Alexandra and Jesús will do a rehearsal of the talks they will give at EDBT 2013. It will take place on Wednesday, March 13, at 11.00, room 445.
Please find the details of the talks below.
When: Wednesday, March 13, at 11.00
Where: PCRI building, room 445
Authors: François Goasdoué, Ioana Manolescu and Alexandra Roatiş
Title: Efficient Query Answering against Dynamic RDF Databases
A promising method for efficiently querying RDF data consists of translating SPARQL queries into efficient RDBMS-style operations. However, answering SPARQL queries requires handling RDF reasoning, which must be implemented outside the relational engines that do not support it. We introduce the database (DB) fragment of RDF, going beyond the expressive power of previously studied RDF fragments. We devise novel sound and complete techniques for answering Basic Graph Pattern (BGP) queries within the DB fragment of RDF, exploring the two established approaches for handling RDF semantics, namely reformulation and saturation. In particular, we focus on handling database updates within each approach and propose a method for incrementally maintaining the saturation; updates raise specific difficulties due to the rich RDF semantics. Our techniques are designed to be deployed on top of any RDBMS(-style) engine, and we experimentally study their performance trade-offs.
Authors: Jesús Camacho Rodríguez, Dario Colazzo and Ioana Manolescu
Title: Web Data Indexing in the Cloud: Efficiency and Cost Reductions
An increasing part of the world’s data is either shared through the Web or directly produced through and for Web platforms, in particular using structured formats like XML or JSON. Cloud platforms are interesting candidates to handle large data repositories, due to their elastic scaling properties. Popular commercial clouds provide a variety of sub-systems and primitives for storing data in specific formats (files, key-value pairs etc.) as well as dedicated sub-systems for running and coordinating execution within the cloud.
We propose an architecture for warehousing large-scale Web data, in particular XML, in a commercial cloud platform, specifically, Amazon Web Services. Since cloud users support monetary costs directly connected to their consumption of cloud resources, we focus on indexing content in the cloud. We study the applicability of several indexing strategies, and show that they lead not only to reducing query evaluation time, but also, importantly, to reducing the monetary costs associated with the exploitation of the cloud-based warehouse. Our architecture can be easily adapted to similar cloud-based complex data warehousing settings, carrying over the benefits of access path selection in the cloud.