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An assessment of RDF/OWL modelling
Reynolds, Dave; Thompson, Carol; Mukerji, Jishnu; Coleman, Derek
HPL-2005-189
Keyword(s): semantic web; modelling
Abstract: The Semantic Web initiative offers a set of standards (RDF, RDFS and OWL) for the representation and exchange of information. We address the question of what sorts of modelling problems these standards can be most fruitfully applied to. What benefits can be gained from using them? What are the costs and trade-offs involved? We use some simplified examples drawn from work exploring the use of RDF/OWL within a systems management setting but the overall discussion should be relevant to a broad range of potential RDF/OWL applications. We do not assume in depth knowledge of the RDF and OWL standards and include a summary of their main features in order to make the discussion accessible. We identify the primary strengths of RDF/OWL as:
- support for information integration and reuse of shared vocabularies
- handling of semi-structured data
- separation of syntax from data modelling -web embedding
- extensibility and resilience to change
- support for inference and classification, based on a formal semantics
- representation flexibility, especially ability to model graph structures
- ability to represent instance and class information in the same formalism and hence combine them
Weaknesses noted are:
- weak ability to validate documents
- expressivity limitations, particularly in terms of correlating across different properties of a resource
- performance -XML serialization issues and impedance mismatch with XML tooling
- lack of familiarity and potentially high learning curve
- inability to natively represent uncertain data and continuous domains
- no built-in representation of processes and change
We conclude that RDF/OWL is particularly suited to modelling applications which involve distributed information problems such as integration of data from multiple sources, publication of shared vocabularies to enable interoperability and development of resilient networks of systems which can cope with changes to the data models. It has less to offer in closed world or point- to-point processing problems where the data models are stable and the data is not to be made available to other clients. It is also largely unsuited to domains involving continuous or fuzzy categories. Notes: Carol Thompson, Jishnu Mukerji and Derek Coleman, HP SGBU (Software Global Business Unit)
24 Pages
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