion, faceted search and navigation, relevance feedback, analytics and visual representation. The visual representation of information is one of the key aspects of HCIR as it shifts complex informations to a more useraccessible form. The features of different visualizations are used to make information quickly processable and to give insights that could not be recognized without the visual processing of data. For example, information of co-authorships can be easier recognized in a network graph than in a textual representation as links between several authors can be seen and processed immediately.Graphics have been used for different aspects of DL like visualization of metadata, queries, results, documents, co-authors and citations. Visualization types include tables [9][7], time lines [8], graphs [11], networks graphs [6] and topic maps [15]. Most recent tools are BiblioViz [13], PaperLens [9], PaperCube [3] and INVISQUE [16]. Most of these tools have in common that they provide an alternative view and access to a document corpora, but are not integrated in the standard search fieldresult list paradigm of Digital Libraries. Gopubmed [2] is a semantic-based search engine for medical papers. Analog to our solution it offers statistical visualizations in the search results for the actual query. Gopubmed shows facet information like top authors, terms, journal, years, cities and countries in lists with integrated bar charts. Publication counts per year are shown in a bar chart to see the distribution of documents over time. A world map shows location facets and a network graph shows collaboration among top authors. User interactivity is limited to items in the lists; these can be clicked to ...

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