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<div><span style="font-family: arial, sans-serif; font-size: 13px;">IEEE VIS 2014</span></div><div><span style="font-family: arial, sans-serif; font-size: 13px;">http://ieeevis.org</span></div><div><span style="font-family: arial, sans-serif; font-size: 13px;">***************************************</span></div><p><span style="font-family: arial, sans-serif; font-size: 13px;"><div>- Hotel reservation is now open.</div><div>- Registration will open in a week</div><div>***************************************</div><div> </div><div>CALL FOR PARTICIPATION: SIX WORKSHOPS</div><div> </div>* Death of the Desktop – Envisioning Visualization without Desktop Computing</span><br style="font-family: arial, sans-serif; font-size: 13px;" /><span style="font-family: arial, sans-serif; font-size: 13px;">* Provenance for Sensemaking</span><br style="font-family: arial, sans-serif; font-size: 13px;" /><span style="font-family: arial, sans-serif; font-size: 13px;">* DECISIVe : Dealing with Cognitive Biases in Visualisations</span><br style="font-family: arial, sans-serif; font-size: 13px;" /><span style="font-family: arial, sans-serif; font-size: 13px;">* Towards An Open Visualization Literacy Testing Platform</span><br style="font-family: arial, sans-serif; font-size: 13px;" /><span style="font-family: arial, sans-serif; font-size: 13px;">* Visualization for Predictive Analytics</span><br style="font-family: arial, sans-serif; font-size: 13px;" /><span style="font-family: arial, sans-serif; font-size: 13px;">* Visualizing Electronic Health Record Data</span></p><div><br style="font-family: arial, sans-serif; font-size: 13px;" /><div><div style="color: rgb(34, 34, 34); font-family: arial; font-size: small;">For submission deadlines, please see links below.</div><div dir="ltr" style="color: rgb(34, 34, 34); font-family: arial; font-size: small;"> </div><div dir="ltr" style="color: rgb(34, 34, 34); font-family: arial; font-size: small;"> </div><div dir="ltr" style="color: rgb(34, 34, 34); font-family: arial; font-size: small;"><p class="MsoNormal" style="margin: 0px;"><b>Death of the Desktop – Envisioning Visualization without Desktop Computing</b><o:p></o:p></p><p class="MsoNormal" style="margin: 0px;">Yvonne Jansen, Petra Isenberg, Jason Dykes, Sheelagh Carpendale, Sriram Subramanian, Daniel Keefe<o:p></o:p></p><p class="MsoNormal" style="margin: 0px;"><span lang="DE"><span lang="EN-US"><a href="http://beyond.wallviz.dk/" style="color: rgb(17, 85, 204);">beyond.wallviz.dk</a></span></span><o:p></o:p></p><p class="MsoNormal" style="margin: 0px;"><span lang="DE"><br /></span></p><p class="MsoNormal" style="margin: 0px;">The Desktop computer is dead. Monitors sit on desks, unplugged - hosting layers of Post-It notes or gathering dust as a retro emergency low-light mirror. Visualization is colourful, big, tangible, nosy, interactive, compelling and everywhere. It supports all sorts of creative activity and is key to problem solving in education, science, government and industry.<o:p></o:p></p><p class="MsoNormal" style="margin: 0px;">But how?<o:p></o:p></p><p class="MsoNormal" style="margin: 0px;">What is your 'imagined future' for visualization?<o:p></o:p></p><p class="MsoNormal" style="margin: 0px;">We will be exploring possible visualization scenarios with short but rich scenarios in which designers, practitioners and researchers creatively explore opportunities for 'beyond-the-desktop' visualization. We will be discussing these and using them to develop the community’s perspective on the future of VIS.<o:p></o:p></p><p class="MsoNormal" style="margin: 0px;">For the detailed workshop description, submission details, and program please visit the workshop website at beyond.wallviz.dk<o:p></o:p></p></div><div dir="ltr" style="color: rgb(34, 34, 34); font-family: arial; font-size: small;"> </div><div dir="ltr" style="color: rgb(34, 34, 34); font-family: arial; font-size: small;"> </div><div dir="ltr" style="color: rgb(34, 34, 34); font-family: arial; font-size: small;"> </div><div dir="ltr" style="color: rgb(34, 34, 34); font-family: arial; font-size: small;"><p class="MsoNormal" style="margin: 0px;"><b>Provenance for Sensemaking</b><o:p></o:p></p><p