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it – Information Technology 2015; 57(1): 30–36 DE GRUYTER OLDENBOURG Special Issue Pattreeya Tanisaro, Julius Schöning*, Kuno Kurzhals, Gunther Heidemann, and Daniel Weiskopf Visual analytics for video applications Abstract: In this article, we describe the concept of video visual analytics with a special focus on the reasoning process in the sensemaking loop. To illustrate this con- cept with real application scenarios, two visual analytics (VA) tools are discussed in detail that cover the sense- making process: (i) for video surveillance, and (ii) for eye

DE GRUYTER OLDENBOURG it – Information Technology 2015; 57(1): 1–2 Editorial Daniel Keim* and Tobias Schreck Special Issue on Visual Analytics DOI 10.1515/itit-2014-1084 Visual Analytics is the science of analytical reasoning sup- ported by interactive visual interfaces. Researchers in this fast growing field regularly consider the design, imple- mentation, application and evaluation of methods that tightly integrate techniques from data analysis and in- teractive data visualization, with the aim of solving real- world analysis problems. Visual Analytics research

M. Koch, A. Butz & J. Schlichter (Hrsg.): Mensch und Computer 2014 Workshopband, München: Oldenbourg Wissenschaftsverlag, 2014, S. 55-62. Visual Analytics für Smart Data Ariane Sutor Corporate Technology, Business Analytics and Monitoring, Siemens AG Zusammenfassung Die Verfügbarkeit großer Mengen an Daten und die technischen Möglichkeiten zur Speicherung und Verarbeitung ermöglichen neue Geschäftsmodelle im industriellen Umfeld. Wichtig ist hier nicht nur die Menge der Daten, vielmehr wird durch das Zusammenbringen von Domänenwissen aus den indus

Visual Analytics in der Studienverlaufsplanung Annette Baumann, Maximilian Endraß, Arturo Alezard IT Service Zentrum, TU München Zusammenfassung Dieser Beitrag stellt kleine studentische Projekte zu Visualisierungen von Studienverlaufsdaten vor. Mit Visual Analytics Elementen werden aus den aggregierten Studienverläufen der Studierenden eines Studiengangs tiefere Einblicke in die Modulbelegung gewonnen. Diese sollen zum einen die Studieren- den in der Informations- und Auswahlphase bei ihrer individuellen Studienplanung und zum anderen die Lehrenden

Nie- derlanden, aber nur 26.000 Nachrichten in Deutschland verfasst. In diesem Artikel soll gezeigt werden, dass interaktive Techniken zur explorati- ven Analyse geeignet sind, um trotz der vergleichsweise dünnen Datenlage in Deutschland eine realistische Perspektive für eine fortschrittliche Lageeinschät- zung zu bieten. Im noch relativ jungen Forschungsfeld Visual Analytics (Keim et al. 2010) werden Verfahren entwickelt, welche eine automatisierte Verarbeitung der Echtzeit-Datenströme ermöglichen und gleichzeitig von der Erfahrung und Einschätzung eines

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humanities as well as the more familiar disciplines of human-computer interaction, ar- tificial intelligence and computer graphics. This paper describes how the new science of visual analytics has built upon the in- terdisciplinary conversations that events such as Smart Graphics began. This new field of research holds a great deal of promise for a variety of application areas, and serves as an example of how the Smart Graphics approach can support other emerging fields of study. Zusammenfassung Je weiter sich die Informatik als Forschungsgebiet entwickelt, desto

analysis of these datasets poses massive challenges. In order to make use of the produced terabytes of data, these datasets need to be integrated, need to be mapped onto existing biological knowledge, and need to be explored by experts. We present UniPAX and BiNA, a scalable system for the integration and analysis of high-throughput data (ge- nomics, transcriptomics, proteomics, and metabolomics) in a network context. A central data warehouse holds the core dataset. A flexible middleware can execute custom queries on this dataset and communicate with our visual analytics

patient subgroups, but also to enable stakeholders to comprehend the processes underlying those subgroups. This comprehension of disease processes underlying patient subgroups enables stakeholders to design interventions that are targeted for each subgroup. Bipartite network analysis and visualization One approach that achieves the goals of analysis and comprehension of multivariable relationships is unsupervised bipartite networks [ 17 ]. Network visualization and analysis [ 17 ] is an advanced form of visual analytics defined as “the science of analytical reasoning

analysis of short, noisy, fragmented, and often subjective textual data still remains a challenge. Typically, the human analyst needs to be actively involved during extraction and modeling to resolve ambiguities that will inevitable arise in such data and to put the model into context. This paper proposes a visual analytics approach that enables a first intuition and exploration of topics appearing in the text corpus, and facilitates the interactive-iterative refinement of the over- all topic model describing the stream of tweets. A second contribution is the discussion

requirements regarding the devel- opment of methods to efficiently integrate varying domain knowledge into theprocesswithout compromising compa- rability of results across subjects or time. Examples from two different strategies are presented and discussed. Keywords: Epidemiology, visual analytics, medical image processing. ACM CCS: Computing methodologies → Artificial intelli- gence → Computer vision → Computer vision problems → Image Segmentation DOI 10.1515/itit-2014-1071 Received July 16, 2014; revised November 3, 2014; accepted Decem- ber 11, 2014 1 Introduction