International Journal on Digital Libraries, Vol.11 (2011), 2, pp. 111-123

Digital Library support for textual and certain types of non-textual documents has significantly advanced over the last years. While Digital Library support implies many aspects along the whole library workflow model, interactive and visual retrieval allowing effective query formulation and result presentation are important functions. Recently, new kinds of non-textual documents which merit Digital Library support, but yet cannot be fully accommodated by existing Digital Library technology, have come into focus. Scientific data, as produced for example, by scientific experimentation, simulation or observation, is such a document type. In this article we report on a concept and first implementation of Digital Library functionality for supporting visual retrieval and exploration in a specific important class of scientific primary data, namely, time-oriented research data. The approach is developed in an interdisciplinary effort by experts from the library, natural sciences, and visual analytics communities. In addition to presenting the concept and to discussing relevant challenges, we present results from a first implementation of our approach as applied on a real-world scientific primary data set. We also report from initial user feedback obtained during discussions with domain experts from the earth observation sciences, indicating the usefulness of our approach.

We present approaches for visualizing uncertainty in an application context through techniques for the visualization of uncertainty. We also describe methods for the reduction of the complexity of the visualization to avoid cognitive overload. Uncertainty in both natural and man-made structures under ground is thus communicated to the user in an appropriate, non threatening manner. The methods were evaluated during an end-user workshop of the research project DeepCity3D. The results of this workshop have led to various extensions to our uncertainty visualization approach in urban management

Procedia Computer Science [online], Vol.7 (2011), pp. 117- 120

Visual analytics is an emerging research discipline aiming at making the best possible use of huge information loads in a wide variety of applications by appropriately combining the strengths of intelligent automatic data analysis with the visual perception and analysis capabilities of the human user. The major goal of visual analytics is the integration of these disciplines into visual analytics to acquire well-established and agreed upon concepts and theories, combining scientific breakthroughs in a single discipline to have a potential impact on visual analytics and vice versa. In a session at FET11, the leaders of the thematic working groups of the recently finalised FET Open coordination action VisMaster CA presented the scientific challenges that were identified in the visual analytics research roadmap, and the connection between the various disciplines and the broader vision of visual analytics. This article contains excerpts from this research roadmap to motivate further research in this direction within FET. © Selection and peer-review under responsibility of FET11 conference organizers and published by Elsevier B.V.

HafenCity University, Hamburg: GeoViz Hamburg 2011 Workshop : Linking Geovisualization with Spatial Analysis and Modeling [online]. [cited 4 April 2011] Available from: http://www.geomatik-hamburg.de/geoviz/program.html 2011, 2 p.

Cities are under constant development. They are characterized not only by their surface constructions like buildings and traffic infrastructure, but also by their underground structures. Besides human-created lifelines, tunnels and quarries, there are also diverse geological formations. Underground information contains a lot of uncertainty by nature, because measurements provide information along drilling lines only. Additionally, man-made structures are often hardly documented. In this paper we will present ways to visualize such uncertainty in combination with exact surface structures from 3D city models in order to assist stakeholders in making decisions. We will evaluate existing techniques and describe the requirements imposed on uncertainty visualization.

Computer Graphics Forum, Vol.30 (2011), 6, pp. 1719-1749

The analysis of large graphs plays a prominent role in various fields of research and is relevant in many important application areas. Effective visual analysis of graphs requires appropriate visual presentations in combination with respective user interaction facilities and algorithmic graph analysis methods. How to design appropriate graph analysis systems depends on many factors, including the type of graph describing the data, the analytical task at hand and the applicability of graph analysis methods. The most recent surveys of graph visualization and navigation techniques cover techniques that had been introduced until 2000 or concentrate only on graph layouts published until 2002. Recently, new techniques have been developed covering a broader range of graph types, such as timevarying graphs. Also, in accordance with ever growing amounts of graph-structured data becoming available, the inclusion of algorithmic graph analysis and interaction techniques becomes increasingly important. In this State-of-the-Art Report, we survey available techniques for the visual analysis of large graphs. Our review first considers graph visualization techniques according to the type of graphs supported. The visualization techniques form the basis for the presentation of interaction approaches suitable for visual graph exploration. As an important component of visual graph analysis, we discuss various graph algorithmic aspects useful for the different stages of the visual graph analysis process. We also present main open research challenges in this field.

Miksch, Silvia (Ed.) et al.: IEEE Conference on Visual Analytics Science and Technology 2011. Proceedings : VAST 2011. New York: IEEE Press, 2011, pp. 111-120

We propose a method for the semi-automated refinement of the results of feature subset selection algorithms. Feature subset selection is a preliminary step in data analysis which identifies the most useful subset of features (columns) in a data table. So-called filter techniques use statistical ranking measures for the correlation of features. Usually a measure is applied to all entities (rows) of a data table. However, the differing contributions of subsets of data entities are masked by statistical aggregation. Feature and entity subset selection are, thus, highly interdependent. Due to the difficulty in visualizing a high-dimensional data table, most feature subset selection algorithms are applied as a black box at the outset of an analysis. Our visualization technique, SmartStripes, allows users to step into the feature subset selection process. It enables the investigation of dependencies and interdependencies between different feature and entity subsets. A user may even choose to control the iterations manually, taking into account the ranking measures, the contributions of different entity subsets, as well as the semantics of the features.

Lalmas, Mounia (Ed.) et al.: Research and Advanced Technology for Digital Libraries : 14th European Conference ECDL. Proceedings. Berlin, Heidelberg, New York: Springer, 2010. (Lecture Notes in Computer Science (LNCS) 6273), pp. 352-363

Digital Library support for textual and certain types of non-textual documents has significantly advanced over the last years. While Digital Library support implies many aspects along the whole library workflow model, interactive and visual retrieval allowing effective query formulation and result presentation are important functions. Recently, new kinds of non-textual documents which merit Digital Library support, but yet cannot be accommodated by existing Digital Library technology, have come into focus. Scientific primary data, as produced for example, by scientific experimentation, earth observation, or simulation, is such a data type. We report on a concept and first implementation of Digital Library functionality, supporting visual retrieval and exploration in a specific important class of scientific primary data, namely, time-oriented data. The approach is developed in an interdisciplinary effort by experts from the library, natural sciences, and visual analytics communities. In addition to presenting the concept and discussing relevant challenges, we present results from a first implementation of our approach as applied on a real-world scientific primary data set.

Keim, Daniel A. (Ed.) et al.: Mastering the Information Age. Solving Problems with Visual Analytics. Goslar: Eurographics Association, 2010, pp. 145-153

This chapter summarises the challenges according to what we believe to be the main entities of visual analytics and then consolidates the recommendations presented in the individual chapters into higher level recommendations for enabling successful visual analytics research. The challenges and recommendations highlight the interdisciplinary nature of visual analytics and the importance of working together. While many initiatives have been started in di erent countries including many EU member states, only under a worldwide and EU-wide umbrella can significant overlap be avoided, and continued strong collaboration between the research groups be fostered.

