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Call for Papers <br>
<br>
BigVis 2023: 6th International Workshop on Big Data Visual Exploration and Analytics
<br>
<a class="moz-txt-link-freetext"
href="https://bigvis.imsi.athenarc.gr/bigvis2023">https://bigvis.imsi.athenarc.gr/bigvis2023</a>
<br>
March 28 2023, Ioannina, GR <br>
<br>
<br>
Held in conjunction with the 26th Intl. Conference on Extending Database Technology & 26th Intl. Conference on Database Theory (EDBT/ICDT 2023)
<br>
<br>
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.<br>
<br>
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.<br>
<br>
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.
<br>
<br>
<br>
Workshop Topics <br>
------------------------------------ <br>
In the context of visual exploration and analytics, topics of interest include, but are not limited to:
<br>
- Visualization, exploration & analytics techniques for various data types; e.g., stream, spatial, graph
<br>
- Human -in -the -loop processing <br>
- Human -centered databases <br>
- Data modeling, storage, indexing, caching, prefetching & query processing for interactive applications
<br>
- Interactive & human -centered machine learning <br>
- Interactive data mining <br>
- User -oriented visualization; e.g., recommendation, assistance, personalization
<br>
- Visualization & knowledge; e.g., storytelling <br>
- Progressive analytics <br>
- In -situ visual exploration & analytics <br>
- Novel interface & interaction paradigms <br>
- Visual representation techniques; e.g., aggregation, sampling, multi -level, filtering
<br>
- Scalable visual operations; e.g., zooming, panning, linking, brushing
<br>
- Scientific visualization; e.g., volume visualization <br>
- Analytics in the fields of scholarly data, digital libraries, multimedia, scientific data, social data, etc.
<br>
- Immersive visualization <br>
- Interactive computer graphics <br>
- Setting -oriented visualization; e.g., display resolution/size, smart phones, visualization over networks
<br>
- High performance, distributed & parallel techniques <br>
- Visualization hardware & acceleration techniques <br>
- Linked Data & ontologies visualization <br>
- Benchmarks for data visualization & analytics <br>
- Case & user studies <br>
- Systems & tools <br>
<br>
<br>
Submissions <br>
------------------------------------ <br>
Regular/Short Research papers [up to 8/4 pages] <br>
Work-in-progress papers [up to 4 pages] <br>
Vision papers [up to 4 pages] <br>
System papers and Demos [up to 4 pages] <br>
<br>
<br>
Important Dates <br>
------------------------------------ <br>
Submission: January 23, 2023 (AoE) <br>
Notification: February 18, 2023 <br>
Camera-ready: February 25, 2023 <br>
Workshop: March 28, 2023 <br>
<br>
<br>
Special Issue <br>
------------------------------------ <br>
TBD <br>
<br>
<br>
Organizing Committee <br>
------------------------------------ <br>
Nikos Bikakis, HMU & ATHENA Reacher Center, Greece <br>
Issei Fujishiro, Keio University, Japan <br>
Steffen Frey University of Stuttgart, Germany <br>
George Papastefanatos, ATHENA Reacher Center, Greece <br>
Shixia Liu, Tsinghua University, China <br>
<br>
<br>
Program Committee <br>
------------------------------------ <br>
James Abello, Rutgers University, USA <br>
Gennady Andrienko, Fraunhofer, Germany <br>
Natalia Andrienko, Fraunhofer, Germany <br>
Marco Angelini, Sapienza University of Rome, Italy <br>
Michael Behrisch, Utrecht University, Netherlands <br>
Jürgen Bernard, University of Zurich, Switzerland <br>
Jacob Biehl, University of Pittsburgh, USA <br>
Yiru Chen, Columbia University, USA <br>
Eva Chondrodima, University of Piraeus, Greece <br>
Panos Chrysanthis, University of Pittsburgh, USA <br>
Daniel Deutch, Tel Aviv University, Israel <br>
Katerina Doka, National Technical University of Athens, Greece <br>
Mennatallah El-Assady, University of Konstanz, Germany <br>
Jean-Daniel Fekete, INRIA, France <br>
Irini Fundulaki, ICS-FORTH, Greece <br>
Christoph Garth, Technische Universität Kaiserslautern, Germany
<br>
Parke Godfrey, York University, USA <br>
Herodotos Herodotou, Cyprus University of Technology, Cyprus <br>
Ekaterini Ioannou, University of Tilburg, Netherlands <br>
Stefan Jänicke, Leipzig University, Germany <br>
Li Jie, Tianjin University, China <br>
Eser Kandogan, Megagon Labs <br>
James Klosowski, AT&T Labs Research <br>
Manolis Koubarakis, National and Kapodistrian University of Athens, Greece
<br>
Stavros Maroulis, National Technical University of Athens, Greece <br>
Suvodeep Mazumdar, The University of Sheffield, United Kingdom <br>
Silvia Miksch, Vienna University of Technology, Austria <br>
Davide Mottin, Aarhus University, Denmark <br>
Evaggelia Pitoura, University of Ioannina, Greece <br>
Laura Po, Unimore, Italy <br>
Giuseppe Polese, University of Salerno, Italy <br>
Kristin Potter, NREL, USA <br>
Sajjadur Rahman, Megagon Labs <br>
Alexander Rind, St. Pölten University of Applied Sciences, Austria <br>
Panagiotis Ritsos, Bangor University, United Kingdom <br>
Maria Riveiro, Jönköping University, Sweden <br>
Hans-Jörg Schulz, Aarhus University, Denmark <br>
Michael Sedlmair, University of Stuttgart, Germany <br>
Tarique Siddiqui, Microsoft Research <br>
Dimitrios Skoutas, Athena Research Center, Creece <br>
Kavitha Srinivas, IBM <br>
Arjun Srinivasan, Georgia Institute of Technology, USA <br>
Manuel Stein, University Konstanz, Germany <br>
Christian Tominski, University of Rostock, Germany <br>
Natkamon Tovanich, École Polytechnique, France <br>
Katerina Tzompanaki, CY Cergy Paris University, France <br>
Katerina Vrotsou, Linköping University, Sweden <br>
Sean Wang, Fudan University, China <br>
Junpeng Wang, Visa Research <br>
Jules Wulms, Vienna University of Technology, Austria <br>
Jiazhi Xia, Central South University, China <br>
Panpan Xu, Bosch Research <br>
Hongfeng Yu, University of Nebraska-Lincoln, USA <br>
Demetris Zeinalipour, University of Cyprus, Cyprus <br>
Dimitris Zissis, Marine Traffic <br>
<br>
<br>
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<pre class="moz-signature" cols="200">--
Nikos Bikakis
Information Management Systems Institute
ATHENA Research Center
Athens | Greece
<a class="moz-txt-link-abbreviated" href="http://www.nbikakis.com">www.nbikakis.com</a>
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