Berlin Brandenburg Information Systems Colloquium

Prof. Dr. Torsten Grust, Database Systems, Universität Tübingen

Titel:

LINQ and Links Aboard the Ferry

Abstract:

Programs formulated using Microsoft LINQ or Philip Wadler's functional
language Links may have selected program fragments compiled for execution
by an accompanying relational database back-end. We demonstrate a LINQ
provider and a variant of the Edinburgh Links system, both of which
are based on our Ferry compiler. Ferry implements a compositional
translation scheme for a rich set of operations over lists that
faithfully preserve order and nesting: with Ferry, significantly more
LINQ and Links programs may be considered database-executable. Ferry's
code generator emits compact bundles of standard SQL:1999 queries and
avoids the infamous ``n+1 query problem'' that may easily overwhelm
database back-ends.

Bio:

Torsten Grust is a professor of Computer Science at Universität
Tübingen, Germany, where he leads the Database Systems research group
since 2008. Prior to his move to Tübingen, Torsten has been a professor
of Database Systems at TU München and TU Clausthal. Torsten received his
Diploma (M.Sc.) in Computer Science in 1994 and his PhD degree in 1999
from Universität Konstanz. In 2000, Torsten was a visiting scientist
with the IBM Silicon Valley Laboratories, San Jose, CA, USA.

Torsten performs research into the compilation, optimization, and
evaluation of a variety of database languages. In this work, he often
walks the fine line between database query and programming language
technology. His group develops techniques that turn relational database
systems into scalable processors also for non-relational query and
programming languages. Torsten is at his happiest whenever he finds new
evidence that database and programming language research can mutually
benefit each other.

Prof. Gustavo Alonso, ETH Zürich

Titel:

SwissBox: revisiting the data processing software stack

Abstract:

Current advances hardware at all levels (memory, storage, network, multicore) pose a significant challenge to established data management architectures. At the same time, they offer a huge opportunity to redesign the data processing software stack from the ground up. In this talk I will present SwissBox, the database appliance we are building at ETH. SwissBox is based on a number of innovative solutions to real world problems such as predictable query response times, seamless scalability, and reduced maintenance costs. In the talk I will briefly discuss the architecture of SwissBox and focus on concrete layers like Crescando, the main memory storage manager we have developed for it, placing special emphasis on the requirements we are addressing and the trade-offs considered in the design.

Bio:

Gustavo Alonso is a professor at the Department of Computer Science (D-INFK) of the Swiss Federal Institute of Technology in Zurich (ETHZ). He was born in Madrid, Spain. He has an engineering degree in telecommunications -similar to electrical engineering- from the Madrid Technical University (ETSIT, Politecnica de Madrid, 1989). As a Fulbright scholar, he completed an M.S. and Ph.D. in Computer Science at UC Santa Barbara (1992 and 1994). After graduating from Santa Barbara, he was a researcher at the IBM Almaden Research Center, where he worked in the Exotica project. He joined ETH Zurich towards the end of 1995 as a senior researcher in the database group. He became assistant professor at ETH Zurich in 1998 and joined the Institute of Information Systems; he was appointed full professor in 2001 and shortly after he joined the newly established Institute of Pervasive Computing. In 2004-2005 he spent a sabbatical at UC Berkeley as a Stonebraker Fellow. At ETHZ, he is currently part of the Systems Group and the Enterprise Computing Center.

Sihem Amer-Yahia, Senior Research Scientist at Yahoo! Labs, Barcelona

Titel:

Composite Retrieval of Stars and Chains

Abstract:

Information retrieval (IR) is the science of searching for documents. Composite retrieval is the study of methods for creating, retrieving and ranking composite responses such as sequences, or more generally, items connected with some relationship. Different applications induce star-shaped or chain-shaped items. Such items can be found in online shopping and trip itinerary planning. In this talk, I will describe concrete applications motivating composite retrieval and discuss how stars and chains affect relevance and efficiency in online recommendations.

