François Picalausa

What are real SPARQL queries like

We present statistics on real world SPARQL queries that may be of interest for building SPARQL query processing engines and benchmarks. In particular, we analyze the syntactical structure of queries in a log of about 3 million queries, harvested from the DBPedia SPARQL endpoint. Although a sizable portion of the log is shown to consist of so-called conjunctive SPARQL queries, non-conjunctive queries that use SPARQLs union or optional operators are more than substantial. It is known, however, that query evaluation quickly becomes hard for queries including the non-conjunctive operators union or optional. We therefore drill deeper into the syntactical structure of the queries that are not conjunctive and show that in 50% of the cases, these queries satisfy certain structural restrictions that imply tractable evaluation in theory. We hope that the identification of these restrictions can aid in the future development of practical heuristics for processing non-conjunctive SPARQL queries.

Storing and Indexing Massive RDF Datasets

The resource description framework (RDF for short) provides a flexible method for modeling information on the Web [34, 40]. All data items in RDF are uniformly represented as triples of the form (subject, predicate, object), sometimes also referred to as (subject, property, value)triples.

A data model for algorithmic multiple criteria decision analysis

Various software tools implementing multiple criteria decision analysis (MCDA) methods have appeared over the last decades. Although MCDA methods share common features, most of the implementing software have been developed independently from scratch. Majority of the tools have a proprietary storage format and exchanging data among software is cumbersome. Common data exchange standard would be useful for an analyst wanting to apply different methods on the same problem. The Decision Deck project has proposed to build components implementing MCDA methods in a reusable and interchangeable manner. A key element in this scheme is the XMCDA standard, a proposal that aims to standardize an XML encoding of common structures appearing in MCDA models, such as criteria and performance evaluations. Although XMCDA allows to present most data structures for MCDA models, it almost completely lacks data integrity checks. In this paper we present a new comprehensive data model for MCDA problems, implemented as an XML schema. The data model includes types that are sufficient to represent multi-attribute value/utility models, ELECTRE III/TRI models, and their stochastic extensions, and AHP. We also discuss use of the data model in algorithmic MCDA.

XEvolve: an XML schema evolution framework

This paper presents XEvolve, a framework that unifies streaming validation of XML documents, and efficient testing of equivalence and inclusion of specifications for various XML schema languages. For these purposes, this framework relies on Visibly Pushdown Automata (VPA) as a unifying model for the various schema languages. Schemas are first translated into VPA; standard algorithms for VPA can be then used to validate documents as well as to test equivalence or inclusion of schemas. In general, inclusion and equivalence are tested in exponential-time. However, when the given specifications are provided as DTD or XSD, these tests have a polynomial-time complexity with respect to the automaton size. Moreover, in this case the memory foot-print of the validation does not depend on the size of the input document but only on its depth.