This book is the result of a community effort of the partners of the VisMaster Coordinated Action funded by the European Union. The overarching aim of VisMaster was to create a research roadmap that outlines the current state of visual analytics across many disciplines, and to describe the next steps that have to be taken to foster a strong visual analytics community, thus enabling the development of advanced visual analytic applications.

Keim, Daniel A. (Ed.) et al.: Mastering the Information Age. Solving Problems with Visual Analytics. Goslar: Eurographics Association, 2010, pp. 1-6

Raw data has no value in itself, only the extracted information has value. Time and money are wasted and opportunities are lost. Success depends on availability of the right information. Visual analytics aims at making data and information processing transparent. Visual analytics combines the strengths of humans and computers.

Keim, Daniel A. (Ed.) et al.: Mastering the Information Age. Solving Problems with Visual Analytics. Goslar: Eurographics Association, 2010, pp. 7-18

Visual analytics is not easy to define, due to its multi-disciplinary nature involving multiple processes and the wide variety of application areas. An early definition was "the science of analytical reasoning facilitated by interactive human-machine interfaces". However, based on current practice, a more specific definition would be: "Visual analytics combines automated Visual analytics combines automated analysis with interactive visualisations analysis techniques with interactive visualisations for an effctive understanding, reasoning and decision making on the basis of very large and complex datasets". So, in terms of the goal of visual analytics, we can elaborate on this definition to state that visual analytics is the creation of tools and techniques to enable people to: - Synthesise information and derive insight from massive, dynamic, ambiguous, and often conflicting data. - Detect the expected and discover the unexpected. - Provide timely, defensible, and understandable assessments. - Communicate these assessment effectively for action

Erleben, Kenny (Ed.) et al.: VRIPHYS 10: 7th Workshop in Virtual Reality Interactions and Physical Simulations. Goslar: Eurographics Association, 2010, pp. 21-29

In the field of garment simulation the resolution of the simulation mesh has a direct impact on visual quality. Unfortunately, an increase in mesh resolution introduces a much higher computational cost and potentially causes instability inside the simulation. In addition, it increases the amount of data sent to the renderer for visualisation. Therefore, a GPU-based refinement of the simulated mesh has several advantages, since all additional data is generated immediately before rendering. This allows an increase in visual quality without adding to computational costs for the simulation process or bandwidth necessary for rendering. In this paper we present a view-dependent, adaptive tessellation method designed for the geometry processing stage of modern GPUs. It uses uniform meshes internally, removing the necessity to store external patches. Since we deal with a local refinement scheme, sudden changes in the mesh structure size on adjacent patches may occur incidentally. To reduce this effect as far as possible, we control the triangle density distribution of the refinement process inside a refined triangle patch.

Institute for Systems and Technologies of Information, Control and Communication (INSTICC): VISIGRAPP 2010. Proceedings : International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications. INSTICC Press, 2010, pp. 246-253

Scene graphs are widely used as a description of spatial relations between objects in a scene. Current scene graphs use linear transformations for this purpose. This limits the relation of two objects in the hierarchy to simple transformations like sheer, translation, rotation and scaling. In contrast to this, we want to represent and control deformations that result from propagating the dynamics of objects to deformable attached objects. Our solution is to replace the linear 4x4 matrix-based transformation of a scene graph by a more generic trilinear transformation. The linear transformation allows the composition of the transformation hierarchy into one transformation. Our approach additionally allows the handling of deformations on the same level. Building on this concept we present a system capable of real-time rendering. The computations of the applied deformations of the scene graph are performed in real-time on the GPU. We allow the approximation of arbitrary nonlinear transformations and deformations by utilising grids of trilinear transformations in our system. As an application we show geometric attachments on deformable objects and their deformation on a scene graph level.

EuroVAST 2010 is the first international symposium on visual analytics science and technology held in Europe. The goal of the symposium is to promote and advance the combination and integration of visualization and analytics methods for the purpose of problem solving in a variety of application domains (engineering, business, public policy, medicine, security, etc). Visual Analytics is the science of analytical reasoning supported by the interactive visual interfaces, which requires interdisciplinary science integrating techniques from visualization and computer graphics, statistics and mathematics, data management and knowledge representation, data analysis and machine learning, cognitive and perceptual sciences, and more.

IM - Die Fachzeitschrift für Information Management & Consulting, Vol.25 (2010), 3, pp. 10-17

Visual Analytics bietet eine Möglichkeit, um große Datenmengen besser zu verstehen. Wissen kann damit aus den gesammelten Unternehmensdaten gewonnen werden. Dieses Wissen kann für Unternehmen einen Wettbewerbsvorteil bedeuten. Bisher werden Unternehmenskennzahlen lediglich mithilfe von statistischen Modellen berechnet. Doch der Bezug zwischen den Daten, den Modellen und den Unternehmenszielen bleibt häufig unklar. Wenn die Visualisierung als wesentlicher Bestandteil des Analyseprozesses eingebunden wird, wird das Verständnis von den Modellen sowie auch von den Daten erhöht. Fehler in den zugrundeliegenden Annahmen können früher behoben werden und neu entdeckte Zusammenhänge können zu sicheren, an Fakten und Zielen überprüfbaren Kennzahlen beim Reporting führen.

Zipf, Alexander (Ed.) et al.: Geoinformatik 2010. Konferenzband : "Die Welt im Netz". Heidelberg: Akademische Verlagsgesellschaft Aka, 2010, pp. 72-80

Modern cities are under constant development. They are characterized not only by their surface constructions like buildings and traffic infrastructure, but also by their underground structures. Besides human-created lifelines, tunnels and quarries, there are also diverse geological formations. All this information is important for a sustainable urban planning and utility management. The DeepCity3D project therefore aims to develop application-adaptive 3D visualization tools that integrate underground data and city models (provided in standardized formats) with advanced functionality to support decision making for stakeholders involved in urban planning, construction companies, insurance companies, architecture, or environmental protection.

Hauser, Helwig (Ed.) et al.: Eurographics 2010. State of the Art Reports (STARs), pp. 113-136

The analysis of large graphs plays a prominent role in various fields of research and is relevant in many important application areas. Effective visual analysis of graphs requires appropriate visual presentations in combination with respective user interaction facilities and algorithmic graph analysis methods. How to design appropriate graph analysis systems depends on many factors, including the type of graph describing the data, the analytical task at hand, and the applicability of graph analysis methods. The most recent surveys of graph visualization and navigation techniques were presented by Herman et al. [HMM00] and Diaz [DPS02]. The first work surveyed the main techniques for visualization of hierarchies and graphs in general that had been introduced until 2000. The second work concentrated on graph layouts introduced until 2002. Recently, new techniques have been developed covering a broader range of graph types, such as time-varying graphs. Also, in accordance with ever growing amounts of graph-structured data becoming available, the inclusion of algorithmic graph analysis and interaction techniques becomes increasingly important. In this State-of-the-Art Report, we survey available techniques for the visual analysis of large graphs. Our review firstly considers graph visualization techniques according to the type of graphs supported. The visualization techniques form the basis for the presentation of interaction approaches suitable for visual graph exploration. As an important component of visual graph analysis, we discuss various graph algorithmic aspects useful for the different stages of the visual graph analysis process.