Bio:

Sihem has been a Senior Research Scientist at Yahoo! Labs since May 2006 after 7 years at AT&T Labs. She received her Ph.D. in CS from U. Paris-Orsay and INRIA, France. Sihem focuses on data management, query processing and relevance models to leverage social behavior for online content serving. Her professional activities include chairing the SIGMOD 2009 Tutorials, the VLDB 2009 Industrial track, the Social Networks and Personal Information track at ICDE 2010, the Structured and Unstructured Data Track at WWW10, the SIGMOD 2010 Undergraduate Posters, the EDBT 2011 demo track and the SIGMOD 2011 Information Retrieval and Extraction track. She is a member of the Board of Trustees of the VLDB Endowment and is of the ACM SIGMOD Executive Committee. Sihem serves as the VLDB Journal Area Chair in the area of structured and unstructured data management and as the Information Systems Journal Area Chair in the area of social search and recommendations. She is currently visiting the Yahoo! Barcelona Lab.
Everybody is cordially welcome!
Please, forward this invitation to interested colleagues.

Sihem Amer-Yahia, Senior Research Scientist at Yahoo! Labs, Barcelona

Titel:

Composite Retrieval of Stars and Chains

Abstract:

Information retrieval (IR) is the science of searching for documents. Composite retrieval is the study of methods for creating, retrieving and ranking composite responses such as sequences, or more generally, items connected with some relationship. Different applications induce star-shaped or chain-shaped items. Such items can be found in online shopping and trip itinerary planning. In this talk, I will describe concrete applications motivating composite retrieval and discuss how stars and chains affect relevance and efficiency in online recommendations.

Bio:

Sihem has been a Senior Research Scientist at Yahoo! Labs since May 2006 after 7 years at AT&T Labs. She received her Ph.D. in CS from U. Paris-Orsay and INRIA, France. Sihem focuses on data management, query processing and relevance models to leverage social behavior for online content serving. Her professional activities include chairing the SIGMOD 2009 Tutorials, the VLDB 2009 Industrial track, the Social Networks and Personal Information track at ICDE 2010, the Structured and Unstructured Data Track at WWW10, the SIGMOD 2010 Undergraduate Posters, the EDBT 2011 demo track and the SIGMOD 2011 Information Retrieval and Extraction track. She is a member of the Board of Trustees of the VLDB Endowment and is of the ACM SIGMOD Executive Committee. Sihem serves as the VLDB Journal Area Chair in the area of structured and unstructured data management and as the Information Systems Journal Area Chair in the area of social search and recommendations. She is currently visiting the Yahoo! Barcelona Lab.


Everybody is cordially welcome!
Please, forward this invitation to interested colleagues.

Gregor Hackenbroich, SAP Dresden

Titel:

B2B-integration with Warp 10

Abstract:

Warp 10 is a novel approach to B2B-integration combining concepts from semantic data modeling, Natural Language Processing and Schema Matching to define a consolidated data model termed canonical model. The canonical model is built up semi-automatically and grows in size and complexity upon matching with schemas provided by a business community. The business context of a matching task allows for an efficient filtering of the relevant information contained in the canonical model.The talk outlines the main concepts of Warp 10 focusing on the challenges for efficient schema matching. A research prototype will be presented that allows to evaluate the growth and quality of the canonical model respectively the B2B-mappings derived from it. It will be shown how collaboration tools such as SAP Streamwork help to quickly consolidate ambiguous or incorrect mappings, thus providing immediate business value.

Bio:

Dr. Gregor Hackenbroich is Deputy Director of the SAP Research Center Dresden leading its activities in Information Management. His main research interest is in data integration, management of unstructured data, and Business Analytics. Within SAP Research, Dr. Hackenbroich shaped the worldwide research program Data Management & Analytics. Prior to joining SAP, he has been faculty member of Essen University, and worked as a researcher at Yale University and the Max-Planck Institute for Nuclear Physics Heidelberg. He received his habilitation in theoretical physics from Essen University and his doctoral degree from the University of Munich. Dr. Hackenbroich has published numerous research papers on computer science and theoretical physics, and regularly works as a reviewer for scientific journals and international research organizations.

Anastasia Ailamaki, EPFL

Titel:

Scaling Transactions on Multicore Hardware


Abstract:

Database systems have long optimized for parallel execution; the research community has pursued parallel database machines since the early `80s, and several the key ideas from that era underlie the design and success of commercial database engines today. Computer architectures have shifted drastically during the intervening decades, however, and today the constraints of semiconductor technology combine with Moore’s Law to double the number of processors per chip every 18 months. Converting this available raw parallelism into scalable performance using conventional servers is increasingly difficult when running transaction processing workloads.
This talk analyzes transaction performance scaling results on future chip multiprocessors and demonstrates that current parallelism methods are insufficient and of bounded utility as the number of processors per chip exponentially increase. To achieve scalability for database transactions on chip multiprocessors, concurrency needs to be converted into parallelism – a challenging task, despite the high levels of concurrency available in OLTP systems. Then, parallelism needs to be extracted from seemingly serial operations, such as locking objects and logging for recoverability; existing research in distributed systems proves to be very useful in this context. We describe a set of techniques to alleviate major scalability bottlenecks in transaction management, and demonstrate the efficiency of our solutions using the Shore-MT multithreaded storage manager.

