Special Session 1:

5th Special Session on HealthCare Data

December 17-20, 2022 @ Osaka, Japan

Health data differs from other industries' data in terms of structure, context, importance, volatility, availability, traceability, liquidity, change speed, usage and sources from which it is collected. As medicine is a constantly developing science, healthcare sector also. In this new emerging research area which stands at the intersection of several different discipline such as Medicine, Behavioral Science, Supply Chain Management or Big Data Analytics, techniques, methods, applications and devices are continuously developed to be used for the acquisition, storage, processing, analysis, standardization and optimization of every process in the health sector. As the healthcare sector is so challenging and related data are consistently explosive, healthcare organizations are focusing to become smarter in order to overcome the industry’s inefficiencies to improve quality of care. “To become smarter” requires impeccable data analytics. All stakeholders in the sector should reveal the deep value of this valuable data in order to apply insights to improve quality of care, clinical outcomes and deliver personalized healthcare value, while reducing medical costs, collaborate across care settings to deliver integrated, personalized care experiences, prevent disease, promote wellness and manage care, build flexibility into operations to support cost reduction and excellence in clinical and business performance and practices.

The general purpose of this special session in IEEE BigData 2022 conference is to bring together researchers, academicians and sector employees from different fields and disciplines and provide them an independent platform to exchange information on their researches, ideas and findings about healthcare data and its analytics. It is also aimed to encourage debate on how big data can effectively support healthcare in terms of diagnosis, treatment and population health, and to develop a common understanding for research conducted in this multidisciplinary field.

Topics of interest include, but are not limited to, the following:

  • Healthcare Data
    • Health data collection and analysis
    • Problems in health data processing
    • Protection and security of personal health data
    • Electronic health records and standards
  • Healthcare Information Systems
    • Medical Imaging Systems
    • Medical Applications
    • Mobile Solutions
  • Pervasive Healthcare Information Systems and Services
    • Sensor nodes
    • Wearable health information
    • Information solutions developed for the disabled
  • Process Management in Health Informatics Systems
  • Health Decision Support Systems
  • E-health Applications
Special Session Organizers
  • Sultan Turhan PhD. (sturhan@gsu.edu.tr), Department of Computer Engineering, Galatasaray University
  • Assist. Prof. Ozgun Pinarer (opinarer@gsu.edu.tr), Department of Computer Engineering, Galatasaray University
Important Dates
  • Full paper submission: August 20, 2022
  • Notification of paper acceptance: Oct 15, 2022
  • Camera-ready of accepted papers: Nov 15, 2022
  • Conference: Dec 17-20, 2022
Instructions

Papers should be submitted as a PDF in 2-column IEEE format. Detailed instructions for the authors can be found at the conference website (https://bigdataieee.org/BigData2022/CallPapers.html).
Accepted papers will be published in the conference proceedings.
All accepted papers must be presented by one of the authors in the conference to include the article in the proceedings.
If you have any questions about the special session, please do not hesitate to contact us.

Paper submission page: https://wi-lab.com/cyberchair/2022/bigdata22/index.php

Important Dates:
Full paper submission: September 10, 2022
Notification of paper acceptance: October 15, 2022
Camera-ready of accepted papers: November 15, 2022
Conference: December 17-20, 2022

Special Session 2:

Machine Learning on Big Data (MLBD 2022)

December 17-20, 2022, Osaka, Japan

Best Papers of MLBD 2022 will be Invited for Extended Submission to a Top-Quality Journal

Aim and Scope
The Special Session “Machine Learning on Big Data” (MLBD 2022) of the 2022 IEEE International Conference on Big Data (IEEE BigData 2022) follows the great success of six previous editions co-located with the IEEE BigData and IEEE ICMLA conference series and focuses on machine learning models, techniques and algorithms related to Big Data, a vibrant and challenging research context playing a leading role in the Machine Learning and Data Mining research communities. Big data is gaining attention from researchers, being driven among others by technological innovations (such as cloud interfaces) and novel paradigms (such as social networks). Devising and developing machine learning models, techniques and algorithms for big data represent a fundamental problem stirredup by the tremendous range of critical applications incorporating machine learning tools in their core platforms. For example, in application settings where big data arise and machine is useful, we recognize, among other things: (i) machine-learning-based processing (e.g., acquisition, knowledge discovery, and so forth) over large-scale sensor networks introduces important advantages over classical data-management-based approaches; similarly, (ii) medical and e-heath information systems usually include successful machine learning tools for processing and mining very large graphs modelling patient-to-disease, patient-todoctor, and patient-to-therapy networks; (iii) genome data management and mining can gain important benefits from machine learning algorithms. Some hot topics in machine learning on big data include: (i) machine learning on unconventional big data sources (e.g., large-scale graphs in scientific applications, strongly-unstructured social networks, and so forth); (ii) machine learning over massive big data in distributed settings; (iii) scalable machine learning algorithms; (iv) deep learning – models, principles, issues; (v) machinelearning-based predictive approaches; (vi) machine-learning-based big data analytics; (vii) privacy-preserving machine learning on big data; (viii) temporal analysis and spatial analysis on big data; (ix) heterogeneous machine learning on big data; (x) novel applications of machine learning on big data (e.g., healthcare, cybersecurity, smart cities, and so forth).