class="MsoNormal" style="margin: 0px;">Kai Xu, Simon Attfield, T.J. Jankun-Kelly<o:p></o:p></p><p class="MsoNormal" style="margin: 0px;"><span lang="DE"><a href="http://www.cs.mdx.ac.uk/prov4sense/" style="color: rgb(17, 85, 204);"><span lang="EN-US">http://www.cs.mdx.ac.uk/prov4sense/</span></a></span><o:p></o:p></p><p class="MsoNormal" style="margin: 0px; text-align: justify;"> </p><p class="MsoNormal" style="margin: 0px; text-align: justify;">During complex sensemaking and analysis task, it can be valuable to maintain a history of the processes and transformations involved - referred to as ‘provenance’ information. Provenance information can be a resource for "re<span lang="DE">fl</span>ection-in-action" during analyses, for supporting planning and reframing of objectives and scope. It can also be a resource after the event, supporting the interpretation of claims, audit, accountability or training.<o:p></o:p></p><p class="MsoNormal" style="margin: 0px; text-align: justify;">There has been considerable work on capturing and visualizing of ‘data provenance’, which focuses on data collection and computation, and ‘analytic provenance’, which captures the interactive data exploration process. However, there is limited work of utilizing these provenance information to support sensemaking, in terms of improving its ef<span lang="DE">fi</span>cacy and avoid pitfalls such as data quality issue and human bias.<o:p></o:p></p><p class="MsoNormal" style="margin: 0px; text-align: justify;">This workshop aims to bring together researchers involved in visual analytics and various aspects of sensemaking to consider emerging positions, questions, and <span lang="DE">fi</span>ndings related to the capture, processing, representation and use of provenance information to support complex sensemaking tasks. The emphasis is on discussion and collaboration, with a goal to produce a paper describing the state-of-the-art of provenance for sensemaking after the workshop.<o:p></o:p></p></div><div dir="ltr" style="color: rgb(34, 34, 34); font-family: arial; font-size: small;"> </div><div dir="ltr" style="color: rgb(34, 34, 34); font-family: arial; font-size: small;"> </div><div dir="ltr" style="color: rgb(34, 34, 34); font-family: arial; font-size: small;"> </div><div dir="ltr" style="color: rgb(34, 34, 34); font-family: arial; font-size: small;"><p class="MsoNormal" style="margin: 0px; text-align: justify;"><b>DECISIVe: Dealing with Cognitive Biases in Visualisations</b><o:p></o:p></p><p class="MsoNormal" style="margin: 0px; text-align: justify;"><span lang="DE">Geoffrey Ellis, David Peebles, Donald Kretz, Gaëlle Lortal</span></p><pre><span lang="DE"><a href="http://decisive-workshop.dbvis.de/" style="color: rgb(17, 85, 204);">http://decisive-workshop.dbvis.de/</a></span></pre><p class="MsoNormal" style="margin: 0px; text-align: justify;"><span lang="DE"> </span></p><span style="font-size: 11pt; line-height: 15.693333625793457px; font-family: Calibri;">Our inherent reliance on mental shortcuts, or heuristics, sometimes results in deviations in judgment from what rational decision models would predict. These deviations are known as cognitive biases. Heuristics allow us to make “good enough” decisions without expending all of our cognitive effort on the task, however, in critical decision environments, “good enough” is often NOT good enough. Visualization tools are increasingly adept at making sense of complex data, but researchers who study cognitive biases have come to realize that the quality of decisions made with these tools are often impaired because tool designers fail to address how heuristics and biases operate in a human-computer interactive setting. The aim of this workshop is to bring together a wide range of researchers and developers from domains such as information visualization, visual analytics and cognitive psychology to explore some of the ways in which biases impact user performance and share ideas and experiences about practical ways to reduce or overcome these potentially harmful effects in the systems we build.