[Infovis] CFP: BigVis : Big Data Visual Exploration and Analytics Intl. Workshop @ EDBT/ICDT

Nikos Bikakis bikakis at imis.athena-innovation.gr
Fri Dec 28 18:47:23 CET 2018

Call for Papers

BigVis 2019 :: 2nd International Workshop on Big Data Visual Exploration and Analytics
   EDBT/ICDT 2019, March 26, 2019, Lisbon, Portugal

Held in conjunction with the 22nd Intl. Conference on Extending Database Technology & 22nd Intl. Conference on Database Theory (EDBT/ICDT 2019)

In the Big Data era, the growing availability of a variety of massive datasets presents challenges and opportunities to not only corporate data analysts but also others, such as research scientists, 
data journalists, policy makers, SMEs, and individual data enthusiasts datasets are typically: accessible in a raw format that are not being loaded or indexed in a database (e.g., plain text, 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 a great 
number of users with little or no support and expertise on the data processing part. The purpose of visual data exploration is to facilitate information perception and manipulation, knowledge 
extraction and inference by non-expert users. Interactive visualization, used in a variety of modern systems, provides users with intuitive means to interpret and explore the content of the data, 
identify interesting patterns, infer correlations and causalities, and supports sense-making activities that are not always possible with traditional data analysis techniques.

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 visual 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 & 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
  - In situ visual exploration and analytics
  - Progressive visual analytics
  - 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)
  - Immersive visualization and visual analytics
  - 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: January 11 2019   **extended**
   Notification: January 22, 2019
   Camera-ready: January 29, 2019
   Deadlines expire at 5pm PT
   Workshop: March 26, 2019

Organizing Committee
   Nikos Bikakis, University of Ioannina, Greece
   Kwan-Liu Ma, University of California-Davis, USA
   Olga Papaemmanouil, Brandeis University, USA
   George Papastefanatos, ATHENA Research Center, Greece

Special Issue
   Extended versions of the best papers of BigVis 2019 will be invited for submission in a special issue of an international journal. (TBA)

Program Committee
   James Abello, Rutgers University, USA
   Demosthenes Akoumianakis, Techn Instit of Crete, Greece
   Gennady Andrienko, Fraunhofer, Germany
   Manos Athanassoulis, Harvard, USA
   Leilani Battle, University of Maryland, USA
   Carsten Binnig, Brown University, UK
   Nan Cao, Tongji University, China
   Maria Beatriz Carmo, Universidade de Lisboa, Portugal
   Giorgio Caviglia, Trifacta Inc
   Wei Chen, Zhejiang University, China
   Rick Cole, Tableau
   Alfredo Cuzzocrea, University of Trieste, Italy
   Aba-Sah Dadzie, The Open University, UK
   Issei Fujishiro, Keio University, Japan
   Giorgos Giannopoulos, ATHENA Research Center, Greece
   Parke Godfrey, University of York, Canada
   Daniel Goncalves, University of Montpellier, France
   Michael Gubanov, University of Texas at San Antonio, USA
   Marcel Hlawatsch, University of Stuttgart, Germany
   Yifan Hu, Yahoo!
   Christophe Hurter, ENAC, France
   Eser Kandogan, IBM
   Anastasios Kementsietsidis, Google
   James Klosowski, AT&T Research
   Stephen G. Kobourov, University of Arizona, USA
   Georgia Koutrika, ATHENA Research Center, Greece
   Giuseppe Liotta, University of Perugia, Italy
   Guoliang Li, Tsinghua University, China
   Zhicheng Liu, Adobe
   Steffen Lohmann, Fraunhofer, Germany
   Marios Meimaris, ATHENA Research Center, Greece
   Davide Mottin, Hasso Plattner Institute, Germany
   Martin Nollenburg, Vienna University of Technology, Austria
   Chris North, Virginia Tech, USA
   Paul Parsons, Purdue University, USA
   Laura Po, Unimore, Italy
   Neoklis Polyzotis, Google
   Gerik Scheuermann, University of Leipzig, Germany
   Tobias Schreck, Graz University of Technology, Austria
   Thibault Sellam, Columbia University, USA
   Mike Sips, GFZ, Germany
   Dimitrios Skoutas, ATHENA Research Center, Greece
   Kostas Stefanidis, University of Tampere, Finland
   Cagatay Turkay, City University London, UK
   Yannis Tzitzikas, University of Crete, Greece
   Panos Vassiliadis, University of Ioannina, Greece
   Chaoli Wang, University of Notre Dame, USA
   Kai Xu, Middlesex University, UK
   Hongfeng Yu, University of Nebraska-Lincoln, USA

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