The MLBD 2022 special session focuses on all the research aspects of machine learning on Big Data. Among these, an unrestricted list includes:

  • Fundamentals
  • Modelling
  • Statistical Approaches
  • Novel Paradigms
  • Innovative Techniques
  • Algorithms
  • Innovative Architectures (GPU, Clouds, Clusters)
  • Non-Conventional Big Data Settings (e.g., Spatio-Temporal Big Data, Streaming Big Data, Graph Big Data, Cloud Big Data, Probabilistic Big Data, Uncertain Big Data)
  • Systems
  • Architectures
  • Advanced Topics (e.g., Dimensionality Reduction, Matrix Approximation Algorithms, Multi-Task Learning, Semi-Supervised Learning, Integration with NoSQL Databases)
  • Case Studies and Applications

  • The Special Session “Machine Learning on Big Data” (MLBD 2022) of the 2022 IEEE International Conference on Big Data (IEEE BigData 2022) will be held in Osaka, Japan, during December 17-20, 2022, and it aims to synergistically connect the research community and industry practitioners. It provides an international forum where scientific domain experts and Machine Learning and Data Mining researchers, practitioners and developers can share their findings in theoretical foundations, current methodologies, and practical experiences on Machine Learning on Big Data. MLBD 2022 will provide a stimulating environment to encourage discussion, fellowship, and exchange of ideas in all aspects of research related to Machine Learning on Big Data. This includes both original research contributions and insights from practical system design, implementation and evaluation, along with new research directions and emerging application domains in the target area. An expected outcome from MLBD 2022 is the identification of new problems in the main topics, and moves to achieve consolidated solutions to already-known problems. Other goals are to help in creating a focused community of scientists who create and drive interest in the area of Machine Learning on Big Data, and additionally to continue on the success of the event across future years.

    Special Session Location
    Osaka, Japan

    Submission Guidelines and Instructions
    Contributions are invited from prospective authors with interests in the indicated session topics and related areas of application. All contributions should be high quality, original and not published elsewhere or submitted for publication during the review period.

    Submitted papers should strictly follow the IEEE official template. Maximum paper length allowed is:

  • Full Papers: 10 pages
  • Short Papers: 4 pages
  • Demo Papers: 4 pages
  • Position Papers: 4 pages

  • Submitted papers will be thoroughly reviewed by members of the Special Session Program Committee for quality, correctness, originality and relevance. All accepted papers must be presented by one of the authors, who must register.

    Papers must be submitted via the CyberChair System by selecting the track “Special Session on Machine Learning on Big Data”.

    Paper Publication
    Accepted papers will appear in the official IEEE Big Data 2022 main conference proceedings, published by IEEE.

    Authors of selected papers from the special session will be invited to submit an extended version of their paper to a special issue of a high-quality international journal.

    Important Dates:
    Paper submission: September 10, 2022
    Notification of acceptance: October 31, 2022
    Camera-ready paper due: November 15, 2022
    Special Session: December 17-20, 2022

    Program Committee Chair
    Alfredo Cuzzocrea, University of Calabria, Italy

    Program Committee
    Michelangelo Ceci, University of Bari, Italy
    Alfredo Cuzzocrea, University of Calabria, Italy
    Joao Gama, University of Porto, Portugal
    Marwan Hassani, TU Eindhoven, The Netherlands
    Mark Last, Ben-Gurion University of the Negev, Israel
    Rocco Langone, Deloitte, Belgium
    Carson K. Leung, University of Manitoba, Canada
    Sofian Maabout, LABRI, Bordeaux University, France
    Anirban Mondal, Shiv Nadar University, India
    Enzo Mumolo, University of Trieste, Italy
    Apostolos Papadopoulos, Aristotle University of Thessaloniki, Greece

    For more information and any inquire, please contact Alfredo Cuzzocrea.

