IEEE International Conference on Big Data

    The Special Session on Data Marketing as Cross-disciplinary Data Exchange and Collaboration (CDEC2020)

    –Designing Data Exchange Ecosystem for Human-AI Collaborative Society–

    December 10th-13th, 2020 in conjunction with IEEE BigData 2020, Atlanta, GA, USA Online conference

    News

    Scope

    The recent social movement of big data and artificial intelligence has resulted in a tremendous increase in the importance of data. In view of these expectations, there are the externalizations of interdisciplinary issues. Many papers about data utilization have been published, and several approaches for analyzing data have been shared widely. However, there are only a limited number of studies on the process of cross-disciplinary data exchange and collaboration and its ecosystem. Since this process encompasses various activities of different stakeholders, it is difficult to evaluate the patterns or processes quantitatively. Moreover, in the data market, there are not only big data but also small data necessary for decision making. It is essential to discuss the dynamics of such a network of heterogeneous data in different fields.

    To address these gaps, we propose to hold a third edition of the session to discuss the processes and interactions among data, humans, and society –Data Marketing as Cross-disciplinary Data Exchange and Collaboration (CDEC). The topics taken up at CDEC will involve practical issues such as the analytical tasks performed using data, solutions for challenging social issues, and cross-disciplinary data collaboration and its process. Our special session will target not only cleanly formatted homogenous data, but also heterogeneous data that affect human behaviors, thoughts, and intentions across different domains. We will also focus on a discussion to obtain tacit knowledge of artificial intelligence and data mining by analysis and synthesis. In addition to these research fields, we will attempt to take a cognitive approach toward observing the processes of knowledge discovery and data exchange. It is expected that conflicts and inconsistencies may arise owing to differences in opinion when stakeholders from different knowledge domains have discussions on data-driven decision making. We believe that this special session focusing on the process of cross-disciplinary data exchange and collaboration will have great significance, not only on academia, but also on the society as a whole.

    This year, we are planning to expand the scope beyond the results of data mining, and present, share, and discuss the entire process from data design to analysis by setting the theme as “Designing Data Exchange Ecosystem for Human-AI Collaborative Society.”

    Moreover, we believe that this workshop is a natural extension of the International workshop on the Market of Data (MoDAT), which was conducted as a series at ICDM from 2013 to 2017. In the MoDAT workshops, we discussed approaches toward designing the data market, and proposed solutions leading to productive actions in businesses and sciences spanning the industrial, political, and educational sectors. In the CDEC workshop, we will also discuss the practical feasibility of these applications based on the discussions at MoDAT. We included MoDAT in the Topics of this proposal.

    Topics

    We call for anyone interested in the following topics of Cross-disciplinary Data Exchange and Collaboration.

    Data Mining Application Areas:

    • Statistical Graphics and Mathematics
    • Financial, Security and Business
    • Physical Sciences and Engineering
    • Earth, Space, and Environmental Sciences
    • Geographic/Geospatial/ Terrain Data Mining
    • Text, Documents and Software
    • Social, Ambient and Information Sciences
    • Multimedia (Image/Video/Music) Mining

    Case Studies on Data Exchange and Collaboration:

    • Methods for data evaluation and utilization
    • Data management and curation
    • Risks, limitations, and challenges of Data Exchange
    • Trust, resilience, privacy and security issues
    • Design of Data

    Empirical And Comprehension Focused Data Mining:

    • Modeling of Machine Learning for Social Data
    • Data Mining and Machine Learning Methods Based on Empirical Knowledge
    • Ontology and Dictionary
    • Business Efficiency
    • Cognition and Perception Issues
    • Natural Language Processing Text mining
    • Retrieval/recommender systems

    Data Focused Visualization Research:

    • High-Dimensional Data, Dimensionality
    • Reduction, and Data Compression
    • Multidimensional Multi-Field, Multi-Modal, Multi-Resolution and Multivariate Data
    • Causality and Uncertainty Data
    • Time Series, Time Varying, Streaming Data
    • Point-Based Data and Large Scale Data

    Data Focused Cognitive Research:

    • Human-Computer Interaction, Cognitive Science, and Behavioral Science and Modeling, including quantitative and qualitative results
    • Theoretical models, technological advances and experimental methods of Human-Computer Interaction, Cognitive Science, and Behavioral Science and Modeling

    Market of Data

    • Process and Technologies for Data Exchange
    • Representation of Knowledge and Requirements
    • Pricing and Evaluating Mechanism of Data
    • Design of Data Platform
    • Data Acquisition, and Sensors

    Key Dates

    All deadlines are at 11:59PM Pacific Standard Time (PST).
    • Full paper submissions: August 31, 2020
    • Full paper submissions: September 30, 2020 (extended)
    • Full paper submissions: October 9, 2020 (extended)
    • Paper notification: October 16, 2020
    • Paper notification: October 26, 2020
    • Camera-ready deadline and copyright forms: November 10, 2020
    • Conference dates: December 10-13, 2020

    Submission

    Paper submissions should be limited to a maximum of ten (10) pages, in the IEEE 2-column format (link), including the bibliography and any possible appendices. Submissions longer than 10 pages will be rejected without review.

