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December 01, 2009

On "Creating Linked Data"

In the age of Twitter, short, "hey, this is cool" blog posts providing quick pointers have rather fallen out of fashion, but I thought this material was worth drawing attention to here. Jeni Tennison, who is contributing to the current work with Linked Data in UK government, has embarked on a short series of tutorial-style posts called "Creating Linked Data", in which she explains the steps typically involved in reformulating existing data as linked data, and discusses some of the issues arising.

Her "use case" is the scenario in which some data is currently available in CSV format, but I think much of the discussion could equally be applied to the case where the provider is making data available for the first time. The opening post on the sequence ("Analysing and Modelling") provides a nice example of working through the sort of "things or strings?" questions which we've tried to highlight in the context of designing DC Application Profiles. And as Jeni emphasises, this always involves design choices:

It’s worth noting that this is a design process rather than a discovery process. There is no inherent model in any set of data; I can guarantee you that someone else will break down a given set of data in a different way from you. That means you have to make decisions along the way.

And further on in the piece, she rationalises her choices for this example in terms of what those choices enable (e.g. "whenever there’s a set of enumerated values it’s a good idea to consider turning them into things, because to do so enables you to associate extra information about them").

The post on URI design offers some tips, not only on designing new URIs but also on using existing URIs where appropriate: I admit I tend to forget about useful resources like placetime.com "a URI space containing URIs that represent places and times" (and provides redirects to descriptions in various formats).

On a related note, the post on choosing/coining properties, classes and datatypes includes a pointer to the OWL Time ontology. This is something I was aware of, but only looked at in any detail relatively recently. At first glance it can seem rather complex; Ian Davis has a summary graphic which I found helpful in trying to get my head round the core concepts of the ontology.

It seems to me these sort of very common areas like time data are those around which some shared practice will emerge, and articles like these, by "hands-on" practitioners, are important contributions to that process.


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