Kohlhammer, Jörn (Ed.) et al.: EuroVAST 2010 : International Symposium on Visual Analytics Science and Technology. Goslar: Eurographics Association, 2010, pp. 45-50

In this work, we combine KVMaps, a visualization technique presented in [May07] for the visualization of statistical aggregations in multivariate contingency tables, with the measures used for the statistical Chi-Square goodness-of-fit test. Goodness-of-fit tests are used to check whether a given distribution of values matches an expected distribution. A single test statistic is calculated to represent the deviation of the complete dataset. By visualizing the deviations for all entries in the contingency table, it is possible to identify the patterns in the distribution of data items, which contribute most to the overall deviation of the dataset. We present two use cases to illustrate how the information about the patterns can be used.

MacEachren, Alan M. (Ed.) et al.: IEEE Conference on Visual Analytics Science and Technology 2010. Proceedings : VAST 2010. New York: IEEE Press, 2010, pp. 251-252

The visual analysis of video content is an important research topic due to the huge amount of video data that is generated every day. Annotating this data will become a major problem since the amount of videos further increases. With this work we introduce a system that combines a visualization tool with automatic video segmentation techniques and a characteristic key-frame extraction. A summary of the content of a whole video in one view is realized. Furthermore, the user can interactively browse through the video via our visualization interface to get more detailed information. The system is adapted to two application scenarios and a third application is discussed for future work.

Trepte, Sabine (Ed.) et al.: Allgemeinbildung in Deutschland : Erkenntnisse aus dem SPIEGEL-Studentenpisa-Test. Wiesbaden: VS Verlag, 2010, pp. 87-104

Wenn Wissenschaftler Daten (z.B. des Studentenpisa-Tests des SPIEGEL) analysieren, stellen sie gemeinhin Hypothesen auf und überprüfen diese dann. In diesem Beitrag wird ein anderes Verfahren vorgestellt. Es handelt sich um ein exploratives Vorgehen, das es erlaubt, versteckte Zusammenhänge in großen und komplexen Datensammlungen zu finden. Dazu werden die Daten ohne die Formulierung einer bestimmten Fragestellung mittels interaktiver graphischer Darstellungen untersucht. Der Beitrag erläutert diese Herangehensweise und stellt drei Techniken vor, die für diesen Zweck am Fraunhofer-Institut für Graphische Datenverarbeitung in Darmstadt und an der TU Darmstadt entwickelt worden sind. Die Vielzahl von möglichen Aussagen über einen unbekannten Datensatz wird mit diesen und vergleichbaren Techniken auf jene reduziert, die es wert sind, genauer untersucht zu werden.

Tavangarian, Djamshid (Ed.) et al.: Intelligent Interactive Assistance and Mobile Multimedia Computing : International Conference, IMC 2009. Berlin, Heidelberg, New York: Springer, 2009. (Communications in Computer and Information Science 53), p. 131-142

The latest mobile devices are capable of displaying graphical content on larger screens and by increased CPU power offer possibilities for new interesting system approaches and technologies especially in the field of 3D visualization. This paper presents a generic framework for remote visualization on such devices. The presented framework focuses on increased portability and flexibility that goes beyond the results of previous work in this research area. On the server side, existing visualization applications can easily be integrated with and connected to mobile devices. On the client side, the utilization of current standard technologies assures a high portability over a variety of different mobile operating systems and devices.

Hansen, Hans Robert (Ed.) et al.: Business Services: Konzepte, Technologien, Anwendungen Band 1 : 9. Internationale Tagung Wirtschaftsinformatik. Wien: Österreichische Computer Gesellschaft, 2009. (books [at] ocg [dot] at 246), pp. 641-650

This paper introduces a remote visualization approach that enables the visualization of data sets on mobile devices or in web environments. With this approach the necessary computing power can be outsourced to a server environment. The developed system allows the rendering of 2D and 3D graphics on mobile phones or web browsers with high quality independent of the size of the original data set. Compared to known terminal server or other proprietary remote systems our approach offers a very simple way to integrate with a large variety of applications which makes it useful for real-life application scenarios in business processes.

Chen, Min (Ed.) et al.: WSCG 2009. Communication Papers Proceedings. Plzen: University of West Bohemia, 2009, pp. 1-8

In this paper we present a hybrid technique for illuminating a dynamic scene with self shadowing. Our goal is to perform the necessary calculations with real-time or interactive frame rates. The main idea is to split up the self shadowing process into a global and a local part. This separation allows us to choose combinations of completely independent algorithmic approaches. The global part calculates the self shadowing information of the entire scene. Since it has to process the whole scene, it has a high computational cost; however, a coarse approximation can be created in a short time. In contrast the process for the local part deals with fine details, which have local impact on the scene. It only processes a relevant subset of the scene. Finally we present results based on an implementation using a GPU based self shadowing approximation combined with screen space ambient occlusion for solving the local part.

Amicis, Raffaele de (Ed.) et al.: GeoSpatial Visual Analytics : Geographical Information Processing and Visual Analytics for Environmental Security. Berlin: Springer Science+Business Media, 2009. (NATO Science for Peace and Security Series C: Environmental Security), pp. 299-310

The collection and storage of huge amounts of data is no longer a challenge by itself. However, rapidly growing data repositories are creating considerable challenges in many application areas. Visualizations that worked well with a few data items now produce confusing or illegible displays. Decision-makers struggle to act based on a severely restricted understanding of the situation. The goal of Visual Analytics is to overcome this information overload and create new opportunities with these large amounts of data and information. The key challenge is to intelligently combine visualization techniques and analytic algorithms, and to enable the human expert to guide the decision making process. This chapter covers interesting and relevant previous work on situation awareness, naturalistic decision making, and decision-centred visualization. These concepts are put into the context of Visual Analytics research and are further illustrated by application examples.

Pellegrini, Tassilo (Ed.) et al.: Networked Knowledge - Networked Media : Integrating Knowledge Management, New Media Technologies and Semantic Systems. Berlin, Heidelberg, New York: Springer, 2009. (Studies in Computational Intelligence 221), pp. 205-216

In the economic and financial analysis domain a quick access to the right information plays a major role. Using current systems, the search for and presentation of data is very cumbersome. The data, mostly in form of time-series, is stored in various databases. In order to retrieve the searched data, the analysts need to know where to search and sometimes even the structure of the database and its coding. Then it is required to export the data, process the data and create a chart to view the data. This might take time from tens of minutes to hours. In our work we present a first prototype of an integrated search engine that takes as input a natural language query and offers graphic and text output depending on the user task. The system automatically identifies the time-series answers, types of graphical data presentation and shows the results in a web browser and in Excel. The knowledge-based expert system uses domain ontologies for extraction of economic terms in the search queries and specially built data type taxonomy with user task and chart type ontologies for identification of graphic output.

