Over the past couple of weeks I’ve been putting together a basic data model for BBC News. The purpose of the model is to allow us to make typed associations between real-world concepts and creative works published by journalists. We are interested in four classes of real-world concepts:
- intangibles (topics or themes)
Additionally we have events, which are really the intersection of people/organisations doing things at a particular place and time, as described in the much-used event ontology. We also have a sixth class called ‘story’ – a collection of events, drived from the stories ontology.
The typed associations that are allowed between the above concepts and the published works are currently:
and soon I hope we can add ‘took place in’ or something similar for location-based associations (most news events happen in a place but are not usually about that place).
Here’s a v0.2 representation of this model (I left 0.1 on a bit of paper in the pub):
The idea is that journalists will apply instances of these classes, together with their typed relationship, as part of the publishing process for BBC News online. We can then expose these instances as navigation routes (like the tags on the Guardian’s website) to allow users to browse more news about that person, organisation, place or event. At the same time publishing indexes (aggregation pages) for these instances will help improve BBC News’s Search Engine Optimisation and help drive traffic to the site.
RDF of this model is here.