    Special Session 3:

    Privacy and Security of Big Data (PSBD 2022)

    December 17-20, 2022, Osaka, Japan

    Best Papers of PSBD 2022 will be Invited for Extended Submission to a Top-Quality Journal

    Aim and Scope
    The Special Session “Privacy and Security of Big Data” (PSBD 2022) of the 2022 IEEE International Conference on Big Data (IEEE BigData 2022) follows the great success of eight previous editions co-located with the IEEE BigData and ACM CIKM conference series and focuses the attention on privacy and security research issues in the context of Big Data, a vibrant and challenging research context which is playing a leading role in the Database research community. Indeed, while Big Data is gaining the attention from the research community, also driven by some relevant technological innovations (like Clouds) as well as novel paradigms (like social networks), the issues of privacy and security of Big Data represent a fundamental problem in this research context, due to the fact Big Data are typically published online for supporting knowledge management and fruition processes and, in addition to this, such data are usually handled by multiple owners, with possible secure multi-part computation issues. Some of the hot topics in the context privacy and security of Big Data include: (i) privacy and security of Big Data integration and exchange; (ii) privacy and security of Big Data in data-intensive Cloud computing; (iii) system architectures in support of privacy and security of Big Data, e.g., GPUs: (iv) privacy and security issues of Big Data querying and analysis.

    The PSBD 2022 special session focuses on all the research aspects of privacy and security of Big Data. Among these, an unrestricted list is the following one:

  • Privacy of Big Data: Fundamentals
  • Privacy of Big Data: Modelling
  • Privacy of Big Data: Statistical Approaches
  • Privacy of Big Data: Novel Paradigms
  • Privacy of Big Data: Innovative Protocols
  • Privacy of Big Data: Algorithms
  • Privacy of Big Data: Query Optimization
  • Privacy of Big Data: Non-Conventional Environments (e.g., Spatio-Temporal Data, Streaming Data, Cloud Data, Probabilistic Data, Uncertain Data)
  • Privacy of Big Data: Systems
  • Privacy of Big Data: Architectures
  • Privacy of Big Data: Advanced Topics (e.g., NoSQL Databases)
  • Privacy of Big Data: Case Studies and Applications
  • Security of Big Data: Fundamentals
  • Security of Big Data: Modelling
  • Security of Big Data: Statistical Approaches
  • Security of Big Data: Novel Paradigms
  • Security of Big Data: Innovative Protocols
  • Security of Big Data: Algorithms
  • Security of Big Data: Query Optimization
  • Security of Big Data: Non-Conventional Environments (e.g., Spatio-Temporal Data, Streaming Data, Cloud Data, Probabilistic Data, Uncertain Data)
  • Security of Big Data: Systems
  • Security of Big Data: Architectures
  • Security of Big Data: Advanced Topics (e.g., NoSQL Databases)
  • Security of Big Data: Case Studies and Applications

  • The Special Session on “Privacy and Security of Big Data” (PSBD 2022) of the 2022 IEEE International Conference on Big Data (BigData 2022) will be held in Osaka, Japan, during December 17-20, 2022, and it focuses on these aspects, by posing the emphasis on a theoretical as well as a practical point of view, and provides a forum for researchers and practitioners interested in privacy and security of big data to meet and exchange preliminary ideas and mature results.

    Special Session Location
    Osaka, Japan

    Submission Guidelines and Instructions
    Contributions are invited from prospective authors with interests in the indicated session topics and related areas of application. All contributions should be high quality, original and not published elsewhere or submitted for publication during the review period.
    Submitted papers should strictly follow the IEEE official template. Maximum paper length allowed is:

  • Full Papers: 10 pages
  • Short Papers: 4 pages
  • Demo Papers: 4 pages
  • Position Papers: 4 pages

  • Submitted papers will be thoroughly reviewed by members of the Workshop Program Committee for quality, correctness, originality and relevance. All accepted papers must be presented by one of the authors, who must register.

    Papers must be submitted via the CyberChair System by selecting the track “Special Session on Privacy and Security of Big Data”.

    Paper Publication
    Accepted papers will appear in the official IEEE Big Data 2022 main conference proceedings, published by IEEE.

    Authors of selected papers from the workshop will be invited to submit an extended version of their paper to a special issue of a high-quality international journal.

    Important Dates:
    Paper submission: September 10, 2022
    Notification of acceptance: October 24, 2022
    Camera-ready paper due: November 15, 2022
    Special Session: December 17-20, 2022

    Program Committee Chair
    Alfredo Cuzzocrea, University of Calabria, Italy

    Program Committee
    Maurizio Atzori, University of Cagliari, Italy
    Roberto Baldoni, University of Rome “Sapienza”, Italy
    Elisa Bertino, CERIAS and Purdue University, USA
    Pietro Colombo, University of Insubria, Italy
    Alfredo Cuzzocrea, University of Calabria, Italy
    Rinku Dewri, University of Denver, USA
    Katerina Doka, NTUA, Greece
    Josep Domingo-Ferrer, Universitat Rovira i Virgili, Spain
    Yucheng Dong, Sichuan University, China
    Murat Kantarcioglu, University of Texas at Dallas, USA
    Thorsten Strufe, Technische Universitat Darmstadt, Germany
    Vicenc Torra, IIIA-CSIC, Spain
    Traian Marius Truta, Northern Kentucky University, USA
    Xiaokui Xiao, Nanyang Technological University, Singapore

    For more information and any inquire, please contact Alfredo Cuzzocrea.

