-------- Forwarded Message -------- Subject: [WI] [CFP] BigVis: Big Data Visual Exploration & Analytics Workshop, EDBT 2021, Cyprus Date: Wed, 23 Dec 2020 20:52:22 +0200 From: Nikos Bikakis bikakis@athenarc.gr Reply-To: Nikos Bikakis bikakis@athenarc.gr

Call for Papers

BigVis 2021: 4th  International Workshop on Big Data Visual Exploration and Analytics   https://bigvis.imsi.athenarc.gr/bigvis2021   March 23, 2021, Nicosia, Cyprus

Held in conjunction with the 24th Intl. Conference on Extending Database Technology & 24th Intl. Conference on Database Theory (EDBT/ICDT 2021)

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 ------------------------------------ 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 *************************************************   Machine Learning and Visualization -------------------------------------------------

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]

Special Issue ------------------------------------   Extended versions of the best papers of BigVis 2021 will be invited for submission in a special issue. [TBA]

Important Dates ------------------------------------   Submission: January 8, 2021   Notification: January 29, 2021   Camera-ready: February 8, 2021   Workshop: March 23, 2021

Organizing Committee ------------------------------------   Nikos Bikakis, ATHENA Research Center, Greece   Panos K. Chrysanthis, University of Pittsburgh, USA   George Papastefanatos, ATHENA Research Center, Greece   Tobias Schreck, Graz University of Technology, Austria

Program Committee ------------------------------------   James Abello, Rutgers University, USA   Gennady Andrienko, Fraunhofer, Germany   Natalia Andrienko, Fraunhofer, Germany   Michael Behrisch, Utrecht University, Netherlands   Jacob Biehl, University of Pittsburgh, USA   Rick Cole, Tableau   Alfredo Cuzzocrea, University of Calabria, Italy   Ahmed Eldawy, University of California, Riverside, USA   Jean-Daniel Fekete, INRIA, France   Steffen Frey, University of Stuttgart, Germany   Issei Fujishiro, Keio University, Japan   Giorgos Giannopoulos, ATHENA Research Center, Greece   Parke Godfrey, University of York, Canada   Silu Huang, Microsoft   Christophe Hurter, Ecole Nationale de l’Aviation Civile, France   Halldor Janetzko, Lucerne University of Applied Sciences & Arts, Switzerland   Stefan Jänicke, University of Southern Denmark, Denmark   Vana Kalogeraki, Athens University of Economics & Business, Greece   Eser Kandogan, IBM   Anastasios Kementsietsidis, Google   James Klosowski, AT&T Research   Stavros Maroulis, National Technical University of Athens, Greece   Suvodeep Mazumdar, The University of Sheffield, United Kingdom   Silvia Miksch, Vienna University of Technology, Austria   Davide Mottin, Aarhus University, Denmark   Martin Nöllenburg, Vienna University of Technology, Austria   Behrooz Omidvar-Tehrani, NAVER LABS Europe, France   Jaakko Peltonen, Aalto University & University of Tampere, Finland   Laura Po, Unimore, Italy   Giuseppe Polese, University of Salerno, Italy   Alexander Rind, St. Pölten University of Applied Sciences, Austria   Rahman Sajjadur, Megagon Labs   Hans-Jörg Schulz, Aarhus University, Denmark   Bettina Speckmann, Eindhoven University of Technology, Netherlands   Kostas Stefanidis, University of Tampere, Finland   Christian Tominski, University of Rostock, Germany   Yannis Tzitzikas, University of Crete & FORTH-ICS, Greece   Katerina Vrotsou, Linköping University, Sweden   Chaoli Wang, University of Notre Dame, USA   Junpeng Wang, Visa Research   Chen Wei, Zhejiang University, China   Yingcai Wu, Zhejiang University, China   Jiazhi Xia, Central South University, China   Panpan Xu, Bosch Research   Hongfeng Yu, University of Nebraska-Lincoln, USA