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Ruppert, Tobias; Staab, Michael; Bannach, Andreas; Lücke-Tieke, Hendrik; Bernard, Jürgen; Kuijper, Arjan; Kohlhammer, Jörn

Visual Interactive Creation and Validation of Text Clustering Workflows to Explore Document Collections


Wischgoll, Thomas (Ed.) et al.: Visualization and Data Analysis 2017. Springfield: IS&T, 2017. (Electronic Imaging), pp. 46-57

Visualization and Data Analysis (VDA) <2017, Burlingame, CA, USA>

The exploration of text document collections is a complex and cumbersome task. Clustering techniques can help to group documents based on their content for the generation of overviews. However, the underlying clustering workflows comprising preprocessing, feature selection, clustering algorithm selection and parameterization offer several degrees of freedom. Since no "best" clustering workflow exists, users have to evaluate clustering results based on the data and analysis tasks at hand. In our approach, we present an interactive system for the creation and validation of text clustering workflows with the goal to explore document collections. The system allows users to control every step of the text clustering workflow. First, users are supported in the feature selection process via feature selection metrics-based feature ranking and linguistic filtering (e.g., part-of-speech filtering). Second, users can choose between different clustering methods and their parameterizations. Third, the clustering results can be explored based on the cluster content (documents and relevant feature terms), and cluster quality measures. Fourth, the results of different clusterings can be compared, and frequent document subsets in clusters can be identified. We validate the usefulness of the system with a usage scenario describing how users can explore document collections in a visual and interactive way.

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Maus, Michael; Kuijper, Arjan (Betreuer); Ruppert, Tobias (Betreuer); Lücke-Tieke, Hendrik (Betreuer)

Definition und Visualisierung von zoombaren 2D-Projektionen im Web


Darmstadt, TU, Bachelor Thesis, 2016

Zielsetzung der Arbeit ist die Erforschung und Entwicklung eines web-basierten Visualisierungssystems zum Erstellen und Testen von zoombaren Projektionskarten. Die grundlegende Idee besteht darin einen multidimensionalen Datensatz mithilfe von Projektionsmethoden auf zwei Dimensionen zu projizieren, um sie auf einer 2D-Fläche darzustellen In Anlehnung an die Card, Mackinlay, Shneiderman Visualisierungspipeline ist ein Datenverarbeitungsmodell entwickelt worden. Für die Datenverarbeitung werden verschiedene Distanzmetriken, Dimensionsreduktionsverfahren, Zooming Ansätze sowie Darstellungskonzepte berücksichtigt. Die Besonderheiten sowie Überlegungen der jeweiligen Technologie werden diskutiert. Ein Zooming-Ansatz ermöglicht große Datenmengen auf einer begrenzten Fläche darzustellen. Um Zusammenhänge innerhalb der Daten besser zu visualisieren werden Darstellungskonzepte diskutiert. Die Datenpunkte werden als glyph-basierte Objekte oder mithilfe Colormaps, verschiedenen Formen und Größen dargestellt. Best-Practices über Colormaps werden diskutiert. Um große Datenmengen in Echtzeit darzustellen erfolgt eine Trennung von dem Generierungs- und Visualisierungsprozess. Bei der Generierung werden mithilfe einer tabellarischen Datei und gewählten Konfiguration rechenintensive Transformationsprozesse ausgeführt, um Kartenmaterial zu erzeugen. Ähnlich zu Google-Maps wird das erzeugte Kartenmaterial durch eine Visualisierung dargestellt. Managementkonzepte zur Verwaltung verschiedener Kartensets sowie deren Erzeugung und Darstellung werden präsentiert. Über eine Oberfläche kann der Benutzer Kartenmaterial erzeugen und visualisieren. Der Benutzer lädt eine tabellarische Datei ins System hoch und wählt zwischen verschiedenen Konfigurationsparametern. Anschließend werden diese Informationen verwendet um Kartenmaterial zu erzeugen. Das Kartenmaterial sowie verschiedene Interaktionsmöglichkeiten werden in der Visualisierungsoberfläche bereitgestellt. Anhand verschiedener Anwendungsbeispiele werden die Vorteile dieses Visualisierungssystems präsentiert.