</span> </div><div dir="ltr" style="color: rgb(34, 34, 34); font-family: arial; font-size: small;"> </div><div dir="ltr" style="color: rgb(34, 34, 34); font-family: arial; font-size: small;"> </div><div dir="ltr" style="color: rgb(34, 34, 34); font-family: arial; font-size: small;"> </div><div dir="ltr" style="color: rgb(34, 34, 34); font-family: arial; font-size: small;"><p class="MsoNormal" style="margin: 0px; text-align: justify;"><b>Towards An Open Visualization Literacy Testing Platform</b><o:p></o:p></p><p class="MsoNormal" style="margin: 0px;">Sung-Hee Kim, Jeremy Boy, Sukwon Lee, Ji Soo Yi, and Niklas Elmqvist<o:p></o:p></p><p class="MsoNormal" style="margin: 0px;"><span lang="DE"><span lang="EN-US" style="font-size: 11.5pt; line-height: 16.406665802001953px; font-family: Arial;"><a href="http://visualizationliteracy.org/" style="color: rgb(17, 85, 204);">http://visualizationliteracy.org</a></span></span><o:p></o:p></p><p class="MsoNormal" style="margin: 0px;"><span lang="DE"><br /></span></p><span style="font-size: 11pt; line-height: 15.693333625793457px; font-family: Calibri;">We propose a hands-on workshop where participants will learn about and discuss visualization literacy by actually designing and evaluating questions for a visualization literacy measure. Though the value of information visualization is becoming apparent to a broad audience, visualization researchers often acknowledge that people have different levels of understanding of visualization techniques. In other words, our understanding of how users interpret visualizations has not caught up with design and technical developments, and even the concept of visualization literacy is still debated. Different domains of research, such as mathematics education, cognitive science, and psychology, have been approaching this problem within their domain. We believe that researchers in information visualization and visual analytics should lead the effort in defining the concept, and in creating valid and practical measurement tools. The goal of our workshop is to take a step in this direction by developing a better understanding of visualization literacy, identifying possible metrics for evaluation, and raising new questions for future research through the design and evaluation of visualization literacy tests. The outcome of our workshop will be a participatory web-platform for collectively created visualization literacy tests and questionnaires that can directly be used by researchers in our community.</span> </div><div dir="ltr" style="color: rgb(34, 34, 34); font-family: arial; font-size: small;"> </div><div dir="ltr" style="color: rgb(34, 34, 34); font-family: arial; font-size: small;"> </div><div dir="ltr" style="color: rgb(34, 34, 34); font-family: arial; font-size: small;"> </div><div dir="ltr" style="color: rgb(34, 34, 34); font-family: arial; font-size: small;"><p class="MsoNormal" style="margin: 0px; text-align: justify;"><b>Visualization for Predictive Analytics</b><o:p></o:p></p><p class="MsoNormal" style="margin: 0px; text-align: justify;">E. Bertini, A. Perer, R. Maciejewski, J. Sun<o:p></o:p></p><p class="MsoNormal" style="margin: 0px; text-align: justify;"><span lang="DE"><a href="http://predictive-workshop.github.io/" style="color: rgb(17, 85, 204);"><span lang="EN-US">http://predictive-workshop.github.io</span></a></span><o:p></o:p></p><p class="MsoNormal" style="margin: 0px; text-align: justify;"><o:p> </o:p></p><p class="MsoNormal" style="margin: 0px;">One of the surprising facts of much current visualization research is that prediction does not often play a significant role. Most visualization research seems to focus exclusively on data analysis and presentation, with little support for predictive analytics and the numerous models researchers have developed for this purpose. Upon reflection, this comes as a surprise as many scientific endeavors and many business problems are mostly concerned with prediction. Looking more closely at the recent advancements (and tremendous popularity) of Data Science, one may recognize that the vast majority of problems addressed involve some form of prediction and modelling. Notable examples are: prediction of drug effectiveness in drug development, prediction of diseases in healthcare, prediction of crime in city management.