Bio: Anastasia (Natassa) Ailamaki is a Professor of Computer Sciences at the Ecole Polytechnique Federale de Lausanne (EPFL) in Switzerland. She earned her Ph.D. in Computer Science from the University of Wisconsin-Madison in 2000. Her research interests are in database systems and applications; in particular (a) in strengthening the interaction between the database software and the underlying hardware and I/O devices, including flash technology, and (b) in automating database design and computational database support for scientific applications. She has received a Finmeccanica endowed chair from the Computer Science Department at Carnegie Mellon (2007), a European Young Investigator Award from the European Science Foundation (2007), an Alfred P. Sloan Research Fellowship (2005), six best-paper awards at top conferences (2001-2006), and an NSF CAREER award (2002).

Guy Lohman / IBM Almaden

Manager, Disruptive Information Management Architectures

Title:

"IBM Smart Analytics Optimizer: Not Your Father's Database!"

Abstract:
Based upon Almaden's "Blink" research prototype, we are now developing (together with developers in Boeblingen and Silicon Valley Lab) an accelerator appliance product for DB2, called "IBM Smart Analytics Optimizer" (ISAO), which will GA on DB2 for z/OS this year, and DB2 for LUW and Informix IDS in the near future. ISAO's ambitious goals are to answer all Business Intelligence queries in mere seconds, regardless of the database size, with an extremely low total cost of ownership (TCO). It takes a very innovative and counter-intuitive approach to processing BI queries, one that exploits several disruptive hardware and software technology trends. Specifically, it is a new, workload-optimized DBMS aimed primarily at BI query processing, and exploits scale-out of commodity multi-core processors and cheap DRAM to retain a (copy of a) data mart completely in main memory. Additionally, it exploits proprietary compression technology and cache-conscious algorithms that reduce memory bandwidth consumption and allow most SQL query processing to be performed on the compressed data. Ignoring the general wisdom of the last three decades that the only way to scalably search large databases is with indexes, ISAO always performs simple, "brute-force" scans of the entire data mart in parallel on all nodes, without using any indexes or materialized views, and without any query optimizer to choose among them.

Bio:

Dr. Guy M. Lohman is Manager of Disruptive Information Management Architectures in the Advanced Information Management Department at IBM Research Division's Almaden Research Center in San Jose, California, where he has worked for over 28 years. He was the architect of the Query Optimizer of DB2 on the Linux, UNIX, and Windows platforms, and was responsible for its development in Versions 2 and 5, as well as the invention and prototyping of Visual Explain and efficient sampling in DB2. During that period, Dr. Lohman also managed the overall effort to incorporate into that DB2 product the Starburst compiler technology that was prototyped at the Almaden Research Center. More recently, he was a co-inventor and designer of the DB2 Index Advisor (now part of the Design Advisor), and co-founder of the DB2 Autonomic Computing project, part of IBM's company-wide Autonomic Computing initiative. From 2004-2006, he was responsible for the design of the extensions to DB2 to optimize XQuery queries in DB2 9. Dr. Lohman was elected to the IBM Academy of Technology in 2002. His current research interests involve disruptive machine architectures for Business Intelligence, query optimization, self-managing database systems, information management appliances, database compression, and autonomic problem determination.

Lori A. Clarke & Leon J. Osterweil / UMASS

Titel:

Using Process Definition and Analysis Techniques to Reduce Healthcare Errors and Inefficiencies

Abstract:

As has been widely reported in the news lately, heathcare errors are a major cause of death and suffering, and healthcare inefficiencies have high costs in both time and pain. In the University of Massachusetts Medical Safety Project, we are investigating if process definition and analysis technologies can be used to help reduce heathcare errors and increase heathcare efficiencies. Specifically, we are modeling healthcare processes with a process definition language and then analyzing these processes using finite-state verification, fault-tree analysis, discrete event simulation, and other analysis techniques. Working with the UMASS School of Nursing and the Baystate Medical Center, we are undertaking in-depth case studies on error-prone and life-critical healthcare processes. In many ways, these processes are similar to complex, distributed systems with many interacting, concurrent threads and numerous exceptional conditions that must be carefully handled.

