Hypothesis 1: Taking a user-centric point of view can enable different types of analysis of activity data, which are valuable to the organisation and the user.
Ontologies are formal, machine processable conceptual models of a domain. Ontology technologies, especially associated with technologies from the semantic web, have proven useful in situations where a meaningful integration of large amounts of heterogeneous data need to be realised, and to a certain extent, reasoned upon in a qualitative way, for interpretation and analysis. Our goal here is to investigate how ontologies and semantic technologies can support the user- centric analysis of activity data. In other words, our second hypothesis is
Hypothesis 2: Ontologies and ontology-based reasoning can support the integration, consolidation and interpretation of activity data from multiple sources.
To test this the first task was to build an ontology capable of flexibly describing the traces of activities across multiple web sites, the users of these web sites and the connections between them. The idea is to use this ontology (or rather, this set of ontologies) as a basis for a pluggable software framework, capable of integrating data from heterogeneous logs, and to interpret such data as traces of high-level activities.