In 2017, EuroVis will be organized in Barcelona. Hosted by the ViRVIG Group of the Universitat Politécnica de Catalunya. This year will be the 19th edition. EuroVis is the annual Visualization Conference organized by the Eurographics Working Group on Data Visualization and supported by the IEEE Visualization and Graphics Technical Committee (IEEE VGTC). It has been a Eurographics and IEEE co-supported international visualization symposium held in Europe annually since 1999. Since 2012 EuroVis is a conference. The exciting and vibrant field of Visualization is an increasingly important research area due to its wide range of applications in many disciplines. In general, our ability to collect, store, and archive data vastly exceeds our ability derive useful knowledge and insight from it. This is a ubiquitous problem. Data visualization is key in gaining an understanding large, complex data sets by exploiting the human visual system. Data visualization leverages computer graphics in order to provide a visual overview, explore, analyze, and present phenomena which is often difficult to understand.

The objective of the EuroVis conference is to create and strengthen connections between visualization researchers and practitioners, to foster collaborations, and to draw more researchers in Europe to enter this rapidly growing area of research. EuroVis has an expanded scope to include all areas of visualization, and a steadily more wide-spread visibility that allows to achieve a more wide-spread impact.

EuroVis papers are published as a special issue of Computer Graphics Forum, the International Journal of the Eurographics Association.

See you in Barcelona!

Isabel Navazo
Pere-Pau Vázquez


INVITED SPEAKERS
The EuroVis 2017 in Barcelona is proud to announce the following invited speakers:

Martin Wattenberg & Fernanda Viégas (Google)
Visualization: The secret weapon for machine learning. Machine learning is playing an increasingly influential role in the world, due to dramatic technical leaps in recent years. But these new developments bring their own questions. What is the best way to train models and to debug them? How can we understand what is going on under the hood of deep neural networks? It turns out that visualization can play a central role in answering these questions. We'll discuss recent work that shows how interactive exploration can help people use, interpret, and learn about machine intelligence. This talk will be an invitation, aimed at visualization experts, to the field of machine learning. About the presenters. Fernanda Viégas and Martin Wattenberg are the leaders of Google’s “Big Picture” data visualization group, part of Google Brain. Their work in machine learning focuses on transparency and interpretability, as part of a broad agenda to improve human/AI interaction. They are well known for their contributions to social and collaborative visualization, and the systems they’ve created are used daily by millions of people. Their visualization-based artwork has been exhibited worldwide, and is part of the permanent collection of Museum of Modern Art in New York.
Helwig Hauser (U. of Bergen)
From One to Many in Visualization. A lot of interesting development has been happening in visualization research in the past 25 years. Certain topics, like medical visualization, flow visualization, tabular data visualization, and network visualization have attracted continued interest over many years and every year fascinating new findings are presented. We focus on the important work of optimizing our solutions and maturing the field. Every now and then, however, we also see promising chances for radical innovation, for new pioneering research in visualization. In this talk, we take a look at one of these chances, i.e., to transition from the visualization of individual datasets to visually studying large sets of datasets, for example from medical cohort studies or from numerical ensemble simulations. It seems that relevant new visualization challenges arise, when hundreds or thousands of datasets are studied simultaneously—in particular, when these are sets of multi-aspect spatiotemporal datasets. This talk brings up some of the related major questions (for example: how to map to the 2D/3D visualization space), together with examples of related work, and hopefully inspires some bright minds to conduct more visualization research on this topic of increasing relevance. About the presenters. Helwig Hauser graduated in 1995 from Vienna University of Technology in Austria and in 1998 he finished his PhD project on the visualization of complex dynamical systems (flow visualization). In 2003, he got his Habilitation at TU Wien, entitled ''Generalizing Focus+Context Visualization''—in 2006 this work was awarded with the Heinz-Zemanek Award by OCG. Already in 2004, his work on the interactive visual analysis of simulation data won the IEEE Visualization Contest in Austin. In 2013, Helwig Hauser then received the Dirk Bartz Prize for Visual Computing in Medicine from Eurographics (medical ultrasound data visualization). With >190 refereed publications and >7500 citations (h-index ≈ 50), he is an active and respected member of the international visualization research community. Recently, he chaired/hosted several important visualization conferences, including EuroVis 2011, PacificVis 2012, IEEE InfoVis 2013 & 2014, and VCBM 2016 in Bergen, and he has been serving as associate editor for three of the central journals (including IEEE TVCG, CGF, and C&G). After first working for TU Wien as assistant and later as assistant professor (1994–), he changed to the new VRVis Research Center in 2000 (having been one of the founding team, also). There, he led the basic research group on interactive visualization (until 2003) before he became the scientific director of VRVis (–2007). Since then, he is professor in visualization at the University of Bergen in Norway, where he built up a new research group on visualization.