Information Visualization, Vol.8 (2009), 1, pp. 14-29

Visual-interactive cluster analysis provides valuable tools for effectively analyzing large and complex data sets. Due to desirable properties and an inherent predisposition for visualization, the Kohonen Feature Map (or Self-Organizing Map, or SOM) algorithm is among the most popular and widely used visual clustering techniques. However, the unsupervised nature of the algorithm may be disadvantageous in certain applications. Depending on initialization and data characteristics, cluster maps (cluster layouts) may emerge that do not comply with user preferences, expectations, or the application context. Considering SOM-based analysis of trajectory data, we propose a comprehensive visual-interactive monitoring and control framework extending the basic SOM algorithm. The framework implements the general Visual Analytics idea to effectively combine automatic data analysis with human expert supervision. It provides simple, yet effective facilities for visually monitoring and interactively controlling the trajectory clustering process at arbitrary levels of detail. The approach allows the user to leverage existing domain knowledge and user preferences, arriving at improved cluster maps. We apply the framework on a trajectory clustering problem, demonstrating its potential in combining both unsupervised (machine) and supervised (human expert) processing, in producing appropriate cluster results.

This thesis discribes the interplay between usability engineering and information visualization by analyzing the possible intersections between them, conducting an usability evaluation of existing asset planning tools and developing visualization concepts for an asset planning tool using the findings of the thesis.

This thesis discribes the interplay between usability engineering and information visualization by analyzing the possible intersections between them, conducting an usability evaluation of existing asset planning tools and developing visualization concepts for an asset planning tool using the findings of the thesis.

This thesis discribes the interplay between usability engineering and information visualization by analyzing the possible intersections between them, conducting an usability evaluation of existing asset planning tools and developing visualization concepts for an asset planning tool using the findings of the thesis.

ZWF Zeitschrift für wirtschaftlichen Fabrikbetrieb, Vol.103 (2008), 4, pp. 205-208

Seit über 20 Jahren überlassen die Wissenschaftler des FraunhoferInstituts für Graphische Datenverarbeitung IGD Wissensmanagement nicht dem Zufall. Die Forscher erarbeiten intelligente Suchlösungen und Informationsvisualisierungstechnologien und bieten mit ihren Innovationen vielen Unternehmen und Organisationen die Möglichkeit, auf Anforderungen der heutigen dynamischen Informationsgesellschaft schnell reagieren zu können. Die am Fraunhofer IGD entwickelte Software ConWeaver bietet Unternehmen eine semantische und integrierte Suche über Datenbankgrenzen hinweg. Das Suchsystem extrahiert Unternehmenswissen automatisiert aus heterogenen Datenquellen und repräsentiert es in Form multilingualer, semantischer Wissensnetze. Mit der Datenvisualisierung und Informationsanalyse beschäftigt sich die Visual Analytics-Gruppe des Fraunhofer IGD. Die Wissenschafter entwickeln Echtzeitlösungen für die Simulation und die interaktive Visualisierung großer multidimensionaler Daten- und Informationsmengen.

Kerren, A. (Ed.) et al.: Information Visualization : Human-Centered Issues and Perspectives. Berlin, Heidelberg, New York: Springer, 2008. (Lecture Notes in Computer Science (LNCS) 4950), pp. 154-175

We are living in a world which faces a rapidly increasing amount of data to be dealt with on a daily basis. In the last decade, the steady improvement of data storage devices and means to create and collect data along the way influenced our way of dealing with information: Most of the time, data is stored without filtering and refinement for later use. Virtually every branch of industry or business, and any political or personal activity nowadays generate vast amounts of data. Making matters worse, the possibilities to collect and store data increase at a faster rate than our ability to use it for making decisions. However, in most applications, raw data has no value in itself; instead we want to extract the information contained in it.

Is-Report, Vol.12 (2008), 7/8, pp. 20-25

Immens wachsende Datenmengen stellen aktuelle Business-Intelligence-Ansätze und Datenverarbeitungsprozesse vor große Herausforderungen. Visual Business Intelligence bezeichnet die Antwort auf die wachsenden Anforderungen der Benutzer insbesondere im Hinblick auf einen intuitiven, zielführenden und interaktiven Zugang zu großen Mengen an Daten und Informationen. Neue interaktive grafische Darstellungen werden dafür sorgen, dass Entscheider ihr Wissen und ihre Fähigkeiten stärker nutzen können, um diese wachsenden Datenmengen effektiv und effizient auswerten zu können.

IEEE Computer Society: VisWeek 08. Conference Proceedings [DVD-ROM] : VIS - INFOVIS - VAST [DVD-ROM]. Los Alamitos, Calif.: IEEE Computer Society Press, 2008, pp. 108-109

In many business applications, decision makers often have to base their decisions on large amounts of data from various sources. Often, the quality of this data varies substantially, affecting the degree of certainty the analyst can put into the analyzed data values. The data quality measures may be of qualitative or quantitative nature, and consist of one or many dimensions. In this poster paper, we first present a brief survey of currently available uncertainty visualization techniques. We then present experimental results we obtained with several techniques for visualization of multidimensional data quality information, applied on multivariate hierarchic data used in an economic data analysis scenario.

Bebis, George (Ed.) et al.: Advances in Visual Computing. Proceedings Part II : ISVC 2008. Berlin, Heidelberg, New York: Springer, 2008. (Lecture Notes in Computer Science (LNCS) 5359), pp. 31-42

The analytical derivation of a hypothesis is a process, that requires a transformation of information between raw data and an analytical model. Even though much effort has been spent to support the creation of hypotheses both by algorithmic and visual means, much less research has been done on how the process can be reversed for the verification of existing hypotheses. An evaluation of empirical hypotheses must be grounded in raw data and may require many tedious drill-downs, especially for complex data. We present a concept combining an analytical technique for the representation of hypotheses and their transformation into the data-space. We also show visualization techniques for the formalization of the hypothesis in the analytical space and its visual evaluation in the data space. The evaluation is supported by a visual-matchmaking between original raw data and a modification of this data based upon the assumptions implied by the hypothesis.

Computer Graphics Forum, Vol.27 (2008), 3, pp. 911-918

The derivation, manipulation and verification of analytical models from raw data is a process which requires a transformation of information across different levels of abstraction. We introduce a concept for the coupling of data classification and interactive visualization in order to make this transformation visible and steerable for the human user. Data classification techniques generate mappings that formally group data items into categories. Interactive visualization includes the user into an iterative refinement process. The user identifies and selects interesting patterns to define these categories. The following step is the transformation of a visible pattern into the formal definition of a classifier. In the last step the classifier is transformed back into a pattern that is blended with the original data in the same visual display. Our approach allows in intuitive assessment of a formal classifier and its model, the detection of outliers and the handling of noisy data using visual pattern-matching. We instantiated the concept using decision trees for classification and KVMaps as the visualization technique. The generation of a classifier from visual patterns and its verification is transformed from a cognitive to a mostly pre-cognitive task.

