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 mining 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 based on the knowledge acquired by data mining. Since this process encompasses various activities of different stakeholders, it is difficult to evaluate the patterns or processes quantitatively.
To address this knowledge gap, we propose to hold a second edition of the workshop to discuss data-driven decision making focusing on the processes and interactions among data, humans, and society – 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 workshop 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 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 a workshop 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.
As part of the ICDM Workshop in 2018, we successfully conducted the 1st International Workshop on CDEC at Singapore. Seven distinguished papers were accepted after a triple blind review process (total acceptance rate was 43%). In the half-day workshop, 10 presentations (7 research presentations, 2 position talks, and 1 invited talk) were made to an audience of approximately 30 participants. 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.”
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 “Design, Acquire, and Integrate Data for Valuable Knowledge Discovery.”
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.
We call for anyone interested in the following topics of Cross-disciplinary Data Exchange and Collaboration.
Data Mining Application Areas:
Case Studies on Data Exchange and Collaboration:
Empirical And Comprehension Focused Data Mining:
Data Focused Visualization Research:
Data Focused Cognitive Research:
Market of Data
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 2019 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.
Dawex (co-Founder and co-CEO)
In June 2019 at the G-20 summit, world leaders adopted Osaka Track to formulate rules on digital governance under the concept of “Data Free Flow with Trust”. This is following the European Commission initiative and guidance on free flow of non-personal data. Considering that today 70% of data exchanges occur between organizations from different sectors and 50% are cross-border, within a data economy that is accelerating, frameworks are being designed to bring the full value of data exchange. Which are the latest data exchange trends? What are the benefits from cross-domain data exchanges and how public/private sectors can collaborate? What are the needs for centralized or decentralized data exchange platforms? Fabrice Tocco, co-Founder and co-CEO of Dawex, will share his view of the future of the data economy.
Fabrice Tocco, serial entrepreneur, co-founder and co-CEO of Dawex, is a recognized expert in the data economy, and regularly invited to engage with the European and international institutions as a speaker. He strongly believes that data is the mirror of the economy, and that boosting tomorrow’s economy requires from organizations to position data exchange at the core of their business strategy. In 2015, Fabrice jumped into his second entrepreneurial adventure with Laurent Lafaye and co-created Dawex. The company’s mission is to build the conditions for the smooth development of the data economy by facilitating data exchange between companies and organizations. Dawex operates the largest data marketplace to date and develops cutting-edge technologies for data trading with the ambition to become the world’s leading Data Exchange. Fabrice started his career at a world leader in the tire industry taking responsibilities in the group marketing and innovation divisions. Fabrice graduated from Reims Management School, Neoma Business School, in France.
D-Ocean, Inc. (CTO)
Social Data Platform, D-Ocean is data focused Social Networking Service which is available globally to help people finding and sharing data with others. D-Ocean isn't just a collection of data sets, but also focuses on people who have contributed to the data economy. Users, such as data scientists, data engineers and etc., can be assessed by others fairly. In this session, I will explain how D-Ocean provides capability as Data Exchanges and also Social Networking Service. I will also introduce use cases where users find new insights which can only be found by mixing with data from other users and how D-Ocean helps those users using unique features as online platform.
Teppei Yagihashi is CTO and Co-Founder of D-Ocean, Inc. D-Ocean provides the world’s first data platform which combines data exchange and social networking service. He established D-Ocean in 2017 and has been developing D-Ocean platform. He already applied for a few patents related to data exchange platform in Japan as well as other foreign countries. Before D-Ocean, he has been working for Google Cloud division as solutions architect and published papers related to mobile, IoT and data management products. He also worked for Amazon Web Services as solutions architect to help customers in various industries to implement cloud native services. He was awarded for the Best Solutions Architect of the year in 2014. As his personal project, he contributed to NATS open-source project and has developed and maintained Java / Scala client libraries for several years.
Teruaki Hayashi (PhD)
The University of Tokyo
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).
Yukio Ohsawa (PhD, Professor)
The University of Tokyo
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.
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.
As part of the ICDM Workshop 2018, we successfully conducted the 1st International Workshop on CDEC in Singapore. Seven distinguished papers were accepted from a triple blind review process (total acceptance rate was 43%). In our half-day workshop, 10 presentations (7 research presentations, 2 position talks, and 1 invited talk) were made to an audience of approximately 30 participants. At the end of the workshop, we recognized the most inspiring and effective presentations and papers. In the afternoon, we had a technology demonstration and discussion of collaboration at Dr. Julian Kuiyu Chang’s office in Singapore.
Thanks to the editors of MDPI, we brought out a special issue of CDEC in the Information Journal (ISSN 2078-2489) after the conclusion of the workshop under the section “Information and Communications Technology.”
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).
Dr. Teruaki Hayashi (co-chair)
Email: hayashi -at- sys.t.u-tokyo.ac.jp