Invited Speakers

  • Phokion Kolaitis (Home page). Univ. California, Santa Cruz.
  • Magdalena Ortiz (Home page). Vienna University of Technology.
  • Genoveva Vargas Solar (Home page). UDLAP.
  • Surajit Chaudhuri (Home page). Microsoft Research, USA.

Phokion G. Kolaitis

Title: The Query Containment Problem: Set Semantics vs. Bag Semantics (slides)


Query containment is a fundamental algorithmic task in database query processing and optimization.

Under set semantics, the query-containment problem for conjunctive queries has long been known to be NP-complete. SQL queries, however, are typically evaluated under bag semantics and return multisets as answers, since duplicates are not eliminated unless explicitly specified. The exact complexity of the query-containment problem for conjunctive queries under bag semantics has been an outstanding and rather poorly understood open problem for twenty years. In fact, to this date, it is not even known whether conjunctive-query containment under bag semantics is decidable.

The goal of this talk is to draw attention to this fascinating problem by presenting a comprehensive overview of old and not-so-old results about the complexity of the query-containment problem for conjunctive queries and their variants, under both set semantics and bag semantics.

Magdalena Ortiz

Title: Ontology Based Query Answering: The Story So Far (slides)


Databases where relations have arity at most two, often called graph databases, play a prominent role in many fields. Ontology languages based on Description Logics (DLs) have been advocated to enrich such repositories (known as ABoxes in DL jargon) with ontological information. Then, in Ontology Based Query Answering (OBQA), one is interested in answering user queries over the data while taking into account the ontological constraints. However, the ontological layer has a significant effect on the query answering problem, and OBQA algorithms are usually more involved than their plain DB counterparts.

The development of OBQA algorithms and their implementation has been the goal of significant research efforts in the DL community in the last decade. In this talk, we will review some of the achieved results. We will discuss the main challenges to be overcome when the ontological knowledge is expressed in different DLs, and when different query languages are considered. We will give an overview of some of the algorithms developed so far, and the computational complexity of the problem for the different combinations of DLs and query languages.

Genoveva Vargas-Solar

Title: Addressing Data Management on the Cloud : Tackling the Big Data Challenges


The increasing adoption of the cloud computing paradigm has motivated a redefinition of traditional software development methods. In particular, data storage management has received a great deal of attention, due to a growing interest in the challenges and opportunities associated to the NoSQL movement. However, appropriate selection, administration and use of cloud storage implementations remain a highly technical endeavor, due to large differences in the way data is represented, stored and accessed by these systems. This presentation proposes solutions for promoting polyglot persistence for building cloud aware database applications by making dependencies between high-level data models and cloud storage implementations transparent. In this way, developers depend only on high-level data models, and then rely on transformation procedures to deal with particular cloud storage details, such as different APIs and deployment providers, and are able to target multiple cloud storage environments, without modifying their core data models.

Surajit Chaudhuri (Microsoft Research)

Title: Big Data and Enterprise Analytics


In this talk, I will describe the key secular trends that characterize the field of Big Data with respect to enterprise analytics. I will describe some of the open challenges for enterprise analytics in the context of Big Data. Although some of these problems are not new, their importance is amplified by Big Data. As an example, we will discuss the task of leveraging unstructured data for enterprise analytics.

Bio: Surajit Chaudhuri is a Distinguished Scientist at Microsoft Research. His current areas of interest are enterprise data analytics, self-manageability and cloud database services. Working with his colleagues in Microsoft Research, he helped incorporate the Index Tuning Wizard (and subsequently Database Engine Tuning Advisor) and data cleaning technology into Microsoft SQL Server. Surajit is an ACM Fellow, a recipient of the ACM SIGMOD Edgar F. Codd Innovations Award, ACM SIGMOD Contributions Award, a VLDB 10 year Best Paper Award, and an IEEE Data Engineering Influential Paper Award. Surajit received his Ph.D. from Stanford University in 1992. Surajit is the managing director of Microsoft's XCG Lab which is a project-driven innovation lab focusing on big data, cloud systems, security, and hardware-software co-design. He also serves on the Senior Leadership Team of the President of Microsoft's Server and Tools division.