Context-Free Path Queries on RDF Graphs

Navigational graph queries are an important class of queries that canextract implicit binary relations over the nodes of input graphs. Most of the navigational query languages used in the RDF community, e.g. property paths in W3C SPARQL 1.1 and nested regular expressions in nSPARQL, are based on the regular expressions. It is known that regular expressions have limited expressivity; for instance, some natural queries, like same generation-queries, are not expressible with regular expressions. To overcome this limitation, in this paper, we present cfSPARQL, an extension of SPARQL query language equipped with context-free grammars. The cfSPARQL language is strictly more expressive than property paths and nested expressions. The additional expressivity can be used for modelling graph similarities, graph summarization and ontology alignment. Despite the increasing expressivity, we show that cfSPARQL still enjoys a low computational complexity and can be evaluated efficiently.Comment: 25 page

Towards a navigational logic for graphical structures

One of the main advantages of the Logic of Nested Conditions, defined by Habel and Pennemann, for reasoning about graphs, is its generality: this logic can be used in the framework of many classes of graphs and graphical structures. It is enough that the category of these structures satisfies certain basic conditions. In a previous paper [14], we extended this logic to be able to deal with graph properties including paths, but this extension was only defined for the category of untyped directed graphs. In addition it seemed difficult to talk about paths abstractly, that is, independently of the given category of graphical structures. In this paper we approach this problem. In particular, given an arbitrary category of graphical structures, we assume that for every object of this category there is an associated edge relation that can be used to define a path relation. Moreover, we consider that edges have some kind of labels and paths can be specified by associating them to a set of label sequences. Then, after the presentation of that general framework, we show how it can be applied to several classes of graphs. Moreover, we present a set of sound inference rules for reasoning in the logic.Peer ReviewedPostprint (author's final draft

Reasoning & Querying – State of the Art

Various query languages for Web and Semantic Web data, both for practical use and as an area of research in the scientific community, have emerged in recent years. At the same time, the broad adoption of the internet where keyword search is used in many applications, e.g. search engines, has familiarized casual users with using keyword queries to retrieve information on the internet. Unlike this easy-to-use querying, traditional query languages require knowledge of the language itself as well as of the data to be queried. Keyword-based query languages for XML and RDF bridge the gap between the two, aiming at enabling simple querying of semi-structured data, which is relevant e.g. in the context of the emerging Semantic Web. This article presents an overview of the field of keyword querying for XML and RDF

XQuery Streaming by Forest Transducers

Streaming of XML transformations is a challenging task and only very few systems support streaming. Research approaches generally define custom fragments of XQuery and XPath that are amenable to streaming, and then design custom algorithms for each fragment. These languages have several shortcomings. Here we take a more principles approach to the problem of streaming XQuery-based transformations. We start with an elegant transducer model for which many static analysis problems are well-understood: the Macro Forest Transducer (MFT). We show that a large fragment of XQuery can be translated into MFTs --- indeed, a fragment of XQuery, that can express important features that are missing from other XQuery stream engines, such as GCX: our fragment of XQuery supports XPath predicates and let-statements. We then rely on a streaming execution engine for MFTs, one which uses a well-founded set of optimizations from functional programming, such as strictness analysis and deforestation. Our prototype achieves time and memory efficiency comparable to the fastest known engine for XQuery streaming, GCX. This is surprising because our engine relies on the OCaml built in garbage collector and does not use any specialized buffer management, while GCX's efficiency is due to clever and explicit buffer management.Comment: Full version of the paper in the Proceedings of the 30th IEEE International Conference on Data Engineering (ICDE 2014

Relative Expressive Power of Navigational Querying on Graphs

Motivated by both established and new applications, we study navigational query languages for graphs (binary relations). The simplest language has only the two operators union and composition, together with the identity relation. We make more powerful languages by adding any of the following operators: intersection; set difference; projection; coprojection; converse; and the diversity relation. All these operators map binary relations to binary relations. We compare the expressive power of all resulting languages. We do this not only for general path queries (queries where the result may be any binary relation) but also for boolean or yes/no queries (expressed by the nonemptiness of an expression). For both cases, we present the complete Hasse diagram of relative expressiveness. In particular the Hasse diagram for boolean queries contains some nontrivial separations and a few surprising collapses.Comment: An extended abstract announcing the results of this paper was presented at the 14th International Conference on Database Theory, Uppsala, Sweden, March 201

Fifty years of Hoare's Logic

We present a history of Hoare's logic.Comment: 79 pages. To appear in Formal Aspects of Computin