[Infovis] [CFP] Special Issue: Interactive Big Data Visualization & Analytics, Big Data Research, Elsevier

[NIkos]

  Call for Papers

Special Issue "Interactive Big Data Visualization and Analytics"
Big Data Research Journal, Elsevier (Impact Factor: 2.95)
https://www.journals.elsevier.com/big-data-research/call-for-papers/big-data-visualization-and-analytics 



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 
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 offer self-service visual analytics, i.e. enable data 
scientists and business analysts to visually gain value and insights out 
of the data as rapidly as possible, minimizing the role of IT-expert in 
the loop.

This special issue aims to publish work on multidisciplinary research 
areas spanning from Data Management and Mining to Information 
Visualization and Human-Computer Interaction.


Topics for the Special Issue
-------------------------------
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



Important Dates
-------------------------------
   Submission Deadline: October 1, 2020  **extended**
   Author Notification: December 1, 2020
   Revised Manuscript Due: January 15, 2021
   Notification of Acceptance: February 1, 2021
   Final Manuscript Due: March 1, 2020
   Tentative Publication Date: May, 2021



Guest Editors
-------------------------------
   David Auber, University Bordeaux, France
   Nikos Bikakis, ATHENA Research Center, Greece
   Panos Chrysanthis, University of Pittsburgh, USA
   George Papastefanatos, ATHENA Research Center, Greece
   Mohamed Sharaf, United Arab Emirates University, UAE





-- 
:nikos