1,287 research outputs found
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
Four Lessons in Versatility or How Query Languages Adapt to the Web
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”
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
A Perfect Match for Reasoning, Explanation, and Reason Maintenance
Path query languages have been previously shown to com-
plement RDF rule languages in a natural way and have been used as
a means to implement the RDFS derivation rules. RPL is a novel path
query language specifically designed to be incorporated with RDF rules
and comes in three
avors: Node-, edge- and path-
avored expressions
allow to express conditional regular expressions over the nodes, edges, or
nodes and edges appearing on paths within RDF graphs. Providing reg-
ular string expressions and negation, RPL is more expressive than other
RDF path languages that have been proposed. We give a compositional
semantics for RPL and show that it can be evaluated efficiently, while
several possible extensions of it cannot
Expressive Stream Reasoning with Laser
An increasing number of use cases require a timely extraction of non-trivial
knowledge from semantically annotated data streams, especially on the Web and
for the Internet of Things (IoT). Often, this extraction requires expressive
reasoning, which is challenging to compute on large streams. We propose Laser,
a new reasoner that supports a pragmatic, non-trivial fragment of the logic
LARS which extends Answer Set Programming (ASP) for streams. At its core, Laser
implements a novel evaluation procedure which annotates formulae to avoid the
re-computation of duplicates at multiple time points. This procedure, combined
with a judicious implementation of the LARS operators, is responsible for
significantly better runtimes than the ones of other state-of-the-art systems
like C-SPARQL and CQELS, or an implementation of LARS which runs on the ASP
solver Clingo. This enables the application of expressive logic-based reasoning
to large streams and opens the door to a wider range of stream reasoning use
cases.Comment: 19 pages, 5 figures. Extended version of accepted paper at ISWC 201
Semantics and Validation of Shapes Schemas for RDF
We present a formal semantics and proof of soundness for shapes schemas, an
expressive schema language for RDF graphs that is the foundation of Shape
Expressions Language 2.0. It can be used to describe the vocabulary and the
structure of an RDF graph, and to constrain the admissible properties and
values for nodes in that graph. The language defines a typing mechanism called
shapes against which nodes of the graph can be checked. It includes an
algebraic grouping operator, a choice operator and cardinality constraints for
the number of allowed occurrences of a property. Shapes can be combined using
Boolean operators, and can use possibly recursive references to other shapes.
We describe the syntax of the language and define its semantics. The
semantics is proven to be well-defined for schemas that satisfy a reasonable
syntactic restriction, namely stratified use of negation and recursion. We
present two algorithms for the validation of an RDF graph against a shapes
schema. The first algorithm is a direct implementation of the semantics,
whereas the second is a non-trivial improvement. We also briefly give
implementation guidelines
A comparison of the cognitive difficulties posed by SPARQL query constructs
This study investigated difficulties in the comprehension of SPARQL. In particular, it compared the declarative and navigational styles present in the language, and various operators used in SPARQL property paths. The study involved participants selecting possible answers given a SPARQL query and knowledgebase. In general, no significant differences were found in terms of the response time and accuracy with which participants could answer questions expressed in either a declarative or navigational form. However, UNION did take significantly longer to comprehend than both braces and verti- cal line in property paths; with braces being faster than vertical line. Inversion and negated property paths both proved difficult, with their combination being very difficult indeed. Questions involving MINUS were answered more accu- rately than those involving negation in property paths, in particular where pred- icates were inverted. Both involve negation, but the semantics are different. With the MINUS questions, negation and inversion can be considered separate- ly; with property paths, negation and inversion need to be considered together. Participants generally expressed a preference for data represented graphically, and this preference was significantly correlated with accuracy of comprehen- sion. Implications for the design and use of query languages are discussed
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