    Special Session 4:

    8th Special Session on Intelligent Data Mining

    December 17-20, 2022 Osaka/JAPAN

    After the successes of the first, second, third, fourth, fifth, sixth and seventh editions of Special Session on Intelligent Data Mining in Santa Clara, CA (2015); Washington, DC (2016); Boston, MA (2017); Seattle, WA, (2018); Los Angeles, CA, (2019); Online Pandemic Session (2020), Online Pandemic Session (2021) and the 8th Special Session on Intelligent Data Mining in Osaka, JAPAN (2022) will continue promoting and disseminating the knowledge concerning several topics and technologies related to data mining science.

    Artificial Intelligence (AI) & Machine Learning (ML) fields are interdisciplinary, including computer science, mathematics, psychology, linguistics, philosophy, neuroscience etc. This interdisciplinary special session seeks scientific understanding on data and intelligence.

    This session may help to create scientific evolution to propose robust and powerful schemes between human nature and big data processing.

    Intelligent Data Mining session open to every researcher as well as industrial partners.

    The aims of this Special Session on Intelligent Data Mining are to:

    • Bring researchers and experts together to discuss and share their experiences
    • Share the current and new research topics and ideas
    • Improve and enhance personal, enterprise, national and international awareness
    • Provide a platform to present and discuss recent advancements
    • Increase international collaborations among university–industry-institutions

    In the fields of theory and applications of data mining, artificial intelligence, computer science, mathematics, psychology, linguistics, philosophy, neuroscience and other disciplines to discuss better understanding of big data and intelligence.

    The papers submitted to this special session might be in a large range of topics that include theory, application and implementation of artificial intelligence, machine learning and data mining including but not limited to the topics given below.

    Use of Artificial Intelligence || Machine Learning in Data Mining as:
    • Data Mining, Data Science and Big Data
    • Data Warehouse, Clustering, Visualization
    • Big Data and Services
    • Graph Mining
    • Data Security and Privacy
    • Homeland Security and Data Analysis
    • GPU Applications
    • Medical Imaging
    • Deep Learning
    • Scalable Computing, Cloud Computing
    • Knowledge Discovery, Integration, Transformation
    • Information Retrieval
    • Information Security
    • Data Classification, Regression, Cleaning
    • Smart Cities & Energy
    • Social Media, Social Networking, Social Data
    • Semantic Computing
    • IoT, Autonomous Systems and Agents
    • Algorithms
    • Mobile Computing
    • Sensors, Networks, Devices
    • Mathematics
    • NLP
    • Philosophy
    • Neuroscience and Bioinformatics
    • Biometric
    • Sustainability
    • HPCC and Hadoop
    • Recent Theory, Trends, Technologies and Applications
    • Future Directions and Challenges in Intelligent Data Mining
    • Industrial Challenges in Data Mining
    • Demo Applications in Data Mining

    Papers should be submitted for this special session by Sept 10, 2022

    Papers should be submitted as a PDF in 2-column IEEE format. Detailed instructions for the authors can be found at the conference website. Accepted papers will be published in the conference proceedings. All accepted papers must be presented by one of the author/s in the conference to include the article in the proceedings (http://bigdataieee.org/BigData2022/).

    If you have any question about this special session, please do not hesitate to direct your question to the special session organizer Asst. Prof. Dr. Uraz Yavanoglu (urazyavanoglu@gmail.com, uraz@gazi.edu.tr)

    Special Session Organizer:
    Asst. Prof. Dr. Uraz Yavanoglu
    Department of Computer Engineering
    Gazi University, Turkey
    www.druraz.com

    The important dates for this special session are:
    • Full Paper Submission Deadline : Sept 10, 2022 11:59pm PST
    • Notification of Acceptance : Nov 5, 2022
    • Camera-ready papers & Pre-registration : Nov 15, 2022, 11:59pm PST
    • Conference Dates : Dec 17-20, 2022

    Special Session 5:

    2nd Special Session on Big Data and Electronics

    December 17-20, 2022 Osaka/JAPAN

    After the successes of the first edition of Special Session on Big Data and Electronics in Seattle, WA, (2018) and the 2nd Special Session on Big Data and Electronics in Osaka, JAPAN (2022) will promote and disseminate the knowledge concerning several topics and technologies related to data mining science and electronics. Electronics plays a vital role in enabling numerous applications. It deals with modern energy processing systems, micro-electronics, thermal analysis, solid-state electronics, logic, architectural, and system level synthesis…etc. Utilize big data processing technology in electronics will help to improve quality, sustanibility and reliability of systems.

