PODS Invited Talks
Keynote
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)
Abstract
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.
Bio
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".
Panel
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
Abstract
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.
Bios
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
Abstract
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.
Bio
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
Abstract
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.
Bio
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).