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Ruddle, Roy A.; Bernard, Jürgen; May, Thorsten; Lücke-Tieke, Hendrik; Kohlhammer, Jörn

Methods and a Research Agenda for the Evaluation of Event Sequence Visualization Techniques


IEEE Computer Society Visualization and Graphics Technical Committee (VGTC): IEEE VIS 2016 Workshop on Temporal and Sequential Event Analysis : The Event Event: Temporal & Sequential Event Analysis [online]. [cited 01 February 2017] Available from: [http://eventevent.github.io/], 2016, 4 p.

IEEE VIS 2016 Workshop on Temporal & Sequential Event Analysis <2016, Baltimore, USA>

The present paper asks how can visualization help data scientists make sense of event sequences, and makes three main contributions. The first is a research agenda, which we divide into methods for presentation, interaction & computation, and scale-up. Second, we introduce the concept of Event Maps to help with scale-up, and illustrate coarse-, medium- and fine-grained Event Maps with electronic health record (EHR) data for prostate cancer. Third, in an experiment we investigated participants' ability to judge the similarity of event sequences. Contrary to previous research into categorical data, color and shape were better than position for encoding event type. However, even with simple sequences (5 events of 3 types in the target sequence), participants only got 88% correct despite averaging 7.4 seconds to respond. This indicates that simple visualization techniques are not effective.

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Ruppert, Tobias; Bannach, Andreas; Bernard, Jürgen; Lücke-Tieke, Hendrik; Ulmer, Alex; Kohlhammer, Jörn

Supporting Collaborative Political Decision Making - An Interactive Policy Process Visualization System


Kerren, Andreas (Ed.) et al.: Proceedings of the 9th International Symposium on Visual Information Communication and Interaction : INCI 2016 [online]. ACM, 2016, 8 p.

International Symposium on Visual Information Communication and Interaction (VINCI 2016) < 9, 2016, Dallas, Texas>

The process of political decision making is often complex and tedious. The policy process consists of multiple steps, most of them are highly iterative. In addition, different stakeholder groups are involved in political decision making and contribute to the process. A series of textual documents accompanies the process. Examples are official documents, discussions, scientific reports, external reviews, newspaper articles, or economic white papers. Experts from the politi- cal domain report that this plethora of textual documents often exceeds their ability to keep track of the entire policy process. We present PolicyLine, a visualization system that supports different stakeholder groups in overview-and-detail tasks for large sets of textual documents in the political decision making process. In a longitudinal design study conducted together with domain experts in political decision making, we identfied missing analytical functionality on the basis of a problem and domain characterization. In an iterative design phase, we created PolicyLine in close collaboration with the domain experts. Finally, we present the results of three evaluation rounds, and reect on our collaborative visualization system.

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Ramfos, Antonis; Kiousi, Akrivi; Kokkonidis, Miltiadis; Leclercq, Christophe; Mekkaoui, David; Sattonnay, Maxime; Maragoudakis, Manolis; Androutsopoulou, Aggeliki; Charalabidis, Yannis; Kohlhammer, Jörn; Ruppert, Tobias; Lücke-Tieke, Hendrik; Dimakopoulos, Nikos; Kallipolitis, Leonidas; Nikodem, Pavel; Madlenak, Tomas; Mureddu, Francesco; Pyrenis, Demetrios; Protonotarios, Matthew; Ipektsidis, Charalampos

The "EU Community" Project - Coupling the Power of Data with Community Expertise


Askounis, Dimitros (Ed.) et al.: EEPM 2015 Enabling Effective Policy Making : Proceedings of the Workshop on Enabling Effective Policy Making 2015 -. CEUR-Workshop Proceedings, 2015. (CEUR Workshop Proceedings 1553), 9 p.

Workshop on Enabling Effective Policy Making (EEPM) <2015, Thessaloniki, Greece>

The EU Community project seeks to promote, facilitate, and ultimately exploit the synergy of a cutting-edge intelligent collaboration platform with a community of institutional actors, stakeholders, scientists, consultants, media analysts and other individuals that can make valuable contributions to EU policy debates. Its ultimate goal is to effectuate a transformation in the modus operandi of EU politics and move closer to achieving the illusive goals of improved transparency, efficiency, awareness and engagement, ultimately leading to better policies for a better European Union.