    Note that all accepted papers will be included in the Proceedings volume in the IEEE Xplore Digital Library. ​​Therefore, papers must not have been accepted for publication elsewhere or be under review for another workshop, conferences or journals.

    The submission guidline has been confirmed by the IEEE BigData chairs. Please read carefully the following instructions.

    • 1. Papers with more than 8 pages will need to pay extra page fee. The allowed max page is 10 pages.
    • 2. The extra page fee is 100US$ per page.

    Go to Submission Page

    Schedules and Invited Speakers



    Go to Schedule

    Organizers

    hayashi

    Teruaki Hayashi (PhD)

    The University of Tokyo

    CV

    Teruaki Hayashi is an Assistant Professor of Systems Innovation affiliated to the School of Engineering at the University of Tokyo, and vice chairman of the Application Committee at the Data Trading Alliance. He received his Ph.D. (Engineering) from the University of Tokyo. Hayashi’s specialization is in knowledge structuring for Data Utilization and Scenario Creation. He developed Data Jacket, a method for summarizing the information in data, as his core research and applied the results to the industry, government, and academia internationally. He was awarded the Dean’s Award by the School of Engineering at the University of Tokyo in 2017, and an Excellence Award at the 23rd Annual Conference of the Japanese Society of Artificial Intelligence in 2018. He is also the co-author of a book “Market of Data” Kindaikagakusha (2017).

    ohsawa

    Yukio Ohsawa (PhD, Professor)

    The University of Tokyo

    CV

    Yukio Ohsawa is a Professor of Systems Innovation with the School of Engineering at the University of Tokyo. He received a PhD from the School of Engineering at the University of Tokyo (1995). Then, he worked at the School of Engineering Science at Osaka University (research associate, 1995-1999), Graduate School of Business Sciences at the University of Tsukuba (associate professor, 1999-2005), and moved back to the University of Tokyo. In the field of artificial intelligence, he has created a new domain Chance Discovery to discover events with significant impact on decision making. He has delivered many keynote talks about Chance Discovery in conferences such as the International Symposium on Knowledge and Systems Sciences, International Conference on Rough Sets and Fuzzy Sets, Joint Conference on Information Sciences, and Knowledge-Based Intelligent Information and Engineering Systems. Chance Discovery has been embodied as an innovators’ marketplace, a methodology for innovation that is borrowed from principles of market dynamics. His original concepts and technologies have been published as books and monographs by global publishers such as Springer Verlag and Taylor and Francis. The two most important books among these are “Chance Discovery” (2003 Springer, Eric von Hippel gave the opening) and “Innovators’ Marketplace: Using Games to Activate and Train Innovators” (2012 Springer, Larry Leifer gave the opening). He has edited special issues as a guest editor for journals mainly related to chance discovery such as Intelligent Decision Technologies (2016), Information Sciences (2009), New Generation Computing (2003), and the Journal of Contingencies and Crisis Management (2002). He has also published 100 journal papers and made several presentations at conferences. He has initiated symposia and workshops on data-based approaches toward business innovation.

    fukami

    Yoshiaki Fukami (PhD)

    Gakushuin University/ Keio University

    CV

    Yoshiaki Fukami is a Specially Appointed Associate Professor of Graduate School of Media and Governance at Keio University, and chairman of the International Standardization Strategy Committee at the Data Trading Alliance. Then, He worked at Rikkyo Business School (Specially Appointed Associate Professor, 2015-2020). He was a director of The Japan Society for Management Information (2017-2019). He received his Ph. D. (Media and Governance) from Keio University. Fukami's specialization is in standardization strategy, platform strategy, open collaborative innovation. He has contributed to Open data technical strategy of government at the Vitalizing Local Economy Organization by Open Data & Big Data (a member of Technical Committee), the Committee at the Infrastructure for Multi-layer Interoperability Working group, the Committee at The Research Committee of Scheme for Interoperability of Public-sector Information, and Technical Committee at the Open Data Promotion Consortium. Information-technology Promotion Agency, Japan. He has also contributed to web standardization activities at the World Wide Web Consortium. He was awarded the Young Investigator Award 2018 autumn by Japan Society for Information and Management. He is the author of books; “Utilizing web application for your business” (Discover Twenty-One Publishing, 2010), “Metadata is changing the world” (NTT Publishing, 2009), and chapter; Platform Strategy suited for IoT based technology: How to Develop and Engage Ecosystems, in "Business Design and Business Science" (Soseisha, 2016), Behavior Analysis in Activities for Building Ecosystems: Competitive Strategy of Platforms in Standardizing Processes in "Platform for Emergence" (Nikkei Newspaper Publishing, 2011). He is also the editor of a book; "Technical review of HTML5 to enhance skills for web contents development” (RIC Telecom Publishing, 2012).

