1,537 research outputs found
vSPARQL: A View Definition Language for the Semantic Web
Translational medicine applications would like to leverage the biological and biomedical ontologies, vocabularies, and data sets available on the semantic web. We present a general solution for RDF information set reuse inspired by database views. Our view definition language, vSPARQL, allows applications to specify the exact content that they are interested in and how that content should be restructured or modified. Applications can access relevant content by querying against these view definitions. We evaluate the expressivity of our approach by defining views for practical use cases and comparing our view definition language to existing query languages
Context-Free Path Querying with Structural Representation of Result
Graph data model and graph databases are very popular in various areas such
as bioinformatics, semantic web, and social networks. One specific problem in
the area is a path querying with constraints formulated in terms of formal
grammars. The query in this approach is written as grammar, and paths querying
is graph parsing with respect to given grammar. There are several solutions to
it, but how to provide structural representation of query result which is
practical for answer processing and debugging is still an open problem. In this
paper we propose a graph parsing technique which allows one to build such
representation with respect to given grammar in polynomial time and space for
arbitrary context-free grammar and graph. Proposed algorithm is based on
generalized LL parsing algorithm, while previous solutions are based mostly on
CYK or Earley algorithms, which reduces time complexity in some cases.Comment: Evaluation extende
Leveraging Semantic Web Technologies for Managing Resources in a Multi-Domain Infrastructure-as-a-Service Environment
This paper reports on experience with using semantically-enabled network
resource models to construct an operational multi-domain networked
infrastructure-as-a-service (NIaaS) testbed called ExoGENI, recently funded
through NSF's GENI project. A defining property of NIaaS is the deep
integration of network provisioning functions alongside the more common storage
and computation provisioning functions. Resource provider topologies and user
requests can be described using network resource models with common base
classes for fundamental cyber-resources (links, nodes, interfaces) specialized
via virtualization and adaptations between networking layers to specific
technologies.
This problem space gives rise to a number of application areas where semantic
web technologies become highly useful - common information models and resource
class hierarchies simplify resource descriptions from multiple providers,
pathfinding and topology embedding algorithms rely on query abstractions as
building blocks.
The paper describes how the semantic resource description models enable
ExoGENI to autonomously instantiate on-demand virtual topologies of virtual
machines provisioned from cloud providers and are linked by on-demand virtual
connections acquired from multiple autonomous network providers to serve a
variety of applications ranging from distributed system experiments to
high-performance computing
RDF Querying
Reactive Web systems, Web services, and Web-based publish/
subscribe systems communicate events as XML messages, and in
many cases require composite event detection: it is not sufficient to react
to single event messages, but events have to be considered in relation to
other events that are received over time.
Emphasizing language design and formal semantics, we describe the
rule-based query language XChangeEQ for detecting composite events.
XChangeEQ is designed to completely cover and integrate the four complementary
querying dimensions: event data, event composition, temporal
relationships, and event accumulation. Semantics are provided as
model and fixpoint theories; while this is an established approach for rule
languages, it has not been applied for event queries before
NOUS: Construction and Querying of Dynamic Knowledge Graphs
The ability to construct domain specific knowledge graphs (KG) and perform
question-answering or hypothesis generation is a transformative capability.
Despite their value, automated construction of knowledge graphs remains an
expensive technical challenge that is beyond the reach for most enterprises and
academic institutions. We propose an end-to-end framework for developing custom
knowledge graph driven analytics for arbitrary application domains. The
uniqueness of our system lies A) in its combination of curated KGs along with
knowledge extracted from unstructured text, B) support for advanced trending
and explanatory questions on a dynamic KG, and C) the ability to answer queries
where the answer is embedded across multiple data sources.Comment: Codebase: https://github.com/streaming-graphs/NOU
Querying a regulatory model for compliant building design audit
The ingredients for an effective automated audit of a building design include a BIM model containing the design information, an electronic regulatory knowledge model, and a practical method of processing these computerised representations. There have been numerous approaches to computer-aided compliance audit in the AEC/FM domain over the last four decades, but none has yet evolved into a practical solution. One reason is that they have all been isolated attempts that lack any form of standardisation. The current research project therefore focuses on using an open standard regulatory knowledge and BIM representations in conjunction with open standard executable compliant design workflows to automate the compliance audit process. This paper provides an overview of different approaches to access information from a regulatory model representation. The paper then describes the use of a purpose-built high-level domain specific query language to extract regulatory information as part of the effort to automate manual design procedures for compliance audit
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