Claudio Gutierrez

Survey of graph database models

Graph database models can be defined as those in which data structures for the schema and instances are modeled as graphs or generalizations of them, and data manipulation is expressed by graph-oriented operations and type constructors. These models took off in the eighties and early nineties alongside object-oriented models. Their influence gradually died out with the emergence of other database models, in particular geographical, spatial, semistructured, and XML. Recently, the need to manage information with graph-like nature has reestablished the relevance of this area. The main objective of this survey is to present the work that has been conducted in the area of graph database modeling, concentrating on data structures, query languages, and integrity constraints.

Introducing Time into RDF

The resource description framework (RDF) is a metadata model and language recommended by the W3C. This paper presents a framework to incorporate temporal reasoning into RDF, yielding temporal RDF graphs. We present a semantics for these kinds of graphs which includes the notion of temporal entailment and a syntax to incorporate this framework into standard RDF graphs, using the RDF vocabulary plus temporal labels. We give a characterization of temporal entailment in terms of RDF entailment and show that the former does not yield extra asymptotic complexity with respect to nontemporal RDF graphs. We also discuss temporal RDF graphs with anonymous timestamps, providing a theoretical framework for the study of temporal anonymity. Finally, we sketch a temporal query language for RDF, along with complexity results for query evaluation that show that the time dimension preserves the tractability of answers

Foundations of semantic web databases

The Semantic Web is based on the idea of adding more machine-readable semantics to web information via annotations written in a language called the Resource Description Framework (RDF). RDF resembles a subset of binary first-order logic including the ability to refer to anonymous objects. Its extended version, RDFS, supports reification, typing and inheritance. These features introduce new challenges into the formal study of sets of RDF/RDFS statements and languages for querying them. Although several such query languages have been proposed, there has been little work on foundational aspects. We investigate these, including computational aspects of testing entailment and redundancy. We propose a query language with well-defined semantics and study the complexity of query processing, query containment, and simplification of answers.

The Expressive Power of SPARQL

This paper studies the expressive power of SPARQL. The main result is that SPARQL and non-recursive safe Datalog with negation have equivalent expressive power, and hence, by classical results, SPARQL is equivalent from an expressiveness point of view to Relational Algebra. We present explicit generic rules of the transformations in both directions. Among other findings of the paper are the proof that negation can be simulated in SPARQL, that non-safe filters are superfluous, and that current SPARQL W3C semantics can be simplified to a standard compositional one.

nSPARQL: A navigational language for RDF

Navigational features have been largely recognized as fundamental for graph database query languages. This fact has motivated several authors to propose RDF query languages with navigational capabilities. In this paper, we propose the query language nSPARQL that uses nested regular expressions to navigate RDF data. We study some of the fundamental properties of nSPARQL and nested regular expressions concerning expressiveness and complexity of evaluation. Regarding expressiveness, we show that nSPARQL is expressive enough to answer queries considering the semantics of the RDFS vocabulary by directly traversing the input graph. We also show that nesting is necessary in nSPARQL to obtain this last result, and we study the expressiveness of the combination of nested regular expressions and SPARQL operators. Regarding complexity of evaluation, we prove that given an RDF graph G and a nested regular expression E, this problem can be solved in time O(|G|@?|E|).

Binary RDF representation for publication and exchange (HDT)

The current Web of Data is producing increasingly large RDF datasets. Massive publication efforts of RDF data driven by initiatives like the Linked Open Data movement, and the need to exchange large datasets has unveiled the drawbacks of traditional RDF representations, inspired and designed by a document-centric and human-readable Web. Among the main problems are high levels of verbosity/redundancy and weak machine-processable capabilities in the description of these datasets. This scenario calls for efficient formats for publication and exchange. This article presents a binary RDF representation addressing these issues. Based on a set of metrics that characterizes the skewed structure of real-world RDF data, we develop a proposal of an RDF representation that modularly partitions and efficiently represents three components of RDF datasets: Header information, a Dictionary, and the actual Triples structure (thus called HDT). Our experimental evaluation shows that datasets in HDT format can be compacted by more than fifteen times as compared to current naive representations, improving both parsing and processing while keeping a consistent publication scheme. Specific compression techniques over HDT further improve these compression rates and prove to outperform existing compression solutions for efficient RDF exchange.

Minimal Deductive Systems for RDF

This paper presents a minimalist program for RDF, by showing how one can do without several predicates and keywords of the RDF Schema vocabulary, obtaining a simpler language which preserves the original semantics. This approach is beneficial in at least two directions: (a) To have a simple abstract fragment of RDFS easy to formalize and to reason about, which captures the essence of RDFS; (b) To obtain algorithmic properties of deduction and optimizations that are relevant for particular fragments. Among our results are: the identification of a simple fragment of RDFS; the proof that it encompasses the main features of RDFS; a formal semantics and a deductive system for it; sound and complete deductive systems for their sub-fragments; and an

Temporal RDF

{\cal O}(n \log n)

Querying RDF data from a graph database perspective

complexity bound for ground entailment in this fragment.

Bipartite graphs as intermediate model for RDF

The Resource Description Framework (RDF) is a metadata model and language recommended by the W3C. This paper presents a framework to incorporate temporal reasoning into RDF, yielding temporal RDF graphs. We present a semantics for temporal RDF graphs, a syntax to incorporate temporality into standard RDF graphs, an inference system for temporal RDF graphs, complexity bounds showing that entailment in temporal RDF graphs does not yield extra asymptotic complexity with respect to standard RDF graphs and sketch a temporal query language for RDF.