10,324 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
AMaĻoSāAbstract 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. AMaĻoS 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 AMaĻoS and discusses how its current architecture realizes
these principles
Annotations for Rule-Based Models
The chapter reviews the syntax to store machine-readable annotations and
describes the mapping between rule-based modelling entities (e.g., agents and
rules) and these annotations. In particular, we review an annotation framework
and the associated guidelines for annotating rule-based models of molecular
interactions, encoded in the commonly used Kappa and BioNetGen languages, and
present prototypes that can be used to extract and query the annotations. An
ontology is used to annotate models and facilitate their description
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