IEEE International Conference on Data Mining

    The 1st International Workshop on Cross-disciplinary Data Exchange and Collaboration (CDEC)

    November 17th, 2018 in conjunction with IEEE ICDM 2018, Singapore

    News

    Scope

    Due to recent social movement of big data and artificial intelligence, the importance of data and data mining has been increasing. In the background of these expectations, there are the externalizations of interdisciplinary issues. Many papers about data mining have been published, and the processes of analyzing data have been shared widely. However, there are not many studies targeting the process of cross-disciplinary data exchange and collaboration using knowledge acquired by data mining. Because cross-disciplinary data exchange and collaboration includes various activities of different stakeholders, it is difficult to evaluate the patterns or the processes quantitatively. To tackle the above problems, we propose a practical workshop to discuss the data-driven decision making focusing on the processes and the interactions among data, humans, and society.

    The workshop is Cross-disciplinary Data Exchange and Collaboration (CDEC). CDEC includes the practical fields which analytically performs the topics using data, the challenging solutions against social issues, and the cross-disciplinary data collaboration and its process. Our workshop targets not only cleanly formatted single data but also heterogeneous data which affect human behaviors, thoughts, and intentions in different domains. We also focus on the discussion to obtain tacit knowledge of data mining by analysis and synthesis. In addition to these research fields, the cognitive approach for observing the processes of knowledge discovery and data exchange is also included in our focus. Conflicts and inconsistencies may arise due to diversity when stakeholders with different knowledge have discussions on data-driven decision making. We believe the workshop focusing on the process of cross-disciplinary data exchange and collaboration has great significance not only on academic fields but also on beyond academia in the society.

    This workshop is a natural extension of MoDAT (International workshop on the Market of Data), which had been conducted as a series of workshops in ICDM in the past five years from 2013 to 2017. In MoDAT workshops, we discussed how to design the market of data, and solutions leading productive actions in businesses and sciences – including industrial, political, and educational sectors – had been created. In the workshop of CDEC, we also discuss the practicality of these applications based on the discussions of MoDAT.

    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
    • Network Mining
    • Data Mining for marketing

    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

    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

    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
    • Large Scale 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

    Key Dates

    All deadlines are at 11:59PM Pacific Time.
    • Workshop paper submissions: August 7, 2018
    • Workshop paper submissions: August 14, 2018 (extended)
    • Workshop paper notification: September 4, 2018
    • Camera-ready deadline and copyright forms: September 15, 2018
    • Camera-ready deadline and copyright forms: September 13, 2018
    • Workshop dates: November 17, 2018

    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 IEEE ICDM 2018 Workshops Proceedings volume published by IEEE Computer Society Press, and will also be included 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 ICDM Workshop chairs. Please read carefully the following instructions.

    • 1. Authors can choose short papers (maximum 4 pages) or long papers (maximum 10 pages) for the submission.
    • 2. Papers with more than 8 pages will need to pay extra page fee. The allowed max page is 10 pages.
    • 3. The norm for ICDM workshop papers is 10 pages (2 extra page fee).

    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 at The University of Tokyo. He received Ph.D. in Department of Systems Innovation from The University of Tokyo (2017). From 2017, he has been an Assistant Professor at the Department of Systems Innovation, The University of Tokyo. His main research topics are knowledge structuring, data management, retrieval system, and human behavior modeling in the market of data. He got Dean's Award of Engineering in Social Contribution and Student Leadership Award in Leading program of The University of Tokyo in 2017 in his research and social activities using Data Jackets. Data Jacket is a framework for describing an overview of data while keeping data itself confidential. He conducted over 100 workshops on cross-disciplinary data exchange and collaboration using Data Jackets involving over 200 companies and institutions in total since 2011. He had 11 domestic and 2 international invited talks about Data Jackets and knowledge structuring. For the international research activities, he is the Scientific Committee member of The 23rd Annual Workshop on Economic Science with Heterogeneous Interacting Agents (WEHIA2018) and International Programme Committee member of International Conference on Knowledge-Based and Intelligent Information and Engineering Systems 2018 (KES2018). For the domestic research activities, he published the book about "Market of Data" (Eds. Yukio Ohsawa) in Japanese in 2017, and edited and published the special issue named "AI and Data --Data driven decision making and social innovation--" at the Japan Society for Artificial Intelligence in 2018. Based on the international and domestic activities using Data Jackets, he started Data Jacket Association with Professor Ohsawa and is in charge of the chairperson of the group involving nine companies and institutions. As the social activities, he is the special member of Data Trading Alliance (DTA) in Japan, and in charge of the Vice Chairperson of Data Utilization Promotion Committee and the expert adviser of the Data Catalog Standardization Project in DTA.

    ohsawa

    Yukio Ohsawa (PhD, Professor)