Ebert, David S. (Ed.) et al.: IEEE Symposium on Visual Analytics Science and Technology 2008. Proceedings : VAST 2008. New York: IEEE Press, 2008, pp. 3-10

Visual-interactive cluster analysis provides valuable tools for effectively analyzing large and complex data sets. Due to desirable properties and an inherent predisposition for visualization, the Kohonen Feature Map (or Self-Organizing Map, or SOM) algorithm is among the most popular and widely used visual clustering techniques. However, the unsupervised nature of the algorithm may be disadvantageous in certain applications. Depending on initialization and data characteristics, cluster maps (cluster layouts) may emerge that do not comply with user preferences, expectations, or the application context. Considering SOM-based analysis of trajectory data, we propose a comprehensive visual-interactive monitoring and control framework extending the basic SOM algorithm. The framework implements the general Visual Analytics idea to effectively combine automatic data analysis with human expert supervision. It provides simple, yet effective facilities for visually monitoring and interactively controlling the trajectory clustering process at arbitrary levels of detail. The approach allows the user to leverage existing domain knowledge and user preferences, arriving at improved cluster maps. We apply the framework on a trajectory clustering problem, demonstrating its potential in combining both unsupervised (machine) and supervised (human expert) processing, in producing appropriate cluster results.

The International Society for Optical Engineering (SPIE): Electronic Imaging 2008. Proceedings CD-ROM : SPIE Proceedings Volumes 6803-6822. Bellingham: SPIE Press, 2008. (Proceedings of SPIE CDS203), Proc. of SPIE 6809, 10 p.

The analysis of large corporate shareholder network structures is an important task in corporate governance, in financing, and in financial investment domains. In a modern economy, large structures of cross-corporation, cross-border shareholder relationships exist, forming complex networks. These networks are often difficult to analyze with traditional approaches. An efficient visualization of the networks helps to reveal the interdependent shareholding formations and the controlling patterns. In this paper, we propose an effective visualization tool that supports the financial analyst in understanding complex shareholding networks. We develop an interactive visual analysis system by combining state-oft he- art visualization technologies with economic analysis methods. Our system is capable to reveal patterns in large corporate shareholder networks, allows the visual identification of the ultimate shareholders, and supports the visual analysis of integrated cash flow and control rights. We apply our system on an extensive real-world database of shareholder relationships, showing its usefulness for effective visual analysis.

Tochtermann, Klaus (Ed.) et al.: I-KNOW '08 and I-MEDIA '08. Proceedings : International Conferences on Knowledge Management and New Media Technology. Graz: Know-Center, 2008. (J.UCS Journal of Universal Computer Science Special Issue), pp. 332-340

In the economic and financial analysis domain a quick access to the right information plays a major role. Using current systems, the search for and presentation of data is very cumbersome. The data, mostly in form of time-series, is stored in various databases. In order to retrieve the searched data, the analysts need to know where to search and sometimes even the structure of the database and its coding. Then it is required to export the data, process the data and create a chart to view the data. This might take time from tens of minutes to hours. In our work we present a first prototype of an integrated search engine that takes as input a natural language query and offers graphic and text output depending on the user task. The system automatically identifies the time-series answers, types of graphical data presentation and shows the results in a web browser and in Excel. The knowledge-based expert system uses domain ontologies for extraction of economic terms in the search queries and specially built data type taxonomy with user task and chart type ontologies for identification of graphic output.

HCI International 2007. Proceedings and Posters [DVD-ROM] : With 8 further Associated Conferences. Berlin, Heidelberg, New York: Springer, 2007. (Lecture Notes in Computer Science (LNCS)), LNCS 4557, pp. 307-316

The development of an in-store sales support system that focuses on the "virtual try-on" of clothing is the aim of the research project "IntExMa". Based on sophisticated virtual reality technology, the interactive system provides visualization of made-to-measure shirts in combination with digital customer counterparts. The system is intended for seamless integration into existing processes at the point-of-sale and for the support of the collaborative consultation process between salesperson and customer. This paper describes the various system parts stemming from different research disciplines and their integration under the goal of high usability in an everyday setting.

GIS Business, (2007), 1/2, pp. 7-9

Mobile Dienste gelten als einer der Zukunftsmärkte schlechthin. Experten erwarten ein Umsatzwachstum auf bis zu 11 Milliarden Euro im Jahr 2007. Forschungsinstitutionen und Unternehmen arbeiten auf Hochtouren an der Entwicklung neuer Anwendungen. Die Nutzungspotenziale der Geräte als Fremdenführer, Navigationsgerät, Unterhaltungsmedium oder elektronische Geldbörse zeigen den multimedialen Alleskönner - zumindest theoretisch. Praktisch nutzt nur ein verschwindend geringer Anteil der Handybesitzer die mobilen Dienste. Nur neun Prozent rufen mit Ihrem Mobiltelefon E-Mails ab, ganze zwei Prozent nutzen mobile Informationsdienste. Laufen die Entwicklungen also ins Leere? Was müssen Hersteller und Anbieter berücksichtigen, damit etwa mobile Internetdienste bald so populär werden wie es das SMS-Schreiben heute bereits ist? Diese Fragen standen im Mittelpunkt der gemeinsamen Veranstaltung "Mobile Anwendungen der Zukunft" von Fraunhofer-Institut für Graphische Datenverarbeitung und InGeoForum am 14. November 2006 in Darmstadt.

ACM SIGKDD Explorations Newsletter, Vol.9 (2007), 2, pp. 30-37

Visual Analytics seeks to combine automatic data analysis with visualization and human-computer interaction facilities to solve analysis problems in applications characterized by occurrence of large amounts of complex data. The financial data analysis domain is a promising field for research and application of Visual Analytics technology, as it prototypically involves the analysis of large data volumes in solving complex analysis tasks. We introduce a Visual Analytics system for supporting the analysis of large amounts of financial time-varying indicator data. A system, driven by the idea of extending standard technical chart analysis from one to two-dimensional indicator space, is developed. The system relies on an unsupervised clustering algorithm combined with an appropriately designed movement data visualization technique. Several analytical views on the full market and specific assets are offered for the user to navigate, to explore, and to analyze. The system includes automatic screening of the potentially large visualization space, preselecting possibly interesting candidate data views for presentation to the user. The system is applied to a large data set of time varying 2-D stock market data, demonstrating its effectiveness for visual analysis of financial data. We expect the proposed techniques to be beneficial in other application areas as well.

