8,184 research outputs found
Using RDF to Model the Structure and Process of Systems
Many systems can be described in terms of networks of discrete elements and
their various relationships to one another. A semantic network, or
multi-relational network, is a directed labeled graph consisting of a
heterogeneous set of entities connected by a heterogeneous set of
relationships. Semantic networks serve as a promising general-purpose modeling
substrate for complex systems. Various standardized formats and tools are now
available to support practical, large-scale semantic network models. First, the
Resource Description Framework (RDF) offers a standardized semantic network
data model that can be further formalized by ontology modeling languages such
as RDF Schema (RDFS) and the Web Ontology Language (OWL). Second, the recent
introduction of highly performant triple-stores (i.e. semantic network
databases) allows semantic network models on the order of edges to be
efficiently stored and manipulated. RDF and its related technologies are
currently used extensively in the domains of computer science, digital library
science, and the biological sciences. This article will provide an introduction
to RDF/RDFS/OWL and an examination of its suitability to model discrete element
complex systems.Comment: International Conference on Complex Systems, Boston MA, October 200
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 Xcerptâs 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
ITR: A grammar-based graph compressor supporting fast neighborhood queries
Neighborhood queries are the most common queries on graphs; thus, it is
desirable to answer them efficiently on compressed data structures. We present
a compression scheme called Incidence-Type-RePair (ITR) for graphs with labeled
nodes and labeled edges based on RePair and apply the scheme to RDF graphs. We
show that ITR speeds up neighborhood queries to only a few milliseconds and
thereby outperforms existing solutions while providing a compression size
comparable to existing RDF graph compressors
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
Distributed Processing of Generalized Graph-Pattern Queries in SPARQL 1.1
We propose an efficient and scalable architecture for processing generalized
graph-pattern queries as they are specified by the current W3C recommendation
of the SPARQL 1.1 "Query Language" component. Specifically, the class of
queries we consider consists of sets of SPARQL triple patterns with labeled
property paths. From a relational perspective, this class resolves to
conjunctive queries of relational joins with additional graph-reachability
predicates. For the scalable, i.e., distributed, processing of this kind of
queries over very large RDF collections, we develop a suitable partitioning and
indexing scheme, which allows us to shard the RDF triples over an entire
cluster of compute nodes and to process an incoming SPARQL query over all of
the relevant graph partitions (and thus compute nodes) in parallel. Unlike most
prior works in this field, we specifically aim at the unified optimization and
distributed processing of queries consisting of both relational joins and
graph-reachability predicates. All communication among the compute nodes is
established via a proprietary, asynchronous communication protocol based on the
Message Passing Interface
An introduction to Graph Data Management
A graph database is a database where the data structures for the schema
and/or instances are modeled as a (labeled)(directed) graph or generalizations
of it, and where querying is expressed by graph-oriented operations and type
constructors. In this article we present the basic notions of graph databases,
give an historical overview of its main development, and study the main current
systems that implement them
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
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