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PODS Invited Talks


Foundations of Data Aware Process Analysis: A Database Theory Perspective

Diego Calvanese, Free University of Bozen-Bolzano (with Giuseppe De Giacomo, Sapienza University of Rome; Marco Montali, Free University of Bozen-Bolzano)


We recall the research on foundations of data-aware (business) processes that has been carried out in the database theory community in the last three decades.  We show that this community has indeed developed over the years a multi-faceted culture of combining static and dynamic aspects of data management, which has recently culminated in a series of significant lines of research addressing the foundations of data-aware process analysis.  We argue that it is this community that should pursue further the investigation of the fundamental issues underlying the dichotomy between data and processes, which still persists in business process management, and calls for a unifying, well-founded framework.


Diego Calvanese is an associate professor at the KRDB Research Centre for Knowledge and Data, Free University of Bozen-Bolzano, Italy. His research spans from Knowledge Representation in AI to Database theory, where he gave significant contributions on foundational issues in the management of data and knowledge. Specifically, he investigated reasoning and query answering in expressive and lightweight description logics, ontology based data access and integration, conceptual data modeling, view-based query processing over graph databases, service modeling and synthesis, and more recently data-aware process verification. He is actively involved in several national and European research projects in the above areas, and he is the author of more than 200 refereed publications, including ones in the most prestigious journals and conferences in Databases and Artificial Intelligence. He is currently a visiting researcher at the Technical University of Vienna as Pauli Fellow of the "Wolfgang Pauli Institute".


SIGMOD Panel: We are Drowning in a Sea of Least Publishable Units (LPUs)

Michael Stonebraker, Professor, MIT; David DeWitt, Technical Fellow, Microsoft; Jeff Naughton, Professor, Univ. of Wisconsin; Ihab Ilyas, Principal Scientist, QCRI and Associate Professor, Univ. of Waterloo


Our field is drowning in a sea of conference submissions.  We assert that the sheer number of papers has begun to seriously hurt the quality of the work that the field is doing and that the field is going to implode unless we take action to remedy the situation. In order to improve the quality of the papers being published we must reduce the number being submitted. This will require a change in the culture of our field where "more" is being equated to “better” by both hiring and promotion committees. In this panel we will explore some ideas for correcting the situation.


Dr. Stonebraker has been a pioneer of data base research and technology for more than a quarter of a century.  He was the main architect of the INGRES relational DBMS, and the object-relational DBMS, POSTGRES.  These prototypes were developed at the University of California at Berkeley where Stonebraker was a Professor of Computer Science for twenty five years.  More recently at M.I.T. he was a co-architect of the Aurora/Borealis stream processing engine, the C-Store column-oriented DBMS, and the H-Store transaction processing engine.   Currently, he is working on science-oriented DBMSs, OLTP DBMSs, and scalable data curation.  He is the founder of five venture-capital backed startups, which commercialized his prototypes.  Presently he serves as Chief Technology Officer of VoltDB and Paradigm4, Inc.
Professor Stonebraker is the author of scores of research papers on data base technology, operating systems and the architecture of system software services.  He was awarded the ACM System Software Award in 1992, for his work on INGRES.  Additionally, he was awarded the first annual Innovation award by the ACM SIGMOD special interest group in 1994, and was elected to the National Academy of Engineering in 1997.  He was awarded the IEEE John Von Neumann award in 2005, and is presently an Adjunct Professor of Computer Science at M.I.T, where he is co-director of the new Intel Science and Technology Center focused on big data.

David DeWitt was a faculty member in the Computer Sciences Department at the University of Wisconsin-Madison from 1976 until he joined Microsoft as a Technical Fellow in March 2008.   He served as department chair from 1999 to 2004.   Dr. DeWitt is a member of the National Academy of Engineering and a Fellow of the American Academy of Arts and Sciences.   His pioneering contributions to the field of parallel database systems were recognized by ACM with the 2009 Software Systems award.   Currently, he manages the Jim Gray Systems Laboratory in Madison for Microsoft.

Jeff Naughton is John P. Morgridge Professor and Chair of the Computer Sciences Department at the University of Wisconsin-Madison. He received the National Science Foundation Presidential Young Investigator Award, is an ACM Fellow, and was a member of the GAMMA team that received the 2008 ACM Software Systems Award. Professor Naughton has served as an adviser or consultant to companies including Greenplum, Microsoft, NEC, and Teradata.

Ihab Ilyas is a principal scientist at the Qatar Computing Research Institute and an associate professor of computer science at the University of Waterloo. He received his PhD in computer science from Purdue University, West Lafayette and his BSc and MSc in computer science from the University of Alexandria. His main research is in the area of database systems, with special interest in rank-aware query processing, data quality, managing uncertain data, and Information extraction. Ihab is an IBM CAS faculty fellow since January 2006, a recipient of the Ontario Early Researcher Award in 2008, and recently a co-founder of Data Tamer, a new startup focusing on large scale data integration and cleaning.

Invited Tutorial 1

Sketching via Hashing: from Heavy Hitters to Compressed Sensing to Sparse Fourier Transform

Piotr Indyk, MIT


Sketching via hashing is a popular and useful method for processing large data sets. It has found applications for diverse computational problems such as data stream algorithms, compressive sensing, numerical linear algebra and sparse Fourier transform. In this talk I will give an overview of the method and its applications to the aforementioned areas.


Piotr Indyk is a Professor of Electrical Engineering and Computer Science at MIT. He joined MIT in 2000, after earning PhD from Stanford University. Earlier, he received Magister degree from Uniwersytet Warszawski in 1995. Piotr's research interests lie in the design and analysis of efficient algorithms. Specific interests include: high-dimensional computational geometry, sketching and streaming algorithms, sparse recovery and compressive sensing. He has received the Sloan Fellowship (2003), the Packard Fellowship (2003) and the MIT Faculty Research Innovation Fellowship (2012). His work on sparse Fourier sampling has been named to Technology Review "TR10" in 2012; his work on locality-sensitive hashing has received the 2012 Kanellakis Theory and Practice Award. He is an Associate Editor for the IEEE Transactions on Signal Processing and SIAM Journal on Computing.

Invited Tutorial 2

Querying Graph Databases

Pablo Barceló, University of Chile


Graph databases have gained renewed interest in the last years, due to their applications in areas such as the Semantic Web and Social Networks Analysis. We study the problem of querying graph databases, and, in particular, the expressiveness and complexity of evaluation for several general-purpose navigational query languages, such as the regular path queries and its extensions with conjunctions and inverses. We distinguish between two semantics for these languages. The first one, based on simple paths, easily leads to intractability in data complexity, while the second one, based on arbitrary paths, allows tractable evaluation for an expressive family of languages. We also study two recent extensions of these languages that have been motivated by modern applications of graph databases. The first one allows to treat paths as first-class citizens, while the second one permits to express queries that combine the topology of the graph with its underlying data.


Pablo Barceló is an Assistant Professor in the Department of Computer Science at the University of Chile. He received his PhD from the University of Toronto in 2006. His main research interest are in the areas of databases and logic in computer science. He has written over 15 technical papers and served on the program committees of the major database conferences (ACM PODS,ICDT).

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