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.

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|).

Abstract. 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 expressive 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. 1

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.

Abstract. This article introduces KWQL, spoken “quickel”, a rulebased query language for a semantic wiki based on the label-keyword query paradigm. KWQL allows for rich combined queries of full text, document structure, and informal to formal semantic annotations. It offers support for continuous queries, that is, queries re-evaluated upon updates to the wiki. KWQL is not restricted to data selection, but also offers database-like views, enabling “construction”, the re-shaping of the selected (meta-)data into new (meta-)data. Such views amount to rules that provide a convenient basis for an admittedly simple, yet remarkably powerful form of reasoning. KWQL queries range from simple lists of keywords or label-keyword pairs to conjunctions, disjunctions, or negations of queries. Thus, queries range from elementary and relatively unspecific to complex and fully specified (meta-)data selections. Consequently, in keeping with the “wiki way”, KWQL has a low entry barrier, allowing casual users to easily locate and retrieve relevant data, while letting advanced users make use of its full power. 1

Exposing not only human-centered information, but machine-processable data on the Web is one of the commonalities of recent Web trends. It has enabled a new kind of applications and businesses where the data is used in ways not foreseen by the data providers. Yet this exposition has fractured the Web into islands of data, each in different Web formats: Some providers choose XML, others RDF, again others JSON or OWL, for their data, even in similar domains. This fracturing stifles innovation as application builders have to cope not only with one Web stack (e.g., XML technology) but with several ones, each of considerable complexity. With Xcerpt we have developed a rule- and pattern based query language that aims to give shield application builders from much of this complexity: In a single query language XML and RDF data can be accessed, processed, combined, and re-published. Though the need for combined access to XML and RDF data has been recognized in previous work (including the W3C’s GRDDL), our approach differs in four main aspects: (1) We provide a single language (rather than two separate or embedded languages), thus minimizing the conceptual overhead of dealing with disparate data formats. (2) Both the declarative (logic-based) and the operational semantics are unified in that they apply for querying XML and RDF in the same way. (3) We show that the resulting query language can be implemented reusing traditional database technology, if desirable. Nevertheless, we also give a unified evaluation approach based on interval labelings of graphs that is at least as fast as existing approaches for tree-shaped XML data, yet provides linear time and space querying also for many RDF graphs. We believe that Web query languages are the right tool for declarative data access in Web applications and that Xcerpt is a significant step towards a more convenient, yet highly efficient data access in a “Web of Data”.

The Semantic Web is the initiative of the W3C to make information on the Web readable not only by humans but also by machines. RDF is the data model for Semantic Web data, and SPARQL is the standard query language for this data model. In the last ten years, we have witnessed a constant growth in the amount of RDF data available on the Web, which have motivated the theoretical study of some fundamental aspects of SPARQL and the development of efficient mechanisms for implementing this query language. Some of the distinctive features of RDF have made the study and implementation of SPARQL challenging. First, as opposed to usual database applications, the semantics of RDF is open world, making RDF databases inherently incomplete. Thus, one usually obtains partial answers when querying RDF with SPARQL, and the possibility of adding optional information if present is a crucial feature of SPARQL. Second, RDF databases have a graph structure and are interlinked, thus making graph navigational capabilities a necessary component of SPARQL. Last, but not least, SPARQL has to work at Web scale! RDF and SPARQL have attracted interest from the database community. However, we think that this community has much more to say about these technologies, and, in particular, about the fundamental database problems that need to be solved in order to provide solid foundations for the development of these technologies. In this paper, we survey some of the main results about the theory of RDF and SPARQL putting emphasis on some research opportunities for the database community.

One significant effort towards combining the virtues of Web search, viz. being accessible to untrained users and able to cope with vastly heterogeneous data, with those of database-style Web queries is are keyword-based Web query languages. These languages operate essentially in the same setting as XQuery or SPARQL but with an interface for untrained users. Keyword-based query languages trade some of the precision that languages like XQuery enable by allowing to formulate exactly what data to select and how to process it, for an easier interface accessible to untrained users. The yardstick for these languages becomes an easily accessible interface that does not sacrifice the essential premise of database-style Web queries, that selection and construction are precise enough to fully automate data processing tasks. To ground the discussion of keyword-based query languages, we give a summary of what we perceive as the main contributions of research and development on Web query languages in the past decade. This summary focuses specifically on what sets Web query languages apart from their predecessors for databases. Further, this tutorial (1) gives an overview over keyword-based query languages for XML and RDF (2) discusses where the existing approaches succeed and what, in our opinion, are the most glaring open issues, and (3) where, beyond keyword-based query languages, we see the need, the challenges, and the opportunities for combining the ease of use of Web search with the virtues of Web queries.

Abstract. The MapReduce programming model has gained traction in different application areas in recent years, ranging from the analysis of log files to the computation of the RDFS closure. Yet, for most users the MapReduce abstraction is too low-level since even simple computations have to be expressed as Map and Reduce phases. In this paper we propose RDFPath, an expressive RDF path query language geared towards casual users that benefits from the scaling properties of the MapReduce framework by automatically transforming declarative path queries into MapReduce jobs. Our evaluation on a real world data set shows the applicability of RDFPath for investigating typical graph properties like shortest paths.

The Semantic Web is the initiative of the W3C to make information on the Web readable not only by humans but also by machines. RDF is the data model for Semantic Web data, and SPARQL is the standard query language