EDBT/ICDT Joint Session on Research Challenges

organized by Dan Olteanu, University of Oxford


Data Privacy in the Cloud: Challenges and Opportunities

Amr El Abbadi, University of California, Santa Barbara


Abstract: Storing data in cloud storage has been increasing in popularity, giving rise to increasing concerns about data security and privacy. Both the database and the cryptography and security communities have been exploring and developing techniques that maintain the privacy of query access and data processing, while scaling to the ever increasing sizes of data stored in the cloud. In this talk, we will discuss some recent advances, and explore future challenges and opportunities for research at the boundaries of theoretical security and privacy approaches in a systems and database applications context.

Amr El Abbadi is a Professor of Computer Science at the University of California, Santa Barbara. He received his B. Eng. from Alexandria University, Egypt, and his Ph.D. from Cornell University. Prof. El Abbadi is an ACM Fellow, AAAS Fellow, and IEEE Fellow. He was Chair of the Computer Science Department at UCSB from 2007 to 2011. He has served as a journal editor for several database journals and has been Program Chair for multiple database and distributed systems conferences. He currently serves on the executive committee of the IEEE Technical Committee on Data Engineering (TCDE) and was a board member of the VLDB Endowment from 2002 to 2008. In 2007, Prof. El Abbadi received the UCSB Senate Outstanding Mentorship Award for his excellence in mentoring graduate students. In 2013, his student, Sudipto Das received the SIGMOD Jim Gray Doctoral Dissertation Award. Most recently Prof. El Abbadi was the co-recipient of the Test of Time Award at EDBT/ICDT 2015. He has published over 300 articles in databases and distributed systems and has supervised over 35 PhD students.


Databases & People: Time to Move on From Baby Talk

Georgia Koutrika, Athena Research Center


Abstract: The advent of computers radically improved mankind’s opportunities to access information. Unfortunately, the volume and complexity of available data preclude easy access for most people but technical experts. For the majority, the road to information goes through simple search tools that allow their users to receive answers to simple questions. Recent years have witnessed a shift in information access interfaces with the rise of chatbots and natural language database interfaces. Chatbots can understand simple, unambiguous questions like “what the weather forecast is today” or “I want to order flowers”. Natural Language Interfaces to Databases can translate (some) natural language questions over a database to queries in the underlying system language and can translate (some) results back to NL. This baby talk with data is fun but at the end of day creates a huge appetite for more: more intelligent, more knowledgeable, more personalized conversation between the two tribes: People and Databases.

Georgia Koutrika is Director of Research at Athena Research Center in Greece. In the past, she worked at HP Labs, at IBM Research-Almaden, and as a postdoctoral researcher at the Computer Science Dept., Stanford University. She has received a PhD and a diploma in Computer Science from the University of Athens in Greece. Her work is in the broader area of big data and in the intersection of databases, information retrieval, and machine learning, and involves: personalization and recommendation systems, user profiling and user analytics, query and data exploration paradigms for databases, and large-scale information extraction, entity resolution and information integration. Her work has been incorporated in commercial products, has been described in 7 granted patents and 19 patent applications in the US and worldwide, and has been published in more than 80 research papers in top-tier conferences and journals. She has served as a General Co-Chair for ACM SIGMOD 2016, Industrial Track PC Chair for EDBT 2016, and Workshop and Tutorial Co-Chair for IEEE ICDE 2016. She is currently Demo PC co-chair for ACM SIGMOD 2018 and Associate Editor for VLDB 2019.


Some Challenges in Approximate Query Processing

Peter Haas, University of Massachusetts Amherst


Abstract: Approximate query processing (APQ) techniques are crucial for enabling analysts to deal with data that is massive in size, arrives at blinding speeds, and must be processed within interactive or quasi-interactive time frames. APQ is a necessary supplement to parallel processing methods because, unlike parallel processing, AQP does not require large investments of money and energy, and can be deployed on platforms where memory and processing power are limited, such sensors and other internet-of-things devices. APQ methods typically operate by querying or analyzing a synopsis, i.e., a lossy compressed representation of the original data. We give a brief overview of APQ methods and data synopses, and discuss some interesting theoretical and practical research directions. The goal is to improve not only the scope and efficiency of the algorithms themselves, but also their consumability by analysts.

Peter J. Haas is a Professor in the College of Information and Computer Sciences at the University of Massachusetts Amherst. Prior to that, he was a Principal Research Staff Member at the IBM Almaden Research Center, where from 1987-2017 he pursued research at the interface of information management, applied probability, statistics, and computer simulation. He was also a Consulting Professor in the Department of Management Science and Engineering at Stanford University from 1992-2017. He was designated an IBM Master Inventor in 2012, and his ideas have been incorporated into products including IBM's DB2 database system. He is a Fellow of both ACM and INFORMS, and has received a number of awards from IBM and both the Simulation and Computer Science communities, including the VLDB 2016 Best Paper Award and the 2007 ACM SIGMOD 10-year Best Paper Award. He is the author of over 130 conference publications, journal articles, and books, and has been granted over 30 patents.

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