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Ruppert, Tobias; Bernard, Jürgen; Lücke-Tieke, Hendrik; May, Thorsten; Kohlhammer, Jörn

Visual-Interactive Text Analysis to Support Political Decision Making - From Sentiments to Arguments to Policies


Bertini, Enrico (Ed.) et al.: EuroVA 2015 : EuroVis Workshop on Visual Analytics. Goslar: Eurographics Association, 2015, pp. 37-41

International EuroVis Workshop on Visual Analytics (EuroVA) <6, 2015, Cagliari, Sardinia, Italy>

Political decision making involves the evaluation of alternative solutions (so called policy models) to a given societal problem and the selection of the most promising one. Large amounts of textual information to be considered in decision making processes can be found on the web. This includes general information about policy models, individual arguments in favor or against these policies, and public opinions. Monitoring large text collections and extracting the relevant information is time consuming. In this approach we present a visual analytics system that supports users in assessing the results of automatic text analysis methods. The methods extract text segments from large document collections and associate them with predefined policy domains, policy models, and policy arguments. Moreover, sentiment analysis is applied on the text segments. Visualization techniques provide non-IT experts an intuitive access to the results. With the system, users can monitor public debates on the web. In addition, we analyze concepts that enable the user to give visual-interactive feedback on the text analysis results. This direct user feedback can help to improve the accuracy of individual text analysis modules and the credibility of the overall text analysis process. The system was tested with real users from the political decision making domain.

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Steiger, Martin; Lücke-Tieke, Hendrik; May, Thorsten; Kuijper, Arjan; Kohlhammer, Jörn

Deterministic Local Layouts through High-Dimensional Layout Stitching


Kurosu, Masaaki (Ed.): Human-Computer Interaction: Part 1 : Theories, Methods, and Tools. HCI International 2014. Berlin, Heidelberg, New York: Springer, 2014. (Lecture Notes in Computer Science (LNCS) 8510), pp. 643-651

International Conference on Human-Computer Interaction (HCII) <16, 2014, Heraklion, Crete, Greece>

In this paper we present a layout technique for dynamic views of large static graphs. It aims to minimize changes between two consecutive frames and most importantly, it is deterministic. First, a set of small layout patches is pre-computed. Then, depending on the users view focus, a subset of these patches is selected and connected to generate the final layout. In contrast to the state-of-the-art approach that operates in the 2D screen space only, we perform this process in high-dimensional space before projecting the results into the 2D plane. This gives additional degrees of freedom and consequently a smoother transition process between two consecutive frames. Whenever the user visits an area of the graph for a second time, the layout will still look the same. This enables the user to recognize areas that have already been explored and thus preserve the mental map.

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Ruppert, Tobias; Bernard, Jürgen; Lücke-Tieke, Hendrik; Kohlhammer, Jörn

Towards a Tighter Coupling of Visualization and Public Policy Making


Chen, Min (Ed.) et al.: IEEE Conference on Visual Analytics Science and Technology. Proceedings : VAST 2014. Los Alamitos, Calif.: IEEE Computer Society, 2014, pp. 271-272

IEEE Symposium on Visual Analytics Science and Technology (VAST) <9, 2014, Paris, France>

The purpose of this ongoing work is to motivate public policy making as an application area for information visualization and visual analytics. Through our expertise gathered in several policy making related projects, we identified parallels between the benefits of visualization and the needs of evidence-based public policy making. In the following, we will share our previous work consisting of the conceptual introduction of information visualization and visual analytics into the application field of public policy making. Moreover, we will show two real-world cases applying this concept. Finally, we will share identified challenges to be addressed by the information visualization and visual analytics domains in the future.

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Ruppert, Tobias; Bernard, Jürgen; Ulmer, Alex; Lücke-Tieke, Hendrik; Kohlhammer, Jörn

Visual Access to an Agent-based Simulation Model to Support Political Decision Making


Lindstaedt, Stefanie (Ed.) et al.: i-KNOW 2014 : Proceedings of the 14th International Conference on Knowledge Technologies and Data-driven Business. New York: ACM, 2014. (ACM International Conference Proceedings Series 889), Article 16, 8 p.

International Conference on Knowledge Technologies and Data-driven Business (I-KNOW) <14, 2014, Graz, Austria>

Decision making in the field of policy making is a complex task. On the one hand conflicting objectives influence the availability of alternative solutions for a given problem. On the other hand economic, social, and environmental impacts of the chosen solution have to be considered. In the political context, these solutions are called policy options. To tackle societal problems a thorough analysis of policy options needs to be executed before a policy can be put into practice. Computational simulation is a method considered for measuring the impacts of policy options. However, due to their complexity, the underlying models and their output may be difficult to access by decision makers. In this work, we present a visual-interactive interface for an agent-based simulation model that enables decision makers to evaluate the impacts of alternative policy options in the field of regional energy planning. The decision maker can specify different subsidy strategies for supporting public photovoltaic installations as input and evaluate their impact on the actual adoption via the simulation output. We show the usability and usefulness of the visual interface in a real-world example evolved from the European research project ePolicy.

