The Blockbuster system is a stand-alone Java application, which was developed entirely by the Human-Computer Interaction Group (WG HCI) at the University of Konstanz. The system architecture and design rationale is based on the visual search system for digital libraries “MedioVis”, which has been developed at the WG HCI since 2003 (http://hci.uni-konstanz.de/MedioVis). For the InfoVis 2007 Contest newly developed visualizations, interaction techniques and visualization components (e.g. parallel bargrams, network visualization, visualization- and layout-management with “drag and drop”, multiple document interface with tab browsing…) were integrated. Furthermore Blockbuster uses open source libraries for web browser integration (JDesktop Integration Components JDIC, http://jdic.dev.java.net), database connectivity (PostgreSQL JDBC driver, http://jdbc.postgresql.org) and graph visualization (Java Universal Network/Graph Framework, http://jung.sourceforge.net).
Please find the Blockbuster video under http://hci.uni-konstanz.de/Blockbuster/InfoVis_Final.mov
Download the 2-page summary under http://hci.uni-konstanz.de/Blockbuster/Paper_InfoVis2007Contest_Blockbuster.pdf
Like any user interface and interaction design process, designing information visualization should follow an end-user-centered approach, not only limited to pragmatic qualities like usability (respectively effectiveness and efficiency ) but also in regard to "hedonic” qualities  like aesthetics , "joy-of-use" or pleasurable design .
To achieve a rich and pleasing user experience the forerunner of Blockbuster "MedioVis" was developed following a holistic user-centered design process and was continuously tested with real end-users in usability labs and with large-scale observation of real work practice in the Library of the University of Konstanz through logging and analysis of interaction data. The knowledge gained from these user evaluations has been used to iteratively improve the interaction and user interface design of the system. The superiority by means of effectiveness, usability and attractiveness was empirically validated in user tests and published in . Based on these insights and experiences gained from "MedioVis" we have formulated a design rationale for Blockbuster that has served as a guideline for the system design and as a heuristic for evaluating the system's user experience throughout development.
With respect to the pragmatic qualities of Blockbuster there are two design principles, which have been considered during the selection of employed visualization techniques and their integration into the consistent interaction paradigm of the system:
With respect to aesthetic and emotional aspects of Blockbuster there are two design principles, which were considered during the user interface and interaction design:
Following this design rationale we created a system aimed at demonstrating the potential of information visualization for end-user- or consumer-centered applications that blur the boundaries of information visualization, visual information seeking and browsing. Like Blockbuster's forerunner "MedioVis" the system illustrates how visualization techniques can support novice users in decision making and also how interactive visualization techniques could be used in a consumer-oriented context like e-commerce or information retrieval on the Web.
As decribed in the above design principles, the exploration of data within Blockbuster is based on the usage simultaneous views on the data set, which are linked by linking and brushing behavior. This allows identifying, focusing and selecting single data sets by complementary use of different visualization techniques. All these visualization combinations and their layout are organized on tabbed panes similar to a multiple-document interface with tab browsing known from state-of-the-art internet browsers. This way Blockbuster allows an easy switching between views and data subsets to allow the user to switch between her different tasks and to keep interesting views or intermediate results during the exploration process.
In Blockbuster all views within a tab are synchronized and allow mutual filtering of data. If the user reduces the amount of data in one visualization (e.g. by drawing a bounding box into the scatter plot and zooming into it or by selecting filtering criteria in the bargrams visualization), the data will be instantly removed from all other views on the tab. This way the consequences of filtering in one spot can be interpreted by looking at the effect on the other visible visualizations, which is especially helpful to identify and select data sets for further exploration or adding them to the user's "favorites".
Effective exploration within the individual visualizations is especially facilitated by the possibility for the user to freely assign film metadata to the visualization, e.g. to the axis of the scatter plot, to columns in the HyperGrid or to the attributes displayed in the parallel bar grams.
Following four visualization techniques were integrated into the Blockbuster system and can be chosen and arbitrarily arranged for complementary use to explore the data according to the user’s task:
According to the user-centered approach during the development of Blockbuster, we have selected data specific tasks, which should correspond to those decisions that film producers have to make throughout the process of motion picture production in reality. Hereby we assume that the data of past US movie releases can be regarded as an indicator for the commercial success of future motion pictures and that the user of Blockbuster is interested in producing a film with a good relation between budget and box office revenues. The data used in our scenario contains all US movie releases from 1970 to 2007 from the IMDb and therefore exceeds the amount of data, which was provided for the InfoVis Contest. Furthermore the 32.000 data sets were enriched with additional data available from the publicly available IMDb offline database files. Due to the nature of quantitative data like "budget" or "user rating" we have not addressed missing value issues by sophisticated interpolation or similar strategies.
Task 3.1: Which actors were active in the genres adventure and action in the recent years and have been involved in successful movies? How is their recent success rate compared to that in the past?
Task 3.2: Is there a typical relation between boxoffice gross revenues and rentals revenues?
Task 3.3: Who were the commercially most successful teams among the producers in 2000 to 2005? Who were the teams with the best IMDb ratings?
We would like to thank Werner König and Daniel Klinkhammer for their valuable input and all the contributors to the JDIC and JUNG Java open source projects which made Blockbuster possible.
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