<o:p></o:p></p><span style="font-size: 11pt; line-height: 15.693333625793457px; font-family: Calibri;">Our goals are to increase the awareness about this interesting opportunity for visualization research, collect and compare examples of existing and ongoing research in this area and to for visual analytics researchers. The workshop will allow participants to showcase their existing research and ideas and to learn and reflect on the latest advances in visualization of predictive models. </span></div><div dir="ltr" style="color: rgb(34, 34, 34); font-family: arial; font-size: small;"><span style="font-size: 11pt; line-height: 15.693333625793457px; font-family: Calibri;"><br /></span></div><div dir="ltr" style="color: rgb(34, 34, 34); font-family: arial; font-size: small;"><span style="font-size: 11pt; line-height: 15.693333625793457px; font-family: Calibri;"><br /></span></div><div dir="ltr" style="color: rgb(34, 34, 34); font-family: arial; font-size: small;"><span style="font-size: 11pt; line-height: 15.693333625793457px; font-family: Calibri;"><br /></span></div><div dir="ltr" style="color: rgb(34, 34, 34); font-family: arial; font-size: small;"><p class="MsoNormal" style="margin: 0px; text-align: justify;"><b>Visualizing Electronic Health Record Data</b><o:p></o:p></p><p class="MsoNormal" style="margin: 0px;">Catherine Plaisant, Silvia Miksch, Theresia Gschwandtner, Sana Malik<o:p></o:p></p><p class="MsoNormal" style="margin: 0px;"><span lang="DE"><span lang="EN-US"><a href="http://www.cs.umd.edu/hcil/parisehrvis" style="color: rgb(17, 85, 204);">http://www.cs.umd.edu/hcil/parisehrvis</a></span></span><o:p></o:p></p><p class="MsoNormal" style="margin: 0px;"><span lang="DE"><br /></span></p><p class="MsoNormal" style="margin: 0px; text-align: justify;">Electronic Health Record (EHR) databases contain millions of patient records including events such as diagnoses, test results, or medication prescriptions. These records are an invaluable data source for clinical research and improvement of clinical quality, as they provide longitudinal health information about patient populations. The use of EHR databases could be dramatically improved if easy-to-use interfaces allowed clinical researchers and quality improvement analysts to explore complex patterns in order to build and test hypotheses regarding the benefits, risks, and appropriateness of treatments or medication regimens.<o:p></o:p></p><p class="MsoNormal" style="margin: 0px; text-align: justify;"><o:p> </o:p></p><p class="MsoNormal" style="margin: 0px; text-align: justify;">Novel strategies in information visualization and visual analytics are needed. The interest in this topic is growing at very rapid pace and is very interdisciplinary by nature, both in term of field (medicine and computer science) but also research environment (academic research as well as industry and government agencies). Because of the European location of the conference, we have a unique opportunity to create bridges and explore new collaborations between groups that would have never met otherwise.<o:p></o:p></p></div><div dir="ltr" style="color: rgb(34, 34, 34); font-family: arial; font-size: small;"> </div><div dir="ltr" style="color: rgb(34, 34, 34); font-family: arial; font-size: small;"> </div><div dir="ltr" style="color: rgb(34, 34, 34); font-family: arial; font-size: small;"> </div><div dir="ltr" style="color: rgb(34, 34, 34); font-family: arial; font-size: small;"><div style="font-family: arial, sans-serif; font-size: 13px;">VIS'14 WORKSHOP CHAIRS</div><div style="font-family: arial, sans-serif; font-size: 13px;">Nathalie Henry Riche, Microsoft Research Redmond</div><div style="font-family: arial, sans-serif; font-size: 13px;">Tobias Isenberg, INRIA Saclay – Île-de-France</div><div style="font-family: arial, sans-serif; font-size: 13px;">Tobias Schreck, University of Konstanz</div><div style="font-family: arial, sans-serif; font-size: 13px;">Zoė J. Wood, California Polytechnic</div><div style="font-family: arial, sans-serif; font-size: 13px;"> </div><div style="font-family: arial, sans-serif; font-size: 13px;">For further information, please email <a href="mailto:workshops@ieeevis.org" target="_blank" style="color: rgb(17, 85, 204);">workshops@ieeevis.org</a>.</div><div> </div></div></div></div><BR><hr />Message sent via Atmail Open - http://atmail.org/</HTML>