Jeni's Musings

As you probably know, I’ve been working quite a lot recently on the UK government’s use of linked data, and in particular on providing guidance for people who want to publish their data as linked data. One of the things that we need to provide guidance about is how to publish linked data that changes over time. I’ve touched on this topic before but things have progressed now to the stage where we have to make some real, practical, recommendations.

data.gov.uk was finally launched to the public last week (still in beta, but now a more public beta than the beta that it’s been in for the last few months). It’s a great step forward, and everyone involved should be proud of both the amount of data that’s been made available and the website itself, which (unlike a lot of UK government IT) was developed rapidly by a small team based on open source software (and at low cost).

This is a first step on a long road.

This is the fifth part in this series about creating linked data. I’ve talked previously about analysis and modelling, defining URIs, defining concept schemes and defining a vocabulary. In this instalment I’ll talk about the finishing touches that can make linked data easier to browse, query, locate and trust.

Note that we don’t have to do any of these things; they’re not part of the core data. We shouldn’t beat ourselves up if we don’t have time to do it right now, because we can always add them later, and it might be that you just don’t agree that they should be done. But many of them don’t take a lot of time and can enhance the user’s experience of the data.

This is the fourth instalment in a series about turning an existing dataset into some linked data. I’ve previously talked about analysis and modelling, defining URIs and defining concept schemes. In this instalment, we’ll look at developing a schema in which we define the classes, properties and datatypes that we want to use in the RDF that describes the things in our dataset.

This is the third instalment in a series that I’m writing about turning data into linked data. I’m using traffic count data as the example, since that’s a dataset that I’m currently working on. In the last two instalments, I talked about analysing and modelling the data and about designing URIs for the things in that model.

Within the model, there are three sets of things that are concepts:

• road categories
• vehicle types
• cardinal directions