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Steiger, Martin; Bernard, Jürgen; Mittelstädt, Sebastian; Lücke-Tieke, Hendrik; Keim, Daniel A.; May, Thorsten; Kohlhammer, Jörn

Visual Analysis of Time-Series Similarities for Anomaly Detection in Sensor Networks


Computer Graphics Forum, Vol.33 (2014), 3, pp. 401-410

Eurographics Conference on Visualization (EuroVis) <16, 2014, Swansea, Wales, UK>

We present a system to analyze time-series data in sensor networks. Our approach supports exploratory tasks for the comparison of univariate, geo-referenced sensor data, in particular for anomaly detection. We split the recordings into fixed-length patterns and show them in order to compare them over time and space using two linked views. Apart from geo-based comparison across sensors we also support different temporal patterns to discover seasonal effects, anomalies and periodicities. The methods we use are best practices in the information visualization domain. They cover the daily, the weekly and seasonal and patterns of the data. Daily patterns can be analyzed in a clustering-based view, weekly patterns in a calendar-based view and seasonal patterns in a projection-based view. The connectivity of the sensors can be analyzed through a dedicated topological network view. We assist the domain expert with interaction techniques to make the results understandable. As a result, the user can identify and analyze erroneous and suspicious measurements in the network. A case study with a domain expert verified the usefulness of our approach.

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Bernard, Jürgen; Steiger, Martin; Widmer, Sven; Lücke-Tieke, Hendrik; May, Thorsten; Kohlhammer, Jörn

Visual-interactive Exploration of Interesting Multivariate Relations in Mixed Research Data Sets


Computer Graphics Forum, Vol.33 (2014), 3, pp. 291-300

Eurographics Conference on Visualization (EuroVis) <16, 2014, Swansea, Wales, UK>

The analysis of research data plays a key role in data-driven areas of science. Varieties of mixed research data sets exist and scientists aim to derive or validate hypotheses to find undiscovered knowledge. Many analysis techniques identify relations of an entire dataset only. This may level the characteristic behavior of different subgroups in the data. Like automatic subspace clustering, we aim at identifying interesting subgroups and attribute sets. We present a visual-interactive system that supports scientists to explore interesting relations between aggregated bins of multivariate attributes in mixed data sets. The abstraction of data to bins enables the application of statistical dependency tests as the measure of interestingness. An overview matrix view shows all attributes, ranked with respect to the interestingness of bins. Complementary, a node-link view reveals multivariate bin relations by positioning dependent bins close to each other. The system supports information drill-down based on both expert knowledge and algorithmic support. Finally, visual-interactive subset clustering assigns multivariate bin relations to groups. A list-based cluster result representation enables the scientist to communicate multivariate findings at a glance. We demonstrate the applicability of the system with two case studies from the earth observation domain and the prostate cancer research domain. In both cases, the system enabled us to identify the most interesting multivariate bin relations, to validate already published results, and, moreover, to discover unexpected relations.

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Steiger, Martin; Lücke-Tieke, Hendrik; May, Thorsten; Kuijper, Arjan; Kohlhammer, Jörn

Using Layout Stitching to Create Deterministic Local Graph Layouts


Oliveira, Manuel M. (Ed.) et al.: WSCG 2013. Full Papers. Proceedings : The 21st International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision. Plzen: University of West Bohemia, 2013, pp. 1-9

International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision (WSCG) <21, 2013, Plzen, Czech Republic>

Dynamic graph layouts are often used to position nodes in local views of large graphs. These layouts can be optimized to minimize changes when navigating to other parts of the graph. Dynamic graph layout techniques do not, however, guarantee that a local layout is recognizable when the user visits the same area twice. In this paper we present a method to create stable and deterministic layouts of dynamic views of large graphs. It is based on a well-known panorama-stitching algorithm from the image processing domain. Given a set of overlapping photographs it creates a larger panorama that combines the original images. In analogy to that our algorithm stitches pre-computed layouts of subgraphs to form a larger, single layout. This deterministic approach makes structures and node locations persistent which creates identical visual representations of the graph. This enables the user to recognize previously encountered parts and to decide whether a certain part of a dataset has already been explored before or not.