    The University of Tokyo

    CV

    Yukio Ohsawa is a professor of Systems Innovation in the School of Engineering. He received BE, ME, and PhD in from the School of Engineering, The University of Tokyo (1995). Then worked for the School of Engineering Science in Osaka University (research associate, 1995-1999), Graduate School of Business Sciences in University of Tsukuba (associate professor, 1999-2005), and moved back to The Univ. of Tokyo. He started researches from non-linear optics, and, via artificial intelligence, created a new domain chance discovery meaning to discover events of significant impact on decision making, since year 2000. About chance discovery he gave keynote talks in conferences such as International Symposium on Knowledge and Systems Sciences, Int’l Conf. on Rough Sets and Fuzzy Sets, Joint Conf. on Information Sciences, Knowledge-Based Intelligent Information and Engineering Systems, etc. Chance discovery came to be embodied as innovators’ marketplace, a methodology for innovation borrowing principles of the dynamics of markets. Then he, when biking from his job in a business school, invented the basic idea of Data Jackets as a new tool for enhancing chance discoveries via combining data from various data owners. Since then, he is introducing the method presented in this book to sciences, educations, and businesses. His original concepts and technologies have been published as books and monographs from global publishers such as Springer Verlag, Taylor and Francis, etc. Two most important books among them are, "Chance Discovery" (2003 Springer, foreword given by Eric von Hippel), "Innovators’ Marketplace: Using Games to Activate and Train Innovators” (2012 Springer, foreword given by Larry Leifer). He edited special issues as guest editors for journals, mainly relevant to chance discovery, such as Intelligent Decision Technologies (2016), Information Sciences (2009), New Generation Computing (2003), Journal of Contingencies and Crisis Management (2002), etc.

    Organizing Committee

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

    This workshop is supported by Data Jacket Association.

    Advisory

    • Randy Goebel, 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

    Program Committee

    • Akinori Abe, Chiba University, Japan
    • Eiji Murakami, Azbil Kimmon Co.Ltd., Japan
    • Dominik Ślęzak, Warsaw University, Poland
    • Hiroki Sakaji, The University of Tokyo, Japan
    • Jun Nakamura, Shibaura Institute of Technology, Japan
    • Junheng Hao, University of California, Los Angeles, USA
    • Kiyoshi Izumi, The University of Tokyo, Japan
    • Kuiyu Chang, LinkSure, Singapore
    • Hiroyasu Matsushima, The University of Tokyo, Japan
    • Mi-Young Kim, The University of Alberta, Canada
    • 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

    We initiated MoDAT workshop since 2013, in ICDM2013. According to the workshop committee of ICDM2013, our workshop has got reported to the steering committee as the best of all 19 workshops in the conference. Also we organized workshops that are linked to the present proposal. That are about data-driven approaches to business strategies such as Chance discovery and Data Synthesis (more than 30 international workshops and symposia, including ICDM 2010, AAAI Springer Symposia 2001, IJCAI 2011, ECAI2004, ECAI2011, KES2000 till 2013) Discovery, Decision, and Design (IEEE SMC 2005-2011), and other workshops organized by the Technical Committee of Information Systems for Design and Marketing: Ohsawa (the chair) has been and is the TC chair of Information Systems for Design and Marketing, in SMC society of IEEE. If we count those including any of the program committee members, the record will be too large to list here, e.g., workshops on data based marketing where business people and data scientists meet. Also we edited Special Issues as guest editors for international journals, mainly relevant to chance discovery. The journals were: International Journal of Knowledge and Systems Science (2013), International Journal of Organizational and Collective Intelligence (2011), International Journal of Advanced Intelligence Paradigms (2010), Information Sciences (2009), International Journal of Knowledge-based and Intelligent Engineering Systems (2007,2008), New Mathematics and Natural Computation (2006), New Generation Computing (2003), and Journal of Contingencies and Crisis Management (2002).

    Ohsawa et al. organized relevant workshops so far, since year 2000. That are about data-driven approaches to business strategies such as Chance discovery and Data Synthesis (more than 30 international workshops and symposia, including ICDM 2010, AAAI Springer Symposia 2001, IJCAI 2011, ECAI2004, ECAI2011, KES2000 till 2013) Discovery, Decision, and Design (IEEE SMC 2005-2011), and other workshops organized by the Technical Committee of Information Systems for Design and Marketing: Ohsawa (the chair) has been and is the TC chair of Information Systems for Design and Marketing, in SMC society of IEEE. If we count those organized by any workshop members, the record will be too large to list here, e.g., workshops on semantic web, linked open data, data based marketing, etc., where business people and data scientists meet.

    Special Issue (NEW!!)

    Thanks to editors of MDPI, we decided "CDEC: Cross-disciplinary Data Exchange and Collaboration" as a special issue of Information (ISSN 2078-2489). This special issue belongs to the section "Information and Communications Technology".

    We believe that this Special Issue provides a chance of reaching even broader audiences to the authors of CDEC 2018, who are therefore invited to submit extended versions of their papers to the Special Issue. However, authors interested in extending their workshop papers must be aware that the final submitted manuscript must provide a minimum of 50% new content and not exceed 30% copy/paste from the proceedings paper. Each manuscript will be blind reviewed by MDPI academic editors.

    Deadline for manuscript submissions: 28 February 2019

    Web page of the SI is available here

    Contact

    Dr. Teruaki Hayashi (co-chair)

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

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