Call for Papers

BigVis 2019 :: 2nd International Workshop on Big Data Visual Exploration and 
Analytics
  https://bigvis.imsi.athenarc.gr/bigvis2019
  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
Submissions
-------------------------------
 - 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 4, 2019
  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. (confirmation 
awaiting)



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 Nöllenburg, Vienna University of Technology, Austria
  Chris North, Virginia Tech, USA
  Paul Parsons, Purdue University, USA
  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
--
:nikos

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