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 International Conference on Complex Systems (ICCS2007)

Using RDF to Model the Structure and Process of Systems

Marko Rodriguez
Los Alamos National Laboratory

Jennifer Watkins
Los Alamos National Laboratory

Johan Bollen
Los Alamos National Laboratory

Carlos Gershenson
New England Complex Systems Institute

     Full text: PDF
     Last modified: October 15, 2007

Abstract
Many if not most complex systems can be described in terms of networks of discrete elements and their various relationships. 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 thus serve as a promising general-purpose modeling substrate for complex systems. In addition to the interesting theoretical implications of such a modeling approach, various standardized formats and tools are now available to support practical, large-scale computations on semantic networks. 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 $10^{10}$ 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. Furthermore, a review of the most promising algorithms and tools to manipulate such networks will be presented. Finally, current methods to encode process information into a semantic network instance such that a single semantic network instance can be used to represent both the state of a system and its evolutionary processes will be presented. The benefits of this last aspect is that researchers can efficiently share their RDF models and algorithms in terms of a common, well-standardized semantic network substrate.







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