Banissi, Ebad (Ed.) et al.: 11th International Conference on Information Visualization. Proceedings : IV 2007. Los Alamitos, Calif.: IEEE Computer Society, 2007, pp. 101-108

For decades, financial analysts have strived to use modern data visualization tools to improve the timeliness and quality of their analysis. As the amount of data to be processed increases rapidly and requirements on quality of financial analysis rise, the demand for analysis support systems grows. We present a system for the visual analysis of large amounts of time-dependent data using animation. For each data entity, indicators are presented in a scatter-plot framework, displaying the correlation between them. The design of the glyphs illustrates additional data dimensions. The system uses animation to handle the time-dimension of the data. It offers various features, such as focus, zoom, details on demand and time period selection to support the analysis. Financial indicators are used to demonstrate the usability of the system. The animation proves to be a powerful tool for analysing time-dependent processes in cross-sectional data sets and discovering patterns in the data.

Banissi, Ebad (Ed.) et al.: 11th International Conference on Information Visualization. Proceedings : IV 2007. Los Alamitos, Calif.: IEEE Computer Society, 2007, pp. 101-108

For decades, financial analysts have strived to use modern data visualization tools to improve the timeliness and quality of their analysis. As the amount of data to be processed increases rapidly and requirements on quality of financial analysis rise, the demand for analysis support systems grows. We present a system for the visual analysis of large amounts of time-dependent data using animation. For each data entity, indicators are presented in a scatter-plot framework, displaying the correlation between them. The design of the glyphs illustrates additional data dimensions. The system uses animation to handle the time-dimension of the data. It offers various features, such as focus, zoom, details on demand and time period selection to support the analysis. Financial indicators are used to demonstrate the usability of the system. The animation proves to be a powerful tool for analysing time-dependent processes in cross-sectional data sets and discovering patterns in the data.

In ihrem Buch zeigen Bernhard Tritsch und Jörn Kohlhammer, wie man mit etwas Engagement aus Code Bares machen kann. Aus ihrer eigenen Berufspraxis heraus haben sie einen Leitfaden zusammengestellt und erklären, welche Aufgaben zu erledigen sind und mit welchen rechtlichen oder bürokratischen Hürden zu rechnen ist. Alle wichtigen Themen werden angesprochen: von Urheberrechtsfragen und Anforderungen an die Dokumentation über die Auswahl der geeigneten Installationsroutine und des geeigneten Lizenzmodells bis hin zu Marketing, Kundengewinnung, Service und Support.

Computers & Graphics, Vol.30 (2006), 2, pp.284-286

The increasing power of computer, simulation and sensor technologies enables us to produce and store data at ever growing rates. Nevertheless, in virtually every application area, data has no value in itself: In very large amounts, data actually hides the important information and makes information more and more difficult to acquire. Decision makers and analysts are often confronted with vast amounts of complex, seemingly inconsistent or incomplete data, which are derived from a number of heterogeneous sources. The strategic effort of Fraunhofer IGD is pursued in collaboration with other national and international experts in this area. The recent Workshop on Visual Analytics was jointly organized with Prof. Keim, University of Konstanz and received endorsement by Jim Thomas, PNNL, who is head of the extensive Visual Analytics efforts in the United States.

ProSTEP iViP Association: ProSTEP iVip Science Days 2005 : Cross-Domain Engineering. Bobingen: Kessler Verlagsdruckerei, 2005, pp. 232-243

This paper presents a system for virtual prototyping of garments. The garments are constructed using standard 2D tools for pattern design. We present data structures for representing virtual garments, which are used for creating an interface between the 2D pattern construction and 3D garment simulation. The clothing is visualized three-dimensionally on virtual humans. Our system allows interactive draping and adjustment of the virtual garments. The system creates cost savings by reducing the number of real prototypes and decreasing the time-to-market.

ProSTEP iViP Association: ProSTEP iVip Science Days 2005 : Cross-Domain Engineering. Bobingen: Kessler Verlagsdruckerei, 2005, pp. 232-243

This paper presents a system for virtual prototyping of garments. The garments are constructed using standard 2D tools for pattern design. We present data structures for representing virtual garments, which are used for creating an interface between the 2D pattern construction and 3D garment simulation. The clothing is visualized three-dimensionally on virtual humans. Our system allows interactive draping and adjustment of the virtual garments. The system creates cost savings by reducing the number of real prototypes and decreasing the time-to-market.

In dieser Diplomarbeit wurde zur Verbesserung der Visualisierung geopositionierter Informationen das geographische Informationssystem ESRI® ArcGIS® Desktop 9.0 mit der 3D-Analyst® Extension, in das aktuelle DCV-System integriert. Decision-Centered Visualization (DCV) ist ein Ansatz für adaptive und interaktive Visualisierung in zeitkritischen und informationsintensiven Anwendungen. Das Hauptaugenmerk liegt dabei auf dem Hervorheben aufgabenrelevanter Informationen, die zum Situationsbewusstsein eines Benutzers unter Zeitdruck beitragen. In zeitkritischen Anwendungen, wie dem Katastrophenschutz, müssen die verantwortlichen Benutzer Entscheidungen in kürzester Zeit treffen. In solchen Anwendungen ist dabei unter anderem die effektive Visualisierung von Informationen von Bedeutung. Die Benutzeroberfläche des aktuellen DCV-Prototyps besteht aus zwei Darstellungsbereichen (oder Frames), einen für die 2D- und den anderen für die 3D-Darstellung, sowie weitere Informationsfelder von ausgewählten Objekten. Die Schnittstelle zur GIS-Funktionalität wird über die ArcObjects®-Technologie zur Verfügung gestellt. Dabei ersetzt ArcGIS® die bisherige Lösung der Karten- und Terraindarstellung in 2D bzw. 3D. Auf der Benutzeroberfläche von DCV werden die Map Control, die Scene Control und die Toolbar Control eingesetzt, um ArcMap®- und ArcScene®-Dokumente zu laden und zu verarbeiten. Die Toolbar Control bietet dabei das gewohnte Erscheinungsbild und die Funktionalitäten von ArcMap® bzw. ArcScene®. Des Weiteren stehen wichtige GIS-Funktionen wie Rotation, Zoomen oder Auslesen von geographischen Daten zur Verfügung. Durch die Darstellung geographischer Informationen auf der Basis von einzelnen Layern bei ArcGIS® ist die Verwendung für mehrere Anwendungsgebiete gewährleistet, z.B. Stadtkarten als Grundlayer für Anwendungen im Notfallmanagement. Je nach Bedarf können weitere Layer mit benötigten Informationen geladen werden. Layer werden im DCV-System für statische Informationen verwendet. Diese Layer können je nach Situation ein- oder ausgeblendet werden. Dynamische Objekte werden für die temporäre Darstellung in Graphikcontainern hinterlegt. Die Schnittstellen zur GIS-Funktionalität von ESRI® und die zusätzliche DCV-eigene Verknüpfung von Karte und Terrain ermöglicht eine koordinierte Darstellung, mit der es beispielsweise möglich ist, die Kamera des 3D-Terrain automatisch an die Position zu setzen, welche in der 2D-Karte durch den Benutzer angeklickt wurde. Durch die erfolgreiche Integration von ArcGIS® in DCV können somit originalgetreue Karten mit den benötigten geopositionierten Informationen in 2D wie auch in 3D visualisiert werden.

