Data Model and Query Constructs for Versatile Web Query Languages

As the Semantic Web is gaining momentum, the need for truly versatile query languages becomes increasingly apparent. A Web query language is called versatile if it can access in the same query program data in different formats (e.g. XML and RDF). Most query languages are not versatile: they have not been specifically designed to cope with both worlds, providing a uniform language and common constructs to query and transform data in various formats. Moreover, most of them do not provide a flexible data model that is powerful enough to naturally convey both Semantic Web data formats (especially RDF and Topic Maps) and XML. This article highlights challenges related to the data model and language constructs for querying both standard Web and Semantic Web data with an emphasis on facilitating sophisticated reasoning. It is shown that Xcerpt’s data model and querying constructs are particularly well-suited for the Semantic Web, but that some adjustments of the Xcerpt syntax allow for even more effective and natural querying of RDF and Topic Maps

Model Theory and Entailment Rules for RDF Containers, Collections and Reification

An RDF graph is, at its core, just a set of statements consisting of subjects, predicates and objects. Nevertheless, since its inception practitioners have asked for richer data structures such as containers (for open lists, sets and bags), collections (for closed lists) and reification (for quoting and provenance). Though this desire has been addressed in the RDF primer and RDF Schema specification, they are explicitely ignored in its model theory. In this paper we formalize the intuitive semantics (as suggested by the RDF primer, the RDF Schema and RDF semantics specifications) of these compound data structures by two orthogonal extensions of the RDFS model theory (RDFCC for RDF containers and collections, and RDFR for RDF reification). Second, we give a set of entailment rules that is sound and complete for the RDFCC and RDFR model theories. We show that complexity of RDFCC and RDFR entailment remains the same as that of simple RDF entailment

AMaχoS—Abstract Machine for Xcerpt

Web query languages promise convenient and efficient access to Web data such as XML, RDF, or Topic Maps. Xcerpt is one such Web query language with strong emphasis on novel high-level constructs for effective and convenient query authoring, particularly tailored to versatile access to data in different Web formats such as XML or RDF. However, so far it lacks an efficient implementation to supplement the convenient language features. AMaχoS is an abstract machine implementation for Xcerpt that aims at efficiency and ease of deployment. It strictly separates compilation and execution of queries: Queries are compiled once to abstract machine code that consists in (1) a code segment with instructions for evaluating each rule and (2) a hint segment that provides the abstract machine with optimization hints derived by the query compilation. This article summarizes the motivation and principles behind AMaχoS and discusses how its current architecture realizes these principles

Data Integration on the (Semantic) Web with Rules and Rich Unification

For the last decade a multitude of new data formats for the World Wide Web have been developed, and a huge amount of heterogeneous semi-structured data is flourishing online. With the ever increasing number of documents on the Web, rules have been identified as the means of choice for reasoning about this data, transforming and integrating it. Query languages such as SPARQL and rule languages such as Xcerpt use compound queries that are matched or unified with semi-structured data. This notion of unification is different from the one that is known from logic programming engines in that it (i) provides constructs that allow queries to be incomplete in several ways (ii) in that variables may have different types, (iii) in that it results in sets of substitutions for the variables in the query instead of a single substitution and (iv) in that subsumption between queries is much harder to decide than in logic programming. This thesis abstracts from Xcerpt query term simulation, SPARQL graph pattern matching and XPath XML document matching, and shows that all of them can be considered as a form of rich unification. Given a set of mappings between substitution sets of different languages, this abstraction opens up the possibility for format-versatile querying, i.e. combination of queries in different formats, or transformation of one format into another format within a single rule. To show the superiority of this approach, this thesis introduces an extension of Xcerpt called Xcrdf, and describes use-cases for the combined querying and integration of RDF and XML data. With XML being the predominant Web format, and RDF the predominant Semantic Web format, Xcrdf extends Xcerpt by a set of RDF query terms and construct terms, including query primitives for RDF containers collections and reifications. Moreover, Xcrdf includes an RDF path query language called RPL that is more expressive than previously proposed polynomial-time RDF path query languages, but can still be evaluated in polynomial time combined complexity. Besides the introduction of this framework for data integration based on rich unification, this thesis extends the theoretical knowledge about Xcerpt in several ways: We show that Xcerpt simulation unification is decidable, and give complexity bounds for subsumption in several fragments of Xcerpt query terms. The proof is based on a set of subsumption monotone query term transformations, and is only feasible because of the injectivity requirement on subterms of Xcerpt queries. The proof gives rise to an algorithm for deciding Xcerpt query term simulation. Moreover, we give a semantics to locally and weakly stratified Xcerpt programs, but this semantics is applicable not only to Xcerpt, but to any rule language with rich unification, including multi-rule SPARQL programs. Finally, we show how Xcerpt grouping stratification can be reduced to Xcerpt negation stratification, thereby also introducing the notion of local grouping stratification and weak grouping stratification