    Artificial Intelligence (AI) & Machine Learning (ML) fields are interdisciplinary, including computer science, mathematics, psychology, linguistics, philosophy, neuroscience etc. This interdisciplinary special session seeks scientific understanding on data and intelligence.

    This session may help to create scientific evolution to propose robust and powerful schemes between electronics and data processing.

    Special Session on Big Data and Electronics session open to every researcher as well as industrial partners

    Thus, The aims of this Special Session on Special Session on Big Data and Electronics are to:

    • Bring researchers and experts together to discuss and share their experiences
    • Share the current and new research topics and ideas
    • Improve and enhance personal, enterprise, national and international awareness
    • Provide a platform to present and discuss recent advancements
    • Increase international collaborations among university–industry-institutions

    Topics of interest include, but are not limited to:

    Big Data analytics and Data mining in:
    • Electrical Engineering
    • Electronics Engineering
    • Supervisory Control and Data Acquisition (SCADA) systems
    • Smart Grids
    • Active and Passive Electronic Components
    • Nonlinear Circuits
    • Microprocessors, Microcontrollers and Digital Signal Processing
    • IP Network Communication And Control Systems
    • RF and Wireless Systems Analog-to-Digital Converters (ADC), Voltage-to-Frequency Converts (VFC), Frequency-to-Digital Converters (FDC), Time-to-Digital Converters (TDC)
    • Security Operation Center (SoC), MPSoC, Network Operations Centers NoC, Session Initiated Protocol SIP, and NIP design and test
    • Complementary Metal-Oxide Semiconductor (CMOS), Bipolar Junction Transistor (BJT), Bipolar CMOS (BiCMOS), FinFETs, SETs, Spintronics, SFQ, MTJ, etc.
    • Robotics and Automation
    • Unmanned Avionics Systems
    • Semiconductor Processing
    • Solid-State Electronics
    • Quantum Electronics
    • Thin Solid Films
    • Nanoprocessing, Nanotechnology And Nanofabrication
    • Flexible And Stretchable Electronics
    • MEMS, MOEMS and NEMS
    • Power Electronics and Power Devices
    • Power Generation, Transmission and Distribution
    • Control Techniques
    • Hybrid Systems
    • Renewable Energy
    • Electrical Vehicles and Components
    • Reliability and Maintenance
    • Sustainability
    • Recent Theory, Trends, Technologies and Applications
    • Future Directions and Challenges in Big Data and Electronics
    • Industrial Challenges in Big Data and Electronics
    • Demo Applications

    Papers should be submitted for this special session by Sept 10, 2022

    Papers should be submitted as a PDF in 2-column IEEE format. Detailed instructions for the authors can be found at the conference website. Accepted papers will be published in the conference proceedings. All accepted papers must be presented by one of the author/s in the conference to include the article in the proceedings (http://bigdataieee.org/BigData2022/).

    If you have any question about this special session, please do not hesitate to direct your question to the special session organizers Dr. Alper Ozbilen (alper.ozbilen@pavotek.com.tr), Dr. Shady Khalil (shady.khalil@qatar.tamu.edu), Dr. Uraz Yavanoglu (uraz@gazi.edu.tr)

    Dr. Alper Ozbilen
    Chairman
    PAVOTEK, Turkey

    Dr. Shady Khalil
    Associate Research Scientist
    Texas A&M University at Qatar, Qatar

    Dr. Uraz Yavanoglu
    Department of Computer Engineering
    Gazi University, Turkey

    The important dates for this special session are:
    • Full Paper Submission Deadline : Sept 10, 2022 11:59pm PST
    • Notification of Acceptance : Nov 5, 2022
    • Camera-ready papers & Pre-registration : Nov 15, 2022, 11:59pm PST
    • Conference Dates : Dec 17-20, 2022

    Special Session 6:

    8th Special Session on Information Granulation in Data Science and Scalable Computing

    December 17-20, 2022 Osaka/JAPAN

    BACKGROUND:
    Granular Computing is a general computation approach for a usage of information granules such as data blocks, clusters, groups, as well as value intervals, sets, hierarchies, etc., to build efficient computational models for complex Big Data applications, characterized by huge amounts of diverse data and associated domain knowledge. Information Granulation, under different names, has appeared in many fields, such as granularity in artificial intelligence, divide and conquer methods for scaling calculations, approximate computing, knowledge representation, topological data analysis, image processing and many others related with human and machine intelligence. The principles of Granular Computing can be also helpful to design simplified descriptions of complex data systems and to bridge the gap between the humans and AI. Herein we may follow the phrase "Information Granules = Fundamental Pieces of Human Knowledge" and treat Granular Computing as one of important meta-mathematical methodologies for Big Data Analytics.