In dieser Diplomarbeit wurde zur Verbesserung der Visualisierung geopositionierter Informationen das geographische Informationssystem ESRI® ArcGIS® Desktop 9.0 mit der 3D-Analyst® Extension, in das aktuelle DCV-System integriert. Decision-Centered Visualization (DCV) ist ein Ansatz für adaptive und interaktive Visualisierung in zeitkritischen und informationsintensiven Anwendungen. Das Hauptaugenmerk liegt dabei auf dem Hervorheben aufgabenrelevanter Informationen, die zum Situationsbewusstsein eines Benutzers unter Zeitdruck beitragen. In zeitkritischen Anwendungen, wie dem Katastrophenschutz, müssen die verantwortlichen Benutzer Entscheidungen in kürzester Zeit treffen. In solchen Anwendungen ist dabei unter anderem die effektive Visualisierung von Informationen von Bedeutung. Die Benutzeroberfläche des aktuellen DCV-Prototyps besteht aus zwei Darstellungsbereichen (oder Frames), einen für die 2D- und den anderen für die 3D-Darstellung, sowie weitere Informationsfelder von ausgewählten Objekten. Die Schnittstelle zur GIS-Funktionalität wird über die ArcObjects®-Technologie zur Verfügung gestellt. Dabei ersetzt ArcGIS® die bisherige Lösung der Karten- und Terraindarstellung in 2D bzw. 3D. Auf der Benutzeroberfläche von DCV werden die Map Control, die Scene Control und die Toolbar Control eingesetzt, um ArcMap®- und ArcScene®-Dokumente zu laden und zu verarbeiten. Die Toolbar Control bietet dabei das gewohnte Erscheinungsbild und die Funktionalitäten von ArcMap® bzw. ArcScene®. Des Weiteren stehen wichtige GIS-Funktionen wie Rotation, Zoomen oder Auslesen von geographischen Daten zur Verfügung. Durch die Darstellung geographischer Informationen auf der Basis von einzelnen Layern bei ArcGIS® ist die Verwendung für mehrere Anwendungsgebiete gewährleistet, z.B. Stadtkarten als Grundlayer für Anwendungen im Notfallmanagement. Je nach Bedarf können weitere Layer mit benötigten Informationen geladen werden. Layer werden im DCV-System für statische Informationen verwendet. Diese Layer können je nach Situation ein- oder ausgeblendet werden. Dynamische Objekte werden für die temporäre Darstellung in Graphikcontainern hinterlegt. Die Schnittstellen zur GIS-Funktionalität von ESRI® und die zusätzliche DCV-eigene Verknüpfung von Karte und Terrain ermöglicht eine koordinierte Darstellung, mit der es beispielsweise möglich ist, die Kamera des 3D-Terrain automatisch an die Position zu setzen, welche in der 2D-Karte durch den Benutzer angeklickt wurde. Durch die erfolgreiche Integration von ArcGIS® in DCV können somit originalgetreue Karten mit den benötigten geopositionierten Informationen in 2D wie auch in 3D visualisiert werden.

In dieser Diplomarbeit wurde zur Verbesserung der Visualisierung geopositionierter Informationen das geographische Informationssystem ESRI® ArcGIS® Desktop 9.0 mit der 3D-Analyst® Extension, in das aktuelle DCV-System integriert. Decision-Centered Visualization (DCV) ist ein Ansatz für adaptive und interaktive Visualisierung in zeitkritischen und informationsintensiven Anwendungen. Das Hauptaugenmerk liegt dabei auf dem Hervorheben aufgabenrelevanter Informationen, die zum Situationsbewusstsein eines Benutzers unter Zeitdruck beitragen. In zeitkritischen Anwendungen, wie dem Katastrophenschutz, müssen die verantwortlichen Benutzer Entscheidungen in kürzester Zeit treffen. In solchen Anwendungen ist dabei unter anderem die effektive Visualisierung von Informationen von Bedeutung. Die Benutzeroberfläche des aktuellen DCV-Prototyps besteht aus zwei Darstellungsbereichen (oder Frames), einen für die 2D- und den anderen für die 3D-Darstellung, sowie weitere Informationsfelder von ausgewählten Objekten. Die Schnittstelle zur GIS-Funktionalität wird über die ArcObjects®-Technologie zur Verfügung gestellt. Dabei ersetzt ArcGIS® die bisherige Lösung der Karten- und Terraindarstellung in 2D bzw. 3D. Auf der Benutzeroberfläche von DCV werden die Map Control, die Scene Control und die Toolbar Control eingesetzt, um ArcMap®- und ArcScene®-Dokumente zu laden und zu verarbeiten. Die Toolbar Control bietet dabei das gewohnte Erscheinungsbild und die Funktionalitäten von ArcMap® bzw. ArcScene®. Des Weiteren stehen wichtige GIS-Funktionen wie Rotation, Zoomen oder Auslesen von geographischen Daten zur Verfügung. Durch die Darstellung geographischer Informationen auf der Basis von einzelnen Layern bei ArcGIS® ist die Verwendung für mehrere Anwendungsgebiete gewährleistet, z.B. Stadtkarten als Grundlayer für Anwendungen im Notfallmanagement. Je nach Bedarf können weitere Layer mit benötigten Informationen geladen werden. Layer werden im DCV-System für statische Informationen verwendet. Diese Layer können je nach Situation ein- oder ausgeblendet werden. Dynamische Objekte werden für die temporäre Darstellung in Graphikcontainern hinterlegt. Die Schnittstellen zur GIS-Funktionalität von ESRI® und die zusätzliche DCV-eigene Verknüpfung von Karte und Terrain ermöglicht eine koordinierte Darstellung, mit der es beispielsweise möglich ist, die Kamera des 3D-Terrain automatisch an die Position zu setzen, welche in der 2D-Karte durch den Benutzer angeklickt wurde. Durch die erfolgreiche Integration von ArcGIS® in DCV können somit originalgetreue Karten mit den benötigten geopositionierten Informationen in 2D wie auch in 3D visualisiert werden.