Taming Existence in RDF Querying

We introduce the recursive, rule-based RDF query language RDFLog. RDFLog extends previous RDF query languages by arbitrary quantifier alternation: blank nodes may occur in the scope of all, some, or none of the universal variables of a rule. In addition RDFLog is aware of important RDF features such as the distinction between blank nodes, literals and URIs or the RDFS vocabulary. The semantics of RDFLog is closed (every answer is an RDF graph), but lifts RDF’s restrictions on literal and blank node occurrences for intermediary data. We show how to define a sound and complete operational semantics that can be implemented using existing logic programming techniques. Using RDFLog we classify previous approaches to RDF querying along their support for blank node construction and show equivalence between languages with full quantifier alternation and languages with only ∀∃ rules

Effective and Efficient Data Access in the Versatile Web Query Language Xcerpt

Access to Web data has become an integral part of many applications and services. In the past, such data has usually been accessed through human-tailoredHTMLinterfaces.Nowadays, rich client interfaces in desktop applications or, increasingly, in browser-based clients ease data access and allow more complex client processing based on XML or RDF data retrieved throughWeb service interfaces. Convenient specifications of the data processing on the client and flexible, expressive service interfaces for data access become essential in this context.Web query languages such as XQuery, XSLT, SPARQL, or Xcerpt have been tailored specifically for such a setting: declarative and efficient access and processing ofWeb data. Xcerpt stands apart among these languages by its versatility, i.e., its ability to access not just oneWeb format but many. In this demonstration, two aspects of Xcerpt are illustrated in detail: The first part of the demonstration focuses on Xcerpt’s pattern matching constructs and rules to enable effective and versatile data access. It uses a concrete practical use case from bibliography management to illustrate these language features. Xcerpt’s visual companion language visXcerpt is used to provide an intuitive interface to both data and queries. The second part of the demonstration shows recent advancements in Xcerpt’s implementation focusing on experimental evaluation of recent complexity results and optimization techniques, as well as scalability over a number of usage scenarios and input sizes

Foundations of Rule-Based Query Answering

This survey article introduces into the essential concepts and methods underlying rule-based query languages. It covers four complementary areas: declarative semantics based on adaptations of mathematical logic, operational semantics, complexity and expressive power, and optimisation of query evaluation. The treatment of these areas is foundation-oriented, the foundations having resulted from over four decades of research in the logic programming and database communities on combinations of query languages and rules. These results have later formed the basis for conceiving, improving, and implementing several Web and Semantic Web technologies, in particular query languages such as XQuery or SPARQL for querying relational, XML, and RDF data, and rule languages like the “Rule Interchange Framework (RIF)” currently being developed in a working group of the W3C. Coverage of the article is deliberately limited to declarative languages in a classical setting: issues such as query answering in F-Logic or in description logics, or the relationship of query answering to reactive rules and events, are not addressed