UCIAD is a relatively small, experimental project looking at how semantic technologies can help the user-centric integration, analysis and interpretation of activity data in a large organisation. As such, as suggested also to all the other projects in the JISC Activity Data programme, it relies on a central hypothesis that will hopefully be verified through the realisation and application of our software platform. But before we can express this hypothesis, we need to introduce a bit of background. Especially, we beed to get back to what we mean by “user-centric”.
To put it simply, a user-centric approach is considered here in opposition to an organisation-centric approach. The most common way of considering activity data in large organisations at the moment is through consolidating visits to websites in analytics, giving statistics about the number of visits on a given website or webpage, and where these visits were coming from. We qualify this as an organisation-centric view as the central point of focus is the website managed by the organisation. By taking such a restricted perspective on the interpretation of activity data, a number of potentially interesting questions, that take the users concerned with the activity data as the focus point, cannot be answered. The analysis of the activity data can also be only beneficial to the organisation, and not the user, as each user becomes aggregated in website related statistics. We therefore express our main hypothesis as
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.
As described in our work plan (see previous blog post), our first task is therefore to build an ontology able to flexibly describe the traces of activities across multiple websites, the users of these websites 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.