Users of information systems in timecritical domains are under pressure to digest and process information that is vital for their task. Too often analysts receive the important information buried within a collection of insignificant data and information. Sorting through such a cluttered display and finding the critical information requires a high level of attention and becomes even more challenging with the increasing amounts of information available. Especially in timecritical domains, the problem of information assessment is replaced by the problem of avoiding the timeintensive efforts to review all the available information. The focus of this dissertation was the combination of knowledge representation, information visualization, and human-centered computing to reduce the probability of such information overload, defining the field of decision-centered visualization (DCV). The DCV approach is unique in how it ties together information visualization and knowledge representation in time-critical and information-intensive environments to support the user's situation awareness. The knowledge representation for DCV as it is defined in this thesis corresponds to the conceptual and architectural requirements of DCV to enable decision- centered applications. The goal of this work was a knowledge representation approach that is user-centered, allows scalable information handling, supports knowledge- based information visualization, flexibly supports various kinds of display and presentation systems, and can be realized in a dynamic network environment - all aspects of information systems typically encountered in time-critical domains like air traffic control. Part of the solution introduced in this work was the scalable combination of domain ontologies and domain databases for human-centered and knowledge-based information visualization. The domain ontology as the knowledge structuring element of the representation is integrated with the scalability advantages of databases, together representing the visualization-relevant aspects of a domain. This thesis extends the current information visualization theory by socalled presentation requirements (PRs). PRs allow the abstract analytical description of information, particularly for the support of situation awareness. By describing entity types, their attributes, and relationships between entity types, knowledge about the information in the domain can be combined with knowledge about the necessary information visualization to users under time pressure. This is enabled by using presentation types and data types for the description of information visualization environments, leaning on and extending the current information visualization models with aspects for time-critical and information-intensive domains. With the help of so-called DCV transformations, this work enables the flexible guidance of various display systems by a DCV system tuning the visualization to the current situation, to the task that the user is working working on, and to the role of the user in the current situation. Depending on the needs of the user and the used display system, filtered and prioritized information can be flexibly mapped to visual structures and presented in an effective and efficient way. The results of this work are most applicable to the area of emergency management and are also applied to the field of visual analytics, an integrated field between data mining and information visualization in the area of very information-intensive domains. Here, the presentation requirements enable the reduction of the complexity of the information on an abstract level based on the provided semantics, before any data instances have to be considered.

TESI 2005 Conference Proceedings CD-ROM : Training, Education & Simulation International. [Maastricht], 2005, 7 p.

This paper presents a framework for efficient GIS-based visualization, simulation and interaction in the emergency management context. Especially the inclusion of availability, distribution, and comprehensibility of information in emergency situations are preconditions for efficient decision making and emergency response. Time-critical domains such as emergency management demand fast decisions from expert users under stress. Decision-centered visualization (DCV) is an approach to adaptive, interactive visualization at the intersection of knowledge engineering and information visualization that is focused on visualization and simulation in time-critical domains. DCV and the covered graphics- and sketch-based interaction approach are the two building blocks of a comprehensive system concept for time-critical applications like emergency management.

Availability, distribution, and comprehensibility of information in emergency situations are preconditions for decision making and emergency response. Concise distribution of available information is especially vital for mobile environments, where bandwidth is a scarce source. In addition, time-critical domains, such as emergency management, demand fast decisions from expert users under stress. The Decisioncentered visualization (DCV) approach supports decision making by integrating domain knowledge and knowledge about human situation awareness for time-critical information distribution. Efficient GIS information presentation is vital for the user's situation awareness and, in consequence, to task performance in emergency situations.

Availability, distribution, and comprehensibility of information in emergency situations are preconditions for decision making and emergency response. Concise distribution of available information is especially vital for mobile environments, where bandwidth is a scarce source. In addition, time-critical domains, such as emergency management, demand fast decisions from expert users under stress. The Decisioncentered visualization (DCV) approach supports decision making by integrating domain knowledge and knowledge about human situation awareness for time-critical information distribution. Efficient GIS information presentation is vital for the user's situation awareness and, in consequence, to task performance in emergency situations.

Jardim Nunes, Nuno (Ed.) et al.: International Conference on Intelligent User Interfaces 2004. Proceedings : IUI 2004. New York: ACM Press, 2004, pp. 271-273

Time-critical domains, such as emergency management, demand fast decisions from expert users under stress. Our Decision-Centered Visualization (DCV) system supports decision making by integrating domain knowledge and knowledge about human situation awareness for time-critical visualization. Efficient information presentation is vital for the user's situation awareness and, in consequence, to his or her task performance. We address the problem of efficiently visualizing both existing and incoming information by connecting domain data types and presentation requirements of the domain's tasks.

Villanueva, J.J. (Ed.): Proceedings of the Fourth IASTED International Conference on Visualization, Imaging, and Image Processing. Anaheim: ACTA Press, 2004, pp. 123-128

Continuing advances in communication technologies enable mobile users to access complex functionality like geographic information systems. Extensions to traditional interaction metaphors are needed for visual queries, decision support, and visualization to facilitate better and faster understanding in users accessing geo-spatial information. We focus on two modules of a general mobile GIS software architecture: SketchQuery and decision-centered visualization (DCV). SketchQuery enables users to freely specify graphic- und sketch-based queries in a GIS context, while the DCV approach supports decision making by integrating domain knowledge and knowledge about human situation awareness for effective informaion visualization. Efficient and user-centered interaction with GIS information is vital to the user's performance in mobile environments.

IEEE Systems, Man and Cybernetics Society: IEEE International Conference on Systems, Man and Cybernetics 2003. Proceedings : System Security and Assurance. New York: IEEE Press, 2003, pp. 3905-3911

Users of information systems in time-critical domains are under constant pressure to digest and process information that is vital for their task. Thus, the user needs efficient information visualization that avoids displaying information that is not vital at the moment. Decision-Centered Visualization is an adaptive, interactive visualization system that supports decision making by integrating domain knowledge and knowledge about human decision making with an interactive visualization architecture. An important facet of this system is the representation of the underlying domain knowledge. We will first describe the main modules and the main structures of the knowledge representation of the DCV system. We then describe how DCV uses the represented domain knowledge to guide the information visualization in time-critical applications.

Callaos, Nagib (Ed.) et al.: 7th World Multiconference on Systemics, Cybernetics and Informatics. Proceedings : Volume VI - Informations Systems, Technologies and Applications: Part I. Orlando, Florida: International Institute of Informatics and Systemics, 2003, pp. 409-414

In time-critical domains, such as emergency management or military command and control, users are required to make decisions in highly stressful situations. The Decision-Centered Visualization (DCV) system under development at Fraunhofer CRCG supports decision making by integrating domain knowledge and knowledge about human decision making with an interactive visualization architecture. Naturalistic Decision Making (NDM) models inform the design of the DCV user interface module in order to appropriately supply the decision-maker with the necessary information.

IEEE Computer Society: 16th International Conference on Data Engineering 2000. Proceedings. Los Alamitos, Calif.: IEEE Computer Society, 2000, pp. 379-388

In a data warehouse, updates are typically collected and performed periodically in a batch mode, e.g., over night. This standard approach of bulk incremental updates to data warehouses has some drawbacks. First, the average runtime for a single update is small but the total runtime for the whole batch of updates may become rather large. Second, the contents of the data warehouse is not always up to date. In this paper, we introduce the DC-tree, a fully dynamic index structure for data warehouses modeled as a data cube. This new index structure is designed for applications where the above drawbacks of the bulk update approach are critical. The DC-tree is a hierarchical index structure - similar to the X-tree - exploiting the concept hierarchies typically defined for the dimensions of a data cube. We conducted an extensive experimental performance evaluation using the TPC-D benchmark data. Our results demonstrate that the DC-tree yields a significant speed-up compared to the Xtree and the sequential search when processing general range queries on a data cube.