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Lücke-Tieke, Hendrik; May, Thorsten (Betreuer); Kuijper, Arjan (Betreuer)

Stabiles Graph-Layout Basierend auf Lokalen Layouts


Darmstadt, TU, Bachelor Thesis, 2012

Das Ziel einer Datenanalyse ist die Gewinnung von Wissen. Neben der vollautomatischen Analyse ist die interaktive Analyse dieser Daten ein vielversprechender Ansatz, denn sie ermöglicht es, die Vorteile des Menschen gegenüber rein maschinengestützter Verarbeitung zu nutzen. Vorteile wie robuste Wahrnehmung, visuelle Intelligenz und die Fähigkeit zur Entscheidung auf Basis ungenauer Informationen können genutzt werden, um den Wissensgewinn zu beschleunigen. Dies ist allerdings nur nutzbar, wenn umgekehrt der Analyst bei der Entwicklung und Evaluation von Hypothesen unterstützt wird. Eine Form der Unterstützung bietet die grafische Visualisierung von Netzwerken als Diagramme. Diese sogenannten Node-Link-Diagramme stellen Zusammenhänge zwischen Datenpunkten (Nodes) durch Linien (Links) dar, die diese miteinander verbinden. Die Effektivität einer visuellen Analyse mit Hilfe von Node-Link-Diagrammen wird 2 Faktoren stark beeinflusst: die Nachvollziehbarkeit von Zusammenhängen und die Übersichtlichkeit der Visualisierung. Dabei kann die Übersichtlichkeit durch die Menge der dargestellten Daten gesteuert werden. Die Nachvollziehbarkeit von Zusammenhängen hängt hingegen von der Positionierung der Datenpunkte ab. Viele Visualisierungsverfahren für Node-Link-Diagramme betrachten den gesamten Datensatz und erzeugen daraus eine Gesamtdarstellung, ein sogenanntes globales Layout. Dieses globale Layout erleichtert dem Betrachter die Orientierung, denn jeder Datenpunkt befindet sich immer an der gleichen Position. Ein Analyst kann sich so auf den Lageplan in seinem Kopf verlassen, die Visualisierung ist in diesem Sinne stabil. Dies ist allerdings ein Kompromiss auf Kosten der Genauigkeit lokaler Zusammenhänge. Doch genau diese Zusammenhänge können relevant sein und bedürfen daher einer gesonderten Betrachtung ohne Abhängigkeiten oder Einflüsse des restlichen Graphen. Ein solcher, unabhängig berechneter Ausschnitt wird als lokales Layout bezeichnet. Mit Unterstützung von interaktiven Explorationsverfahren kann die Übersichtlichkeit eines Node-Link- Diagramms gewährleistet werden. Dabei erkundet der Benutzer das Netzwerk schrittweise und kann so die Komplexität der Visualisierung steuern. Die statische, interaktive Exploration eines Graphen wird durch Filterung des globalen Layouts realisiert. Die dynamische, interaktive Exploration eines Graphen basiert dagegen auf einem modifizierten lokalen Layout. Mit jeder Änderung des darzustellenden Ausschnitts wird ein neues lokales Layout berechnet, welches dem vorherigen Layout ähnelt. Mit diesem Verfahren können lokale Zusammenhänge übersichtlich und nachvollziehbar visualisiert werden. Aber unterschiedliche Explorationsverläufe resultieren in unterschiedlichen Layouts, der Transfer des Wissens aus einer Exploration auf eine andere Exploration ist schwierig. Gibt es also eine Methode, die die Vorteile beider Verfahren verbinden kann? Eine Methode, die es dem Anwender erlaubt, sich auf seine Orientierung zu verlassen und trotzdem lokale Zusammenhänge des betrachteten Ausschnitts übersichtlich darzustellen? Dieser Frage widmet sich die vorliegende Arbeit. Es wird ein Ansatz zur Verschmelzung von Fotografien auf Node-Link-Diagramme übertragen, so dass 2 lokale Layouts zueinander ausgerichtet und miteinander verschmolzen werden können. Im Anschluss wird dieses Verfahren dann so erweitert, dass auch beliebige Mengen von lokalen Layouts miteinander verschmolzen werden können.