One of the features of our RDFa parser (Ubiquity RDFa) is the ability to import RDFa from external documents. This is particularly useful for bringing in definitions for templates and other processing rules that you would like to have applied to the document being parsed, or for importing one definition into another (owl:imports is implemented this way). The technique used to garner these triples is simply to import the external document into a hidden iframe, and then run the parser on it. However, as the JavaScript programmers amongst you will know, that only gets you so far; if the document containing the RDFa you want to import comes from a different domain to the one that your source document originates from, most browsers won’t give you access to the DOM in the iframe. There are all sorts of ways to try to work around this, and a common one is to use a server to convert the RDFa to JSON, since script tags aren’t victims of the cross- domain limitation. We therefore decided to create a JSON format that was as close as possible to RDFa. Of course, since RDFa itself is a serialisation of RDF, then really we were actually looking to create a JSON format for RDF.


A JSON format for RDF does already exist, called RDF/JSON, and devised by some of the clever semantic web folks at Talis. However, the main problem with this serialisation is that it’s sole purpose is to be just that – a serialisation. Although it ‘does what it says on the tin’, it doesn’t do any more than that.

JSON and semantic objects

We found that our goal was quite different. We’ve been using JavaScript for more and more of our work, and the RDFa parser was increasingly becoming a dynamic JSON object creation mechanism (more on this in a future post). We therefore wanted a closer relationship between JSON and RDF than RDF/JSON provided.

Functions as objects

For example, we often retrieve a set of triples from a triple store, use the triples to create JSON objects, and then check to see if any of the objects have ‘action’ properties on them. If we find such a property, it is executed as a function. Since the action property will serve as a function, the most natural way to express this in JSON would be as follows: { “http://ubiquity-”: function(obj) { doSomething(); return; } } Of course, we could have expressed this in RDF/JSON by turning the function into a string and then having our code use eval() to execute it: { “_:abc” : { “” : [ { “value” : “ \ doSomething(); \ return;”, “type” : “literal” } ] } } However, there are many benefits to passing around ‘real’ functions rather than strings. An obvious one is not having to use the JavaScript line continuation character all the time, but probably the main benefit is that we’ll spot any errors in our script before the code is executed; if our editor supports syntax highlighting we’ll see errors there, and when our code is loaded in the browser, the function will be parsed then, and any JSON loading errors will show up.

Anonymous objects

Another example of how we’d like to take advantage of the natural flow of JSON is with anonymous objects. It’s common to have structures where one object relates to another, and in RDF this is often achieved with a bnode – essentially an identifier that is only usable as a reference within the context of the document, and not by any other documents. RDF/JSON would represent the relationship between such structures like this: { “” : { “” : [ { “value” : “Anna’s Homepage”, “type” : “literal”, “lang” : “en” } ] , “” : [ { “value” : “:person”, “type” : “bnode” } ] } , “:person” : { “” : [ { “value” : “”, “type” : “uri” } ] , “” : [ { “value” : “Anna Wilder”, “type” : “literal” } ] } } Here we are saying that the web-site at URL was ‘made’ by the item that has the bnode identifier _:person, and in turn, that the item with the bnode identifier _:person has the name ‘Anna Wilder’. RDFj supports the same kind of ‘explicit bnode’ approach as well: [ { “$”: “”, “”: “Anna’s Homepage”, “”: “" }, { "$": "", "": "Anna Wilder", "": "<>" } ] However, in situations where an item is not referred to from elsewhere, RDFj also provides a more natural format -- the JSON object being referred to becomes the actual value of the predicate: { "$": "<>", "": "Anna's Homepage", "": { "": "Anna Wilder", "": "<>" } }

From JSON to RDF, rather than RDF to JSON

Essentially, what we’ve done with RDFj is to map JSON to RDF – with a few extra tweaks thrown in – rather than simply mapping RDF to JSON. (RDFa took the same approach, starting with HTML, and then working out what RDF various patterns might represent.) There are of course many uses for the straightforward serialisation approach, taken by RDF/JSON. But we’re finding that as our applications increasingly use both JavaScript and RDF, it’s very useful to blur the lines between the two. RDFj takes us an important step towards that. The latest definition of RDFj is on the Ubiquity RDFa Google Code project.