** Paper submission deadline has been extended to February 4, 2022 (AoE) ** 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 [Online] 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 ------------------------------------ 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 ------------------------------------   _Human-AI Collaboration_   BigVis 2022 will devote a session to Human-AI collaboration approaches in the context of Big data visualization and analytics. 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: February 4 (AoE) ***Extended***   Notification: February 20, 2022   Camera-ready: February 25, 2022   Workshop: March 29, 2022 [Online] Special Issue ------------------------------------     TBD Organizing Committee ------------------------------------   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 ------------------------------------ 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 -- Nikos Bikakis Information Management Systems Institute ATHENA Research Center Athens | Greece www.nbikakis.com