Keynote 1
Data, More Data, Too Much Data
Speaker
Tova Milo (Professor, Tel Aviv University)
Abstract
Over the past 30 years, the world of data management has undergone a dramatic evolution, allowing us to consider an increasingly wide range of data types, sources, and processing models. This has also led to the collection of tremendous volumes of data, and we are now at a point where almost every aspect of our lives is data-driven. In this talk, I will share my perspective on some of the “hot topics” that I have been personally involved with in this evolution, and discuss why certain research topics become popular and when they lose their relevance. I will furthermore argue that we are now facing a turning point where the deluge of data has become a serious risk, and that the next “hot” research agenda should focus on data disposal. Despite advances in storage technology, the amount of data generated is projected to surpass storage production by an order of magnitude by 2025, and uncontrolled data retention further poses significant risks to security and privacy. I will discuss the logical, algorithmic, and methodological foundations necessary for the systematic disposal of large-scale data, highlighting new research challenges and the potential for reusing existing techniques. I will also share insights from the research conducted by the Tel Aviv Databases group in this direction.
Bio
Tova Milo is the Dean of the Faculty of Exact Science at Tel Aviv University. She received her Ph.D. degree in Computer Science from the Hebrew University, Jerusalem, in 1992. After graduating she worked at the INRIA research institute in Paris and at University of Toronto and returned to Israel in 1995, joining the School of Computer Science at Tel Aviv university, where she is now a full Professor and holds the Chair of Information Management. She served as the Head of the Computer Science Department from 2011-2014.
Her research focuses on large-scale data management applications such as data integration, semi-structured information, Data-centered Business Processes and Crowd-sourcing, studying both theoretical and practical aspects. Tova served as the Program Chair of multiple international conferences, including PODS, VLDB, ICDT, XSym, and WebDB, and as the chair of the PODS Executive Committee. She served as a member of the VLDB Endowment and the PODS and ICDT executive boards and as an editor of TODS, IEEE Data Eng. Bull, and the LMCS Journal. Tova has received grants from the Israel Science Foundation, the US-Israel Binational Science Foundation, the Israeli and French Ministry of Science and the European Union. She is an ACM Fellow, a member of Academia Europaea, a recipient of the 2010 ACM PODS Alberto O. Mendelzon Test-of-Time Award, the 2017 VLDB Women in Database Research award, the 2017 Weizmann award for Exact Sciences Research, and of the prestigious EU ERC Advanced Investigators grant.
Keynote 2
Querying Structured and Unstructured Data: LLM-first or DB-first?
Speaker
Paolo Papotti (Associate Professor, EURECOM)
Abstract
Is there a way to build data applications on top of information stored both in databases (DBs) and documents in natural language (NL)? We explore the merits and limitations of both Large Language Models (LLMs) and relational databases, questioning whether a LLM-first or a DB-first strategy is more effective to access data in a unified interface. The talk evaluates the role of NL questions and SQL in structured data retrieval and the processing capabilities of the corresponding models. We compare and contrast recent results on these topics and then conclude with an overview of the research challenges in effectively leveraging the combined power of SQL and LLMs.
Bio
Paolo Papotti is an Associate Professor at EURECOM, France since 2017. He got his PhD from Roma Tre University (Italy) in 2007 and had research positions at the Qatar Computing Research Institute (Qatar) and Arizona State University (USA). His research is focused on data management and, more recently, on NLP. He has authored more than 150 publications and his work has been recognized with two “Best of the Conference” citations (SIGMOD 2009, VLDB 2016), three best demo award (SIGMOD 2015, DBA 2020, SIGMOD 2022), and two Google Faculty Research Award (2016, 2020).
Keynote 3
The Path to Support Massive Graphs: Insights into Algorithms, Systems, and Learning
Speaker
Jeffrey Xu Yu (Professor, The Chinese University of Hong Kong)
Abstract
There has been a long history of supporting complex objects in Database Management Systems (DBMSs) since early 1970. With the emergence of online social networks in the 2000s, the focus has shifted towards supporting massive graph data. And graph data has extensive applications across various domains, from transportation and communication networks that form the backbone of our global infrastructure, to economic networks, citation networks, knowledge graphs, etc. Over the decades, the demand for handling such massive graph data has necessitated the design of new graph algorithms and the development of graph processing systems. Furthermore, graph neural networks have added a new dimension to this field. In this talk, we aim at delving deeper into the realm of graph algorithms, graph processing systems, and graph neural networks. We will explore their approaches, and the insights they offer.
Bio
Dr Jeffrey Xu Yu is a Professor in the Department of Systems Engineering and Engineering Management, The Chinese University of Hong Kong. His current main research interests include graph algorithms, graph processing systems, graph neural networks, and query processing in database systems. Dr. Yu served as an Information Director and a member in ACM SIGMOD executive committee (2007-2011), an associate editor of IEEE TKDE (2004-2008), and an associate editor in VLDB Journal (2007-2013). Currently he servers as an associate editor of ACM TODS, WWW Journal, etc. Dr. Yu served/serves in many organization committees and program committees in international conferences/workshops including PC Co-chair of APWeb'04, WAIM'06, APWeb/WAIM'07, WISE'09, PAKDD'10, DASFAA'11, ICDM'12, NDBC'13, ADMA'14, CIKM'15, Bigcomp17, DSAA'19, CIKM'19, and DASFAA'20, and conference general Co-chair of APWeb'13, ICDM'18, and ADC'22.