    SESSION SCOPE:
    The 8th session in this series continues to address the theory and practice of derivations and computations based on various types of granular models and structures. It provides researchers from both academia and industry with the means to present the state-of-the-art results and methodologies related to Information Granulation and Granular Computing, with a special emphasis on applications in Data Science and Scalable Computing. The session also refers – from the particular viewpoint of Information Granulation – to currently important research tracks such as social network computing, cloud computing, cyber-security, data mining, process mining, machine learning, statistics, knowledge management, AI-based systems, soft computing, e-Intelligence, business intelligence, bioinformatics, health informatics and IoT. The papers addressing Information Granulation in the emerging field of XAI and using its principles to construct interpretable AI models are highly welcome as well. Particularly, we encourage the papers which deliver experimental results but in the same time, provide theoretical foundations to justify those results.

    HIGHLIGHTS:

    • The session is organized as a part of the IEEE Big Data 2022 conference (December 17-20), which is a well-established and competitive international event targeted at modern trends in big data processing and analytics.
    • The session is intended to be a forum for discussing ideas, issues and methods based on and inspired by Information Granulation and Granular Computing, in an atmosphere promoting free exchange of viewpoints and perspectives coming from different application areas.
    • Papers accepted to the session will be published in the IEEE Big Data 2022 conference proceedings, together with papers accepted to the main conference track.
    • Organizers are planning a special issue in a relevant scientific journal, such as Big Data Research (Elsevier), Granular Computing (Springer) or Big Data Mining and Analytics (Tsinghua University Press).
    • Organizers particularly encourage papers which deliver experimental results but in the same time, provide theoretical foundations to justify those results.

    ORGANIZERS

    • Shusaku Tsumoto
      Department of Medical Informatics, Faculty of Medicine
      Shimane University
      tsumoto@med.shimane-u.ac.jp
    • Dominik Slezak
      Institute of Informatics
      University of Warsaw
      slezak@mimuw.edu.pl
    • Tzung-Pei Hong
      Department of Computer Science and Information Engineering
      National University of Kaohsiung
      tphong@nuk.edu.tw
    • Leon S. L. Wang
      Department of Information Management
      National University of Kaohsiung
      slwang@nuk.edu.tw
    • Weiping Ding
      School of Information Science and Technology
      Nantong University
      dwp9988@hotmail.com

    IMPORTANT DATES
    Full paper submission: October 7, 2022
    Notification of paper acceptance: October 30, 2022
    Camera-ready of accepted papers: November 15, 2022
    Conference: December 17-20, 2022

    INSTRUCTIONS
    Papers should be submitted as PDF in 2-column IEEE format, up to 10 pages long. Detailed instructions for the authors can be found at the conference homepage: Link
    Accepted papers will be published in the conference proceedings. However, the necessary condition is that one of authors presents the paper at the conference.
    Paper submission page: Link

    Special Session 7:

    Special Session on Platform for DFFT (Data Free Flow with Trust)

    December 17-20, 2022 Osaka/JAPAN

    Data is the most important property for bringing innovation and digital transformation. By using highly developed information and communication technology, we can generate, store, replicate, transfer, process and analyze data at very low cost, which realizes democratization of innovation, that is to give everyone in the world a chance for innovation. Today, the world is using the power of data to solve all kinds of issues, from global ones to everyday life ones.

    Data-driven society achieves both economic development and resolution of social problems in parallel by connecting everyone and everything with each other, sharing various knowledge and information, and creating new value. From the perspective of economy, it will contribute to sustainable and harmonious economic development in the world. On the other hands, from the perspective of domestic social issues, it will contribute to the sustainability of regions and national security, including the declining birthrate, increasing aging population, depopulation of rural areas, economic disparity, and prevention of natural disasters and pandemics. For this purpose, vast Big Data in cyber space (virtual space) and physical space (real space) are linked across all over the world among various stakeholders to realize the vision of "Data Free Flow with Trust" (DFFT). To establish a DFFT that spans multiple stakeholders, the openness, transparency and interoperability of data exchange must be achieved. The privacy, security, quality assurance and ease of use of the data itself must also be considered.

