CFP: BigVis :: 3rd Big Data Visual Exploration & Analytics workshop @ EDBT 2020, Copenhagen

Call for Papers


BigVis 2020: 3rd International Workshop on Big Data Visual Exploration 
and Analytics
   https://bigvis.imsi.athenarc.gr/bigvis2020
   March 30, 2020, Copenhagen, Denmark

Held in conjunction with the 23rd Intl. Conference on Extending Database 
Technology & 23rd Intl. Conference on Database Theory (EDBT/ICDT 2020)

Information Visualization is nowadays one of the cornerstones of Data 
Science, turning the abundance of Big Data being produced through modern 
systems into actionable knowledge. Indeed, the Big Data era has realized 
the availability of voluminous datasets that are dynamic, noisy and 
heterogeneous in nature. 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. Thus, the area of data visualization, visual 
exploration and analysis has gained great attention recently, calling 
for joint action from different research areas from the HCI, Computer 
graphics and Data management and mining communities.

In this respect, several traditional problems from these communities 
such as efficient data storage, querying & indexing for enabling visual 
analytics, new ways for visual presentation of massive data, efficient 
interaction and personalization techniques that can fit to different 
user needs are revisited. The modern exploration and visualization 
systems should nowadays offer scalable techniques to efficiently handle 
billion objects datasets, limiting the visual response in a few 
milliseconds along with mechanisms for information abstraction, sampling 
and summarization for addressing problems related to visual information 
over-plotting. 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 offer self-service visual analytics, i.e. enable data 
scientists and business analysts to visually gain value and insights out 
of the data as repidly 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, exploration & analytics techniques for various data 
types; e.g., stream, spatial, high-dimensional, graph
  - Human-in-the-loop processing
  - Human-centered databases
  - Data modeling, storage, indexing, caching, prefetching & query 
processing for interactive applications
  - Interactive machine learning
  - Interactive data mining
  - User-oriented visualization; e.g., recommendation, assistance, 
personalization
  - Visualization & knowledge; e.g., storytelling
  - Progressive analytics
  - In-situ visual exploration & analytics
  - Novel interface & interaction paradigms
  - Visual representation techniques; e.g., aggregation, sampling, 
multi-level, filtering
  - Scalable visual operations; e.g., zooming, panning, linking, brushing
  - Scientific visualization; e.g., volume visualization
  - Analytics in the fields of scholarly data, digital libraries, 
multimedia, scientific data, social data, etc.
  - Immersive visualization
  - Interactive computer graphics
  - Setting-oriented visualization; e.g., display resolution/size, smart 
phones, visualization over networks
  - High performance, distributed & parallel techniques
  - Visualization hardware & acceleration techniques
  - Linked Data & ontologies visualization
  - Benchmarks for data visualization & analytics
  - Case & user studies
  - Systems & tools


Submissions
------------------------------------
   Regular/Short Research papers [up to 8/4 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 5, 2020
   Notification: January 24, 2020
   Camera-ready: January 29, 2020
   Workshop: March 30, 2020


Organizing Committee
------------------------------------
   David Auber, University Bordeaux, France
   Nikos Bikakis, University of Ioannina, Greece
   Panos K. Chrysanthis, University of Pittsburgh, USA
   George Papastefanatos, ATHENA Research Center, Greece
   Mohamed Sharaf, United Arab Emirates University, UAE


Special Issue
------------------------------------
Extended versions of the best papers of BigVis 2020 will be invited for 
submission in a Special Issue of the "Big Data Research Journal", 
Elsevier (IF: 2.95)


Program Committee
------------------------------------
   James Abello, Rutgers Univ, USA
   Demosthenes Akoumianakis, Hellenic Mediterranean Univ, Greece
   Gennady Andrienko, Fraunhofer, Germany
   Rick Cole, Tableau
   Alfredo Cuzzocrea, ICAR-CNR & Univ of Calabria, Italy
   Danyel Fisher, Honeycomb.io
   Steffen Frey, Univ of Stuttgart, Germany
   Giorgos Giannopoulos, ATHENA Research Center, Greece
   Parke Godfrey, Univ of York, Canada
   Michael Gubanov, Univ of Texas at San Antonio, USA
   Silu Huang, Microsoft
   Christophe Hurter, Ecole Nationale de l’Aviation Civile, France
   Vana Kalogeraki, Athens Univ of Economics & Business, Greece
   Eser Kandogan, IBM
   James Klosowski, AT&T Research
   Manolis Koubarakis, University of Athens, Greece
   Zhicheng Liu, Adobe
   Steffen Lohmann, Fraunhofer, Germany
   Ioana Manolescu, INRIA & Ecole Polytechnique, France
   Marios Meimaris, ATHENA Research Center, Greece
   Silvia Miksch, Vienna Univ of Technology, Austria
   Davide Mottin, Hasso Plattner Institute, Germany
   Martin Nöllenburg, Vienna Univ of Technology, Austria
   Olga Papaemmanouil, Brandeis Univ, USA
   Paul Parsons, Purdue Univ, USA
   Laura Po, Unimore, Italy
   Giuseppe Polese, Univ of Salerno, Italy
   Alexander Rind, St. Pölten Univ of Applied Sciences, Austria
   Gerik Scheuermann, Univ of Leipzig, Germany
   Heidrun Schumann, Univ of Rostock, Germany
   Michael Sedlmair, Univ of Stuttgart, Germany
   Thibault Sellam, Columbia Univ, USA
   Bettina Speckmann, Eindhoven Univ of Technology, Netherlands
   Kostas Stefanidis, Univ of Tampere, Finland
   Cagatay Turkay, Univ of Warwick, UK
   Panos Vassiliadis, Univ of Ioannina, Greece
   Junpeng Wang, Visa Research
   Chaoli Wang, Univ of Notre Dame, USA
   Panpan Xu, Bosch Research
   Kai Xu, Middlesex Univ, UK
   Hongfeng Yu, Univ of Nebraska-Lincoln, USA

-- 


  _nikos bikakis

Received on Tuesday, 5 November 2019 08:25:51 UTC