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BigVis 2018 : International Workshop on Big Data Visual Exploration and Analytics


When Mar 26, 2018 - Mar 26, 2018
Where Vienna
Submission Deadline Dec 25, 2017
Notification Due Jan 22, 2018
Final Version Due Jan 29, 2018

Call For Papers

BigVis 2018 Call for Papers

**Selected papers of the BigVis 2018 will be invited to a Special Issue of the Big Data Research Journal, Elsevier

BigVis 2018 :: International Workshop on Big Data Visual Exploration and Analytics
Vienna, Austria

Held in conjunction with the 21th Intl. Conference on Extending Database Technology & 21th Intl. Conference on Database Theory (EDBT/ICDT 2018)

One the major challenges of the Big Data era is that it has realized the availability of a great amount and variety of massive datasets for analysis by non-corporate data analysts, such as research scientists, data journalists, policy makers, SMEs and individuals. A major characteristic of these datasets is that they are: accessible in a raw format that are not being loaded or indexed in a database (e.g., plain text files, json, rdf), dynamic, dirty and heterogeneous in nature. The level of difficulty in transforming a data-curious user into someone who can access and analyze that data is even more burdensome now for numerous non-expert users.

In the Big Data era, several challenges arise in the field of data visualization and analytics. First, the modern exploration and visualization systems should offer scalable data management techniques in order to efficiently handle billion objects datasets, limiting the system response in a few milliseconds. Besides, nowadays systems must address the challenge of on-the-fly scalable visualizations over large and dynamic sets of volatile raw data, offering efficient interactive exploration techniques, as well as mechanisms for information abstraction, sampling and summarization for addressing problems related to information overplotting. Further, they must encourage user comprehension offering customization capabilities to different user-defined exploration scenarios and preferences according to the analysis needs. Overall, the challenge is to enable users to gain value and insights out of the data as rapidly as possible, minimizing the role of IT-expert in the loop.

The BigVis workshop aims at addressing the above challenges and issues by providing a forum for researchers and practitioners to discuss exchange and disseminate their work. BigVis attempts to attract attention from the research areas of Data Management and Mining, Information Visualization and Human-Computer Interaction and highlight novel works that bridge together these communities.

Workshop Topics
In the context of visual exploration and analytics, topics of interest include, but are not limited to:
- Visualization and exploration techniques for various Big Data types (e.g., stream, spatial, high-dimensional, graph)
- Human-centered database techniques
- Indexes and data structures for data visualization
- Raw data visual exploration and analytics
- Incremental and adaptive processing
- Interactive caching and prefetching
- Scalable visual operations (e.g., zooming, panning, linking, brushing)
- Big Data visual representation techniques (e.g., aggregation, sampling, multi-level, filtering)
- Setting-oriented visualization (e.g., display resolution/size, smart phones, pixel-oriented, visualization over networks)
- User-oriented visualization (e.g., assistance, personalization, recommendation)
- Visual analytics (e.g., pattern matching, timeseries analytics, prediction analysis, outlier detection, OLAP)
- Visual and interactive data mining
- Models of human-in-the-loop data analysis
- High performance/Parallel techniques
- Visualization hardware and acceleration techniques
- Linked Data and ontologies visualization
- Case and user studies
- Systems and tools

- regular research papers (up to 8 pages)
- work-in-progress papers (up to 4 pages)
- vision papers (up to 4 pages)
- system papers and demos (up to 4 pages)

Important Dates
Submission: December 25, 2017
Notification: January 22, 2018
Camera-ready: January 29, 2018
Deadlines expire at 5pm PT
Workshop: March 26, 2018

Organizing Committee
Nikos Bikakis, ATHENA Research Center, Greece
George Papastefanatos, ATHENA Research Center, Greece
Olga Papaemmanouil, Brandeis University, USA

Program Committee
Ioannis Alagiannis, Microsoft
Manos Athanassoulis, Harvard, USA
David Auber, Universite Bordeaux 1, France
Leilani Battle, Univeristy of Maryland, USA
Carsten Binnig, Brown University, UK
Nan Cao, Tongji University, China
Giorgio Caviglia, Trifacta Inc
Remco Chang, Tufts University, USA
Michael Gubanov, University of Texas at San Antonio, USA
Rick Cole, Tableau Software
Aba-Sah Dadzie, The Open University, UK
Giorgos Giannopoulos, ATHENA Research Center, Greece
Parke Godfrey, York University, Canada
Jarek Gryz, York University, Canada
Alexander Hinneburg, MLU, Germany
Marcel Hlawatsch, Universitat Stuttgart, Germany
Bill Howe, University of Washington, USA
Yifan Hu Yahoo! Research
Valentina Ivanova, Linkoping University, Sweden
Vana Kalogeraki, AUEB, Greece
Niranjan Kamat, Ohio State University, USA
Manos Karpathiotakis, EPFL, Switzerland
Manolis Koubarakis, University of Athens, Greece
Danai Koutra, University of Michigan, USA
Georgia Koutrika, ATHENA Research Center, Greece
Steffen Lohmann, Fraunhofer, Germany
Kwan-Liu Ma, University of California at Davis, USA
Suvodeep Mazumdar, University of Sheffield, Sweden
Davide Mottin, Hasso Plattner Institute, Germany
Paul Parsons, Purdue University, USA
Tobias Schreck, Graz University of Technology, Austria
Mariano Rico, UPM, Spain
Thibault Sellam, Columbia University, USA
Mike Sips, GFZ, Germany
Dimitrios Skoutas, ATHENA Research Center, Greece
Kostas Stefanidis, University of Tampere, Finland
Hanghang Tong, Arizona State University, USA
Yannis Tzitzikas, University of Crete, Greece
Panos Vassiliadis, University of Ioannina, Greece

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