    The general purpose of this special session in IEEE BigData 2022 conference is to bring together researchers, academicians, and sector employees from different fields and disciplines and to exchange information on their practical activities, research, ideas and findings about global platform for DFFT. It is also aimed to encourage debate on how global platform can effectively support big data distribution, sharing, and application in terms of infrastructure, technology, governance, business, and so on, and to develop a common understanding for research conducted in this multidisciplinary field.

    Topics of interest include, but are not limited to, the following:

    • Global Data Space Platform
      • Federated Data Platform
      • Federated Data Catalog
      • Supply Chain Data Management
    • Data Platform Federation Technology
      • Connector and Broker Technology
      • Data Collection Technology
      • Trust Federation
    • Data Business Platform
      • Data Trading Market
    • Data Processing Platform
      • DWH (Data Warehouse) Platform
      • Data Lake Platform
      • ETL (Extract, Transform, Load) Platform
      • IoT Realtime Data Collection Platform
      • Open Source Data Processing Platform
    • Secure Data Sharing/Processing Platform
      • Data Platform with Secure Multiparty Computation
      • Federated Learning Platform
      • Blockchain-based Data Platform
    • Data Governance Rules, Law, and Policy
      • Personal Data and Privacy Protection
      • Industry Confidential Data Protection
    • Cross-domain Data Sharing Applications
      • Smart City
      • Digital Government
      • Disaster Prevention and Response

    Session Organizers
    Noboru Koshizuka (Chair)
    Interfaculty Initiative in Information Studies
    The University of Tokyo
    noboru@koshizuka-lab.org

    Stephan Haller
    Institute for Public Sector Transformation
    Bern University of Applied Sciences
    stephan.haller@bfh.ch

    Hiroshi Mano
    Data Society Alliance
    h.mano@data-society-alliance.org

    Takashi Michikata
    Interfaculty Initiative in Information Studies
    The University of Tokyo
    takashi.michikata@koshizuka-lab.org

    Yukio Ohsawa
    Department of Systems Innovation,School of Engineering,
    The University of Tokyo
    ohsawa@sys.t.u-tokyo.ac.jp

    Boris Otto
    Fraunhofer ISST
    Boris.Otto@isst.fraunhofer.de

    Shinji Shimojo
    Cybermedia Center,
    Osaka University
    shinji.shimojo.cmc@osaka-u.ac.jp

    Hideaki Takeda
    National Institute of Informatics
    takeda@nii.ac.jp

    Important Dates

    • Full paper submission: September 15, 2022
    • Notification of paper acceptance: Oct 20, 2022
    • Camera-ready of accepted papers: Nov 15, 2022
    • Conference: Dec 17-20, 2022

    Instructions
    Papers should be submitted as a PDF in 2-column IEEE format. Detailed instructions for the authors can be found at the conference website https://bigdataieee.org/BigData2022/CallPapers.html).
    Accepted papers will be published in the conference proceedings.
    All accepted papers must be presented by one of the authors in the conference to include the article in the proceedings.
    If you have any questions about the special session, please do not hesitate to contact us.
    Paper submission page: https://wi-lab.com/cyberchair/2022/bigdata22/index.php

    Special Session 8:

    40 Years of Rough Sets from Big Data Perspective

    December 17-20, 2022 Osaka/JAPAN

    BACKGROUND
    The theory of Rough Sets was founded by Zdzisław Pawlak in order to serve as an efficient framework for data / information / knowledge representation and exploration. Following Professor Pawlak’s seminal paper, titled “Rough Sets”, published in 1982 in International Journal of Computer and Information Sciences (currently International Journal of Parallel Programming), it is important to discuss the history, the presence, and possible future developments of this theory, as well as its applications, with a particular focus on solving Big Data problems (often referred as Big Data V’s). It is also important to emphasize that although the world around us becomes more and more complex – by means of, in particular, the growth of available data – there will be always a demand for simple and interpretable solutions.

    SESSION SCOPE
    Our aim is to discuss to what extent the paradigms of Rough Sets can help in solving Big Data problems (so-called Big Data V’s). We can refer to, e.g., the role of rough set approximations in scaling calculations on large data (Volume), the role of rough-set-driven model simplification algorithms in dealing with data of low quality (Veracity), or the focus of computational frameworks based on Rough Sets on producing interpretable results (and thus delivering Value to the experts and users). Our aim is also to discuss how to scale the rough-set-based approaches to cope with other V’s, such as Velocity or Variety of data. Given the anniversary flavor of the session, we intend to refer to the past achievements of Rough Sets but at the same time, discuss what should come next. We invite papers explaining how to take advantage of Rough Sets in combination with other approaches. We invite papers that report experimental results obtained for Big Data scenarios but at the same time, provide theoretical foundations that underpin those results. We also invite papers addressing the task of active data acquisition, especially when it comes to modeling complex phenomena and decision making in interaction with Big Data environments.