This talk describes the technologies we are using, discusses case studies, and presents our observations and findings to date. Although presented in terms of the healthcare domain, the described approach could be applied to human-intensive processes in other domains to provide a technology-driven approach to process improvement





Bio:

Lori A. Clarke is a professor in the Department of Computer Science at the University of Massachusetts, Amherst, and co-director of the Laboratory for Advanced Software Engineering Research (LASER). She is a Fellow of the ACM and a board member of the Computing Research Association's Committee on the Status of Women in Computing Research (CRA-W). She is a former vice chair of the Computing Research Association (CRA), co-chair of CRA-W, IEEE Publication Board member, associate editor of ACM TOPLAS and IEEE TSE, member of the CCR NSF advisory board, ACM SIGSOFT secretary/treasurer, vice-chair and chair, IEEE Distinguished Visitor, and ACM National Lecturer. She received a 2009 College of Natural Sciences and Mathematics Outstanding Faculty Service Award, a 2004 Distinguished Engineering Alumni Award from the University of Colorado, Boulder, the 2002 SIGSOFT Distinguished Service Award, a 1993 University Faculty Fellowship, and a 1991 University of Massachusetts Distinguished Faculty Chancellor's Medal. She has written numerous papers, served on many program committees, and was program co-chair of the 14th and general chair of the 25^th International Conference on Software Engineering. She has been a Principal Investigator on a number of NSF and DARPA projects.

Dr. Clarke's research is in the area of software engineering, primarily focusing on the finite-state verification of concurrent systems and requirements engineering. Recently she has been investigating applying software engineering technologies to detect errors and vulnerabilities in complex processes in domains such as medicine, scientific workflow, and digital government. She is also involved in several efforts to increase participation of underrepresented groups in computing research.

Leon J. Osterweil is a professor in the Department of Computer Science, co-director of the Laboratory for Advanced Software Engineering Research (LASER), and founding co-director of the Electronic Enterprise Institute, all at the University of Massachusetts Amherst, where he also served as Interim Dean of the College of Natural Sciences and Mathematics from 2001-02005.  Previously he had been a Professor in, and Chair of, Computer Science Departments at both the University of California, Irvine, and the University of Colorado, Boulder.  He was the founding director of the Irvine Research Unit in Software (IRUS) and the Southern California SPIN.  Professor Osterweil was awarded the ACM SIGSOFT Outstanding Research Award for Lifetime Excellence in Research in 2003.  His ICSE 9 paper has been awarded a prize as the most influential paper of ICSE 9, awarded as a 10-year retrospective.  Prof. Osterweil is a Fellow of the Association for Computing Machinery.  He is a member of the editorial boards of IEEE Transactions on Software Engineering, Automated Software Engineering, the International Journal of Software and Informatics, and Software Process Improvement and Practice.  Previously he had been on the editorial board of the ACM Transactions on Software Engineering Methods and IEEE Software.  Prof. Osterweil has been the Program Committee Chair for the 16^th International Conference on Software Engineering, and the General Chair of the 28^th International Conference on Software Engineering, and the Sixth ACM Sigsoft Conference on the Foundations of Software Engineering.  He has consulted for such organizations as IBM, Bell Laboratories, SAIC, MCC, and TRW, and SEI's Process Program Advisory Board.

Dr. Osterweil's research focuses on languages for the clear and precise definition of processes.  His 1987 paper, "Software Processes are Software Too", is one of the 10 most frequently cited papers from the International Conference on Software Engineering (ICSE) series, and has led to considerable interest in precise process definition.  Currently his work has concentrated on the development of the Little-JIL process definition language, and it application to defining processes in such domains as healthcare, software development, elections, labor-management disputes, and scientific data processing.

Roger Barga, Microsoft Research

"Cloud Computing Architecture and Application Programming"

Abstract:

Cloud  computing uses data centers to provide on-demand access to services such as data storage and hosted applications that provide scalable web services and large scale scientific data analysis. While the architecture of a data center is similar to a conventional supercomputer, they are designed with very different goals.  This talk will cover the basic cloud computing system architectures and the application programming models, beginning with general concepts of data center architecture including the use of virtualization and the role of low power. We next examine cloud computing and storage models with a detailed look at the Microsoft Azure cloud computing platform. The talk concludes with an overview of our ongoing efforts to leverage the power of the Microsoft Azure cloud computing platform to address some of the most challenging problems in data intensive research.


