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DSDM @ VLDB 2022 : Workshop on Data Science for Data Marketplaces @ VLDB 2022 | |||||||||||||||
Link: https://sites.google.com/view/dsdm2022/home | |||||||||||||||
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Call For Papers | |||||||||||||||
Call for Papers
—--------------------------------------------------------- Workshop on Data Science for Data Marketplaces In conjunction with the 48th International Conference on Very Large Data Bases (VLDB) https://sites.google.com/view/dsdm2022/ September 5, 2022 Sydney, Australia —--------------------------------------------------------- We are entering a brave new world ushered in by the global digital transformation. With an estimated more than 2.5 quintillion bytes of data produced every day, data is becoming an independent and strategic asset. There have appeared data marketplaces of various forms, which aim to make access to data a commodity. In these marketplaces, the main idea is to facilitate interaction between data providers (e.g., individuals or organizations that possess data in diverse domains and wish to offer their data to other interested parties) and data consumers who are interested in obtaining data to accomplish certain tasks, such as training new machine learning models, increasing the accuracy of existing ones, and conducting statistical estimation. Since such platforms aim to adopt the characteristics of a marketplace, data exchange carries an underlying cost (e.g., monetary value). The advent of such marketplaces can be viewed as an initial step to the enablement of efficient trading of data, with enormous social and economic benefits. The design of the operating principles, marketplace mechanisms and trading strategies (to name a few topics) of such marketplaces constitute open research directions and involve multiple research communities, such as economics and data science. The theme of this workshop is to address the challenges and opportunities of data management and data science in a data marketplace environment. We welcome submissions presenting interesting and initial ideas that address fundamental research and technical issues in this challenging area and especially encourage reports on system level research and interdisciplinary practice related to data management and data science in data marketplaces. We also welcome new visions and critical reviews on marketplaces. Topics of interest include, but not limited to: - Data valuation - Data pricing - Data acquisition - Data quality measurement - Data utility - Arbitrage and prevention - Game-theoretic approaches to data marketplaces - Privacy issues in data trading - System support for data trading *** Submission Instructions *** We welcome submissions that fall in one of the following two categories with different page limits: (1) vision papers (up to 4 pages), and (2) technical papers, including research papers and application papers (8-12 pages). Submissions are to be formatted following the standard VLDB template available at: http://vldb.org/pvldb/vol15-formatting/ The review process is single-blinded. Authors must include their names and affiliations on the first page of the manuscript. We use CMT’s conflict management system, through which authors should flag conflicts with members of the program committee. To encourage submissions discussing on-going work, papers presented in the workshop are not regarded as formally published, so that they can still be submitted to other venues. *** Submission Site *** https://cmt3.research.microsoft.com/DSDM2022 *** Important Dates *** Paper submission: May 16, 2022 (Anywhere on Earth, UTC-12) Notification of acceptance: June 14, 2022 Camera-ready copies: July 25, 2022 Workshop: September 5, 2022 *** Keynote Speakers *** Professor Yiling Chen, Harvard University Professor Raul Castro Fernandez, University of Chicago *** Workshop Co-Chairs *** Xiaohui Yu, York University, Canada Jian Pei, Simon Fraser University, Canada *** Program Committee *** Anish Agarwal (MIT) Yang Cao (Kyoto University) Raul Castro Fernandez (UChicago) Rubén Cuevas Rumín (Universidad Carlos III de Madrid) Ruoxi Jia (Virginia Tech) Yuqing Kong (Peking University) Jinfei Liu (Zhejiang University) Yang Liu (UC Santa Cruz) Ce Zhang (ETH) |
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