    HIGHLIGHTS
    • The session is organized as a part of the IEEE Big Data 2022 conference (December 17-20), which is a well-established and competitive international event targeted at modern trends in Big Data processing and analytics.
    • The session is a forum for discussing ideas, issues and methods based on and inspired by Rough Sets, in an atmosphere promoting free exchange of viewpoints.
    • Papers accepted to the session will be published in the IEEE Big Data 2022 conference proceedings, together with papers accepted to the main conference track.
    • Organizers invite particularly papers that deliver experimental results but at the same time, provide theoretical foundations supporting those results.
    • Given the anniversary nature of the session, organizers also invite retrospective papers referring to the history of Rough Sets, but only if the relationship to the fundamental aspects of Big Data is sufficiently strongly exposed.

    ORGANIZERS:
    Dominik Ślęzak
    Institute of Informatics
    University of Warsaw
    slezak@mimuw.edu.pl

    Andrzej Janusz
    Institute of Informatics
    University of Warsaw
    janusza@mimuw.edu.pl

    Hung Son Nguyen
    Institute of Informatics
    University of Warsaw
    son@mimuw.edu.pl

    Andrzej Skowron
    Systems Research Institute
    Polish Academy of Sciences
    skowron@mimuw.edu.pl

    Marcin Szczuka
    Institute of Informatics
    University of Warsaw
    szczuka@mimuw.edu.pl

    IMPORTANT DATES
    Full paper submission: October 7, 2022
    Notification of paper acceptance: October 30, 2022
    Camera-ready of accepted papers: November 15, 2022
    Conference: December 17-20, 2022

    INSTRUCTIONS
    Papers should be submitted as PDF in 2-column IEEE format, up to 10 pages long. Detailed instructions for the authors can be found at the conference homepage: Link
    Accepted papers will be published in the conference proceedings. However, the necessary condition is that one of authors presents the paper at the conference.
    Paper submission page: Link

    Special Session 4:

    Data-Driven Designation and Implementation of Automated Guided Vehicles

    December 17-20, 2022 Osaka/JAPAN

    The growing popularity of Autonomous Guided Vehicles (AGVs) has not only been the result of their technical features but also their ability to cooperate. Cooperative-based internal logistics enables increased production flexibility. AGVs have become a key enabling technology for the flexible internal logistics that are required for agile production systems. Modern production systems are characterized by frequent changes that result from orders that are changed by customers, low material buffers, the agile production technologies that are performed by robotized production stands and the many variants of production technology that can be used. All of the above-mentioned factors require the production process to be supported online by highly advanced information services, which are performed during successive steps in the production chain. In addition, big and remote sensing data play a fundamental role in AGV, which helps acquire the patterns of driving/travel behaviour, human mobility, and traffic flow, and in sensing a more large-scale environment and giving more accurate, traffic-aware navigation. This means that the production activities cannot be centrally planned but have to be performed cooperatively concerning the sensing data, ongoing production tasks, available materials, production equipment and technologies. The new generation of data-driven systems in AGVs has to support the autonomy and distribution of decision-making processes.

      Thus, this special session is focused on the following issues but not limited to:
    • Data Mining support for Energy and Resource Efficient Internal Logistics
    • Communication between Automated Guided Vehicles and Production Stands and Production System
    • Automated Guided Vehicle Integrated with Collaborative Robot
    • Use Case-based CoBotAGVs Integration with Industry4.0 Production Systems
    • Multi-source sensor data collection, processing and data fusion by collaborative AGV
    • Machine learning-based traffic safety analysis, trajectory and route prediction
    • Data-driven autonomous driving assistance
    • Prediction of traffic flow based on sensing data of AGVs
    • Pavement performance evaluation and predictions of AGVs
    • Architecture design, implementation and case studies of AGVs


    Special Session Organizer:
    Jerry Chun-Wei Lin
    Western Norway University of Applied Sciences, Norway

    Rafał Cupek
    Silesian University of Technology, Poland

    Dariusz Mrozek
    Silesian University of Technology, Poland

    Gautam Srivastava
    Brandon University, Canada

    Important Dates:
    Full paper submission: Oct 15, 2022
    Notification of paper acceptance: Oct 30, 2022
    Camera-ready of accepted papers: Nov 15, 2022
    Conference: Dec 17-20, 2022

    Papers should be submitted as a PDF in 2-column IEEE format. Detailed instructions for the authors can be found on the conference website (https://bigdataieee.org/BigData2022/CallPapers.html).
    Accepted papers will be published in the conference proceedings.
    All accepted papers must be presented by one of the authors in the conference to include the article in the proceedings.
    If you have any question about the special session, please do not hesitate to contact us.

    Paper submission page: Link