Bio:

Roger Barga is Senior Architect in the Cloud Computing Futures team in Microsoft Research, where he leads a team responsible for developing tools and services on the Microsoft cloud computing platform to revolutionize and accelerate research. Roger joined Microsoft in 1997 as a Researcher in the Database Group of Microsoft Research, where he directed both systems research and product development efforts in database, workflow and stream processing systems.  Roger served as Principal Architect of the External Research Division of External Research (MSR) from 2007 to 2009, prior to joining the cloud computing futures group. Roger has published over 50 peer reviewed papers, filed over 30 patent applications, and served more than 70 times on program committees for more than 30 different international conferences and workshops.

Goetz Graefe, HP

Titel:
Self-selecting, self-tuning, incrementally optimized indexes

Abstract:
Goetz Graefe, joint work with Harumi Kuno (both Hewlett-Packard
Laboratories)
In a relational data warehouse with many tables, the number of possible
and promising indexes exceeds human comprehension and requires automatic
index tuning. While monitoring and reactive index tuning have been
proposed, adaptive indexing focuses on adapting the physical database
layout for and by actual queries.
"Database cracking" is one such technique. Only if and when a column is
used in query predicates, an index for the column is created; and only
if and when a key range is queried, the index is optimized for this key
range. The effect is akin to a sort that is adaptive and incremental.
This sort is, however, very inefficient, particularly when applied on
block-access devices. In contrast, traditional index creation sorts data
with an efficient merge sort optimized for block-access devices, but it
is neither adaptive nor incremental.
We propose adaptive merging, an adaptive, incremental, and efficient
technique for index creation. Index optimization focuses on key ranges
used in actual queries. The resulting index adapts more quickly to new
data and to new query patterns than database cracking. Sort efficiency
is comparable to that of traditional B-tree creation. Nonetheless, the
new technique promises better query performance than database cracking,
both in memory and on block-access storage.

Bio:

Goetz Graefe is an HP Fellow working in the Intelligent Information
Management Lab within Hewlett-Packard Laboratories. Prior to joining HP
in 2006, Goetz spent 12 years as software architect in product
development at Microsoft, mostly in database management. Both query
optimization and query execution of Microsoft's re-implementation of SQL
Server are based on his designs. Goetz's research credentials include
numerous publications as well as surveys published by ACM Computing
Surveys. His original publications cover query optimization, query
execution, and indexing. His work has been honored by the ACM SIGMOD
2000 "test of time" award for work on parallel query execution, by the
IEEE ICDE 2005 "influential paper" award for work on extensible query
execution, and by the 2009 ACM "software systems" award for
participation in the Gamma database machine research project.

Stefano Ceri, Dipartimento di Elettronica e Informazione (DEI), Politecnico di Milano

Search Computing Challenges and Directions

Abstract

Search Computing (SeCo, www.search-computing.it) is a project funded by the European Research Council (ERC). It focuses on building the answers to complex search queries like "Where can I attend an interesting conference in my field close to a sunny beach?" by interacting with a constellation of cooperating search services, using ranking and joining of results as the dominant factors for service composition. SeCo started on November 2008 and will last 5 years. The project is now addressing several research problems, entitled: Search as a Process, Business Strategies, Semantic Resource Framework, Wrapping Technology and Ontological Annotation, Design Tools and Mashup Languages, Ranking Aggregation Theory, Query Optimization and Execution Engine, Biomedical Applications, Visual Interfaces and User Interaction. The seminar will give a general introduction to the Search Computing approach and then focus on some of the above research directions.

Bio

Stefano Ceri (http://home.dei.polimi.it/ceri/) is Professor of "Database Systems" at DEI; his research interests are focused on extending database technology to incorporate data distribution, deductive and active rules, object orientation, XML query languages; recent work is focused on design methods for data-intensive WEB sites, stream reasoning, and search computing.

Steve Loughran, Hewlett Packard, Automated Infrastructure Labs, Bristol, U.K.

