- From: Nikos Bikakis <bikakis.nikos@gmail.com>
- Date: Mon, 17 Jan 2022 12:32:27 +0200
- To: undisclosed-recipients: ;
Call for Papers
BigVis 2022: 5th International Workshop on Big Data Visual Exploration and Analytics, EDBT/ICDT 2022
https://bigvis.imsi.athenarc.gr/bigvis2022
March 29 2022, Edinburgh, UK [Virtual]
Held in conjunction with the 25th Intl. Conference on Extending Database Technology & 25th Intl. Conference on Database Theory (EDBT/ICDT 2022)
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 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
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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, graph
- Human -in -the -loop processing
- Human -centered databases
- Data modeling, storage, indexing, caching, prefetching & query processing for interactive applications
- Interactive & human -centered 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
Special Theme
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_Human-AI Collaboration_
BigVis 2022 will devote a session to Human-AI collaboration approaches in the context of Big data visualization and analytics.
Submissions
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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
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Submission: January 28, 2022 (AoE)
Notification: February 20, 2022
Camera-ready: February 25, 2022
Workshop: March 29, 2022 [Online]
Special Issue
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TBD
Organizing Committee
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Nikos Bikakis, ATHENA Research Center, Greece
Hanna Hauptmann, Utrecht University, Netherlands
George Papastefanatos, ATHENA Research Center, Greece
Michael Sedlmair, University of Stuttgart, Germany
Program Committee
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James Abello, Rutgers University
Demosthenes Akoumianakis, Hellenic Mediterranean University
Gennady Andrienko, Fraunhofer
Natalia Andrienko, Fraunhofer
Jacob Biehl, University of Pittsburgh
Wei Chen, Zhejiang University
Panos Chrysanthis, University of Pittsburgh
Alfredo Cuzzocrea, University of Calabria
Evanthia Dimara, Université Paris-Sud
Harish Doraiswamy, Microsoft
Mennatallah El-Assady, University of Konstanz
Ahmed Eldawy, University of California, Riverside
Steffen Frey, University of Groningen
Issei Fujishiro, Keio University
Christoph Garth, Technische Universität Kaiserslautern
Parke Godfrey, York University
Hamed Haddadi, Imperial College London
Eser Kandogan, Megagon Labs
Alireza Karduni, Northwestern University
James Klosowski, AT&T Labs Research
Manolis Koubarakis, National University of Athens
Kwan-Liu Ma, University of California, Davis
Stavros Maroulis, National Technical University of Athens
Suvodeep Mazumdar, The University of Sheffield
Silvia Miksch, Vienna University of Technology
Davide Mottin, Aarhus University
Laura Po, Universitá di Modena e Reggio Emilia
Giuseppe Polese, University of Salerno
Sajjadur Rahman, Megagon Labs
Alexander Rind, St. Pölten University of Applied Sciences
Panagiotis Ritsos, Bangor University
Maria Riveiro, Jönköping University
Hans-Jörg Schulz, Aarhus University
Arjun Srinivasan, Tableau
Manuel Stein, Universität Konstanz
Christian Tominski, University of Rostock
Natkamon Tovanich, IRT SystemX
Yannis Tzitzikas, University of Crete & FORTH-ICS
Katerina Vrotsou, Linköping University
Junpeng Wang, Visa Research
Yunhai Wang, Graduate University of Chinese Academy of Sciences
Jules Wulms, Vienna University of Technology
Jiazhi Xia, Central South University
Kai Xu, Middlesex University
Hongfeng Yu, University of Nebraska-Lincoln
Received on Monday, 17 January 2022 10:32:45 UTC