Interpreting measurement and monitoring data from networks in general and the Internet in particular is a challenge. The motivation for this work has been to in- vestigate new ways to bridge the gap between the kind of data which are available and the more developed information which is needed by network stakeholders to support decision making and network management. Specific problems of syntax, semantics, conflicting data and modeling domain-specific knowledge have been identified. The methods developed and tested have used the Resource Descrip- tion Framework (rdf) and the ontology languages of the Semantic Web to bring together data from disparate sources into unified knowledgebases in two discrete case studies, both using real network data. Those knowledgebases have then been demonstrated to be usable and valuable sources of information about the networks concerned. Some success has been achieved in overcoming each of the identified problems using these techniques, proving the thesis that taking an ontological ap- proach to the processing of network monitoring data can be a very useful technique for overcoming problems of interpretation and for making information available to those who need it.
A Doctoral Thesis. Submitted in partial fulfilment of the requirements for the award of Doctor of Philosophy of Loughborough University.