"New Roles in the Cloud"

Abstract:

We are trying align Cloud Infrastructures management tools and
programming interfaces with the organizational structure of large
enterprises. We believe that dividing up tasks into architecture,
operations and development roles is still important, because designing
a cloud-hosted application is different from getting it to work,
which is different from keeping it running. We have built a prototype
front-end service to Cloud APIs, "CloudFarmer" service to offer
different features to the different roles.

We also pass down this concept of "role" into the API itself.
Rather than make people ask for Virtual Machines with specific CPU
and memory options, mounting named disk images, the API lets its callers
ask for machines by "role", roles that have been predefined. This keeps
machine configuration under control, and makes it easier to switch
between cloud service providers.

Prof. Dr. Rudolf Kruse, Univ. Magdeburg

"Temporal Pattern Mining"

Abstract:

Data mining can be considered a vital component in strategic planning for companies that are aware of global competition, ever-shorter production cycles and increasing customer requirements. It is of paramount importance to identify meaningful patterns quickly within the collected data in order to respond to impending supply shortages or evolving problems with delivered products. However, patterns that correspond to such lingering problems rarely occur out of a sudden. Therefore we suggest a temporal view on the data as well as the resulting patterns.

Further, we intend to enable users that not necessarily have a statistical background to assess and understand the identified patterns. This will be accomplished by devising appropriate visualization methods for patterns as well as their temporal change.

Specifically, real-world examples with different types of patterns from four projects in the areas automotive manufacturing, finance, health and online communities are studied. Using these examples, new visualization techniques for the identification of interesting association rules change over time and the identification of changes in cooccurrence graphs are presented.


Bio:

Rudolf Kruse obtained his diploma (Mathematics) degree in 1979 from the University of Braunschweig, Germany, and a PhD in Mathematics in 1980 as well as the venia legendi in Mathematics in 1984 from the same university. Following a short stay at the Fraunhofer Gesellschaft, in 1986 he joined the University of Braunschweig as a professor of computer science. Since 1996 he is a full professor at the Department of Computer Science of the University of Magdeburg where he is leading the computational intelligence research group.

He has carried out research and projects in statistics, artificial intelligence, expert systems, fuzzy control, fuzzy data analysis, computational intelligence, and information mining. His research group is very successful in various industrial applications.

Rudolf Kruse has coauthored more than 30 books as well as more than 330 refereed technical papers in various scientific areas. He is associate editor of several scientific journals. He is a fellow of the International Fuzzy Systems Association (IFSA), fellow of the European Coordinating Committee for Artificial Intelligence (ECCAI) and fellow of the Institute of Electrical and Electronics Engineers (IEEE).

Dr. Stefan Manegold, CWI, Amsterdam, NL

"MonetDB: Open-source Database Technology Beyond Textbooks"

Abstract:

Column-store database management systems have recently experienced a
considerable popularity-boost. The underlying ideas, however, date back to
(at least) the mid 1980's and the technology has been pioneered since the
early 1990's in the MonetDB, a column-store research prototype that has been
developed into a complete SQL- and XML/XQuery-compliant column-store DBMS
freely available in open source. Next to its column-store back-bone, MonetDB
focuses on high-performance hardware-conscious algorithms and novel
workload-adaptive query processing techniques such as "cracking",
"recycling" and run-time query optimization.
In this talk, we will provide detailed insight into MonetDB's column-store
architecture and query-processing technology as available in open-source,
and discus ongoing research projects towards self-managing datamanagment
technology.

Bio:

Stefan Manegold is a tenured researcher in the database architecture
research group at CWI in Amsterdam, The Netherlands. He received his PhD
from the University of Amsterdam, The Netherlands, in 2002 and his Master
(Diplom) in computer science from the Technical University of Clausthal,
Germany, in 1994.

Manegold's research work comprises database architectures, query processing
algorithms and data management on modern hardware, as well as leveraging
column-store database technology for efficient and scalable XML/XQuery
processing, with a particular focus on optimization, performance,
benchmarking and testing. Manegold co-authored of more than 40 scientific
publications, and recently received the VLDB 2009 10-year Best Paper Award
together with his co-authors Peter Boncz & Martin Kersten.

Stefan Manegold is a core member of the developers team of the open-source
column-oriented database system MonetDB, co-founder of the DaMoN workshop
series (co-located with SIGMOD since 2005), and co-chair of the
Repeatability and Workability Evaluation for SIGMOD 2009 & 2010.

URL: http://homepages.cwi.nl/~manegold