    navez

    Didier Navez

    Dawex

    CV

    Didier Navez is Senior Vice President of Strategy and Alliances at Dawex, a company pioneering the data economy and the leading provider of data exchange and marketplace technology. A thought leader in the domain of digital and data strategy, data monetization, ecommerce and mobile, Didier worked for over 10 years with leading technology research firms Gartner and Forrester, advising business and technology leaders in their digital transformation journeys, across Europe and North America. He previously had leading roles at international consultancies and technology firms, including CSG International and Texas Instruments. Didier holds an MBA from Solvay Brussels School with a specialization in Finance.

    Organizing Committee

    Note: Since we are contacting to other researchers, more program committees will be added to the list.

    Advisory

    • Shusaku Tsumoto, Department of Medical Informatics, Shimane University, Japan
    • Randy Goebel, Computing Science in the Department of Computing Science at the University of Alberta, Canada
    • Seiji Yamada, National Institute of Informatics, Japan

    Co-chairs

    • Teruaki Hayashi, The University of Tokyo, Japan
    • Yukio Ohsawa, The University of Tokyo, Japan
    • Yoshiaki Fukami, Gakushuin University/ Keio University, Japan
    • Didier Navez, Dawex, France

    Program Committee

    • Akinori Abe, Chiba University, Japan
    • Chengjie Sun, Harbin Institute of Technology, China
    • Eiji Murakami, Azbil Kimmon Co.Ltd., Japan
    • Dominik Ślęzak, Warsaw University, Poland
    • Hiroki Sakaji, The University of Tokyo, Japan
    • Hiroyasu Matsushima, Shiga University, Japan
    • Jun Nakamura, Chuo University, Japan
    • Junheng Hao, University of California, Los Angeles, USA
    • Kiyoshi Izumi, The University of Tokyo, Japan
    • Mi-Young Kim, The University of Alberta, Canada
    • Takumi Shimizu, Waseda University, Japan
    • Naohiro Matsumura, Osaka Univeristy, Japan
    • Noriyuki Kushiro, Kyushu Institute of Technology, Japan
    • Sindhu Hak Gupta, Amity University, India
    • Yasufumi Takama, Tokyo Metropolitan University, Japan

    Our Past Records

    As part of the ICDM (International Conference on Data Mining) workshops, we successfully conducted the 1st and 2nd International Workshop on CDEC at Singapore and Beijing (2018 and 2019). Seven distinguished papers were accepted after a triple blind review process (the acceptance rate: 43%) and presented to an audience of approximately 30 participants in 2018. In 2019, 10 papers have been accepted and been presented (the acceptance rate: 48%) after a triple blind review process. Thanks to the editors of MDPI, a special issue of CDEC was issued in the Information Journal (ISSN 2078-2489) after the conclusion of the workshop under the section “Information and Communications Technology.”

    CDEC Series

    Moreover, we have had experience in initiating and conducting the MoDAT workshop at ICDM from 2013 to 2017. According to the workshop committee of ICDM 2013, MoDAT was reported to the steering committee as the best of all the 17 workshops in the conference. Moreover, MoDAT was selected as one of the nine full day workshops from among 30 proposals for ICDM 2014 according to Wei Wang and Zhi-Hua Zhou, the workshop chairs of ICDM 2014. MoDAT was included both in ICDM 2015 and ICDM 2017 as a full day workshop. Furthermore, we organized and are organizing the following workshops/sessions about data-based approaches to chance discovery and MoDAT: Chance Discovery and Data Synthesis (more than 30 international workshops and symposia, including IJCAI 2015, IJCAI 2011, ECAI 2016, ECAI 2011, ICDM 2010, ECAI2004, KES2000-2019, AAAI Springer Symposia 2001).

    past1 past2 past3 past4 past6 past7

    Contact

    Dr. Teruaki Hayashi (co-chair)

    Email: hayashi -at- sys.t.u-tokyo.ac.jp

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