[Invited Talk] Facilitating Collaborative Data Sharing

The majority of data integration systems, architectures, and implementations tend to focus on providing a single point of access (with a single unified schema and consistent data instance) over diverse data. This is often appropriate for a single enterprise -- but it faces many challenges in collaborative settings across organizations or research communities. We outline several data management research challenges we have encountered in fostering collaborative data sharing environments in the sciences, and describe technical solutions that use provenance and context to determine what data is relevant to a given user. We also outline how modern approaches to data science are changing the problems of data sharing and data management.
Zachary G. Ives (University of Pennsylvania)
Zachary Ives is the Chair and Adani President's Distinguished Professor of Computer and Information Science at the University of Pennsylvania. He is a co-founder of Blackfynn, Inc., a company focused on enabling life sciences research and discovery through data integration. Zack's research interests include data integration and sharing, big data analytics, scientific data management, and data provenance and authoritativeness. He is a recipient of the NSF CAREER award, and an alumnus of the DARPA Computer Science Study Panel and Information Science and Technology advisory panel. He has also been awarded the Christian R. and Mary F. Lindback Foundation Award for Distinguished Teaching. He is a co-author of the textbook Principles of Data Integration, and has received 10-year most-influential paper awards from the International Conference on Data Engineering (2013) and International Semantic Web Conference (2017). He has served as a Program Co-Chair for the ACM SIGMOD conference (2015) as well as an Associate Editor for Proc. VLDB, the VLDB Journal, and the IEEE Transactions on Data and Knowledge Engineering.

[Invited Talk] Reversible Programming Languages and Reversible Programming

We illustrate the principles of reversible programming languages with reference to the design and implementation of reversible imperative languages, namely, Janus and a family of R-WHILE languages. The theoretical basis of structured programming in high-level reversible languages is provided by a reversible version of the structured program theorem. Each atomic step of a reversible program must correspond to a partial injective function, conforming to a logically reversible update. As only trivial standard interpreters can be realized in reversible languages, we extend the usual definition of a standard interpreter to be reversible. We illustrate reversible interpreters in imperative reversibly universal (r-Turing-complete) languages. Reversible interpreters are useful constructs for a basis for future work on reversible computability and complexity theory. Furthermore, we show that one of these interpreters is linear-time and linear-space. Using the reversible imperative languages, we aim to efficiently reversibilize a family of algorithm strategies. In this presentation, we illustrate two examples: reversible comparison sorts and the reversible version of memoization. We also introduce a measure of efficiency of reversible programs. The proposed programs include efficient reversible simulation of comparison sorts and share the form of garbage data. The resulting reversible program of memoization is the abstract interpretation of reversible binary counters. We show that given any sequence represented by injective recurrence relations there is a reversible program with constant amortized time and constant garbage usage.
Tetsuo Yokoyama (Nanzan University)
Tetsuo Yokoyama is an Associate Professor at the Department of Software Engineering, Nanzan University. He received his Ph.D. in Information Science and Technology from the University of Tokyo in 2006. He was a researcher at the Center for Embedded Computing Systems, Nagoya University from 2007 to 2009; an Assistant Professor from 2009 to 2011 at the Department of Software Engineering, Nanzan University.