日本データベース学会のみなさま， 阪大の鬼塚です． 東京で開催される国際会議 VLDB2020 の併設ワークショップ Poly'20: Polystore systems for heterogeneous data in multiple databases with privacy and security assurances のご案内です． データ発見，データ統合，データクリーニング，プライバシーに関する研究を広く公募します． 詳細は以下のようになっておりますので，ご投稿をご検討頂けますようよろしく お願いいたします． Workshop site: https://sites.google.com/view/poly20/home Submission deadline August 5, 2020 CALL FOR PAPERS Poly'20: Polystore systems for heterogeneous data in multiple databases with privacy and security assurances Co-located with VLDB 2020 Conference date: August 31, 2020 Location: Tokyo, Japan (Virtual) Website: https://sites.google.com/view/poly20/home Important Dates (Extended): July 15, 2020: Due date for full workshop papers submission August 1, 2020: Notification of paper acceptance to authors August 5, 2020: Camera ready version of workshop papers August 31, 2020: Workshop (will be virtual) Introduction: Enterprises are routinely divided into independent business units to support agile operation. However, this leads to "siloed" information systems. Such silos generate a host of problems, such as: -DISCOVERY of relevant data to a problem at hand. For example: Merck has 4000 (+/-) Oracle databases, a data lake, large numbers of files and an interest in public data from the web. Finding relevant data in this sea of information is a challenge. -INTEGRATING the discovered data. Independently constructed schemas are never compatible. -CLEANING the resulting data. A good figure of merit is that 10% of all data is missing or wrong. -ENSURING EFFICIENT ACCESS to resulting data. At scale operations must be performed "in situ", and a good polystore system is a requirement It is often said that data scientists spent 80% (or more) of their time on these tasks, and it is crucial to have better solutions. In addition, the EU has recently enacted GDPR that will force enterprises to assuredly delete personal data on request. This "right to be forgotten" is one of several requirements of GDPR, and it is likely that GDPR-like requirements will spread to other locations, for example California. In addition, privacy and security issues are increasingly an issue for large internet platforms. In enterprises, these issues will be front and center in the distributed information systems in place today. Lastly, enterprise access to data in practice will require queries constructed from a variety of programming models. A "one size fits all" mentality just won't work in these cases. At IEEE BigData'16, BigData'17, VLDB'18, and VLDB'19 we organized workshops on Polystore systems. These successful workshops brought together experts from around the world working on novel advances in the field. Poly'20 will continue to focus on the broader real-world polystore problem, which includes data management, data integration, data curation, privacy and security. In the past, conference proceedings have been published as a part of the Springer Lecture Notes in Computer Science. This year's workshop will be virtual. Research topics included in workshop: *Research Topics Included: *Privacy, Security, and Policy in heterogenous data management. *Languages/Models for integrating disparate data such as graphs, arrays, relations *Query evaluation and optimization in polystore and other multi-DBMS systems *Efficient data movement and scheduling, failures and recovery for polystore analytics *High Performance/Parallel Computing Platforms for Big Data *Data Acquisition, Integration, Cleaning, and Best Practices *Privacy and Access control in Polystore and multi-DBMS systems *Enterprise support for GDPR and similar privacy regulations *Policy implications of GDPR and similar privacy regulations *Mathematics for Polystore and other multi-DBMS systems *Demonstrations of new tools and techniques for heterogeneous data Submissions: Please visit: https://sites.google.com/view/poly20/submission Workshop Organizers: Vijay Gadepally, MIT Lincoln Laboratory Danny Weitzner, MIT Internet Policy Research Initiative Michael Gubanov, FSU Edmon Begoli, ORNL Dimitris Kolovos, University of York Amarnath Gupta, UCSD Ratnesh Sahay, AstraZeneca Rada Chirkova, NCSU Sam Madden, MIT Tim Kraska, MIT Timothy Mattson, Intel Corporation Michael Stonebraker, MIT Makoto Onizuka, University of Osaka