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May 12, 2010

RIF (Core) and LOD

Linked Data (Semantic Web) candies
Image by reedster via Flickr

W3C has just published a Proposed Recommendation for the Rule Interchange Format (RIF); this means, in the W3C jargon, that the technical work is done, and the W3C asks its members for a seal of approval to publish it as Recommendation.

Somehow the RIF development was not on the radar screen of the Semantic Web community. There may be many reasons for that, and I think we should just accept this as part of history. The future is much more important; we should indeed realize that RIF is an important piece of the Semantic Web technical architecture and let us do our best to get it embraced widely.

RIF Core is the simplest variant of RIF. It is not very complicated. It is a simple rule language; one can define a series of Horn rules, there are some safety features built in so that the rules can be executed, conceptually, by a forward chaining engine, it has the familiar XSD datatypes with the usual operations, it operates on URI-s, and it has a notion analogous to RDF blank nodes. There is a separate document that describes how RIF (Core) rules operate with RDF data and how the various semantics (RIF, RDF(S), OWL) work together. The details are not really important here, suffices it to say that it, essentially, works like one would expect as a layperson… The RIF syntax is a little bit convoluted for the moment, but there may be work coming up to improve that in form of alternative, more readable syntaxes.

So what can it be used for? At the W3C LOD Camp in Raleigh (held as part of the WWW2010 conference), Sandro Hawke already gave a simple example why RIF should be interesting for LOD applications. Let me add a few further examples that might be of interest.

Remember OWL-RL? The OWL Working Group has defined a subset of OWL that can be handled by rules. The rules themselves were also published by the OWL WG, albeit using an abstract notation. Those rules can be described in RIF Core as well; the RIF group has published this mapping in a separate document. Following those rules a RIF Core engine can handle OWL-RL directly.

Why is that interesting?—you might ask. Well, there has been quite some discussions when defining OWL RL on whether the features included in OWL RL represent the right set for users. Some claimed that there are other OWL features that could be added; others said that, on the contrary, the complexity of OWL RL is already too high and the features should be reduced to make them more palatable to users. In some ways, the usage of RIF Core may make this discussion moot. Indeed, users, or user communities, can define the rules they are interested in RIF by cherry picking the rules described by the RIF WG in the document cited above. They can send those rules to their RIF Core reasoner alongside their data, and get what they want. If that rule set consists only of 2-3 OWL rules, because that is all the application cares about, than all the better, the RIF inference engine will just do its job faster. If the user wants to add OWL features that are not in OWL RL, that may also be doable; the OWL 2 RDF-Based semantics specification is such that, in many cases, the extra rules can be extracted fairly easily from the OWL 2 Full semantics, using the patterns in the RIF/OWL RL document (although I have to emphasize that this does not work in all cases!). Note that this model of “sending” the RIF rule set alongside the RDF data to a reasoner is exactly the way RIF reasoning is being defined for SPARQL1.1 in the separate Entailment Regimes document (still in draft). Note also that I referred to OWL RL here, but the same approach could be used with RDFS with, obviously, a smaller RIF Rule set.

Another, albeit related application of RIF came to my mind reading an email discussion on whether inferences should be materialized for large LOD datasets or not and, if yes, which ones. As an answer to Vasiliy Faronov’s question, Leigh Dodds also proposed a text to be added to his Linked Data Patterns book. The resulting discussion thread was really about which inferences should really be materialized. Materializing them all may not be realistic; but if only a selection of the possible inferences is used (eg, subset of RDFS or OWL) how would consumers of the data know? It looks like RIF may come to rescue. Publishers could simply publish the rules they use for materializing their inferences in RIF. (Again, this is not always possible; RIF cannot cover the whole of OWL. But it does cover a very large percentage of the use cases.) Consumers may actually choose whether they want to download all the triples, including the inferenced triples, or whether they choose to download data from the “core” dataset only together with the RIF file, and materialize the inferences locally using a local RIF engine (or use the RIF file with an RIF Entailment aware SPARQL 1.1 engine).

RIF is and should be considered as integral and essential part of the Semantic Web Technology landscape. Let us hope many implementations of, at least, RIF Core will bloom to make this a reality! (There is a public list of existing implementations so far.)


1 Comment

  1. Hello Ivan,

    While it troubles me to hear that this RIF was off the radar of those who would then presumably be the early adopters — am hoping that is not a trend, but rather an exception, as it would run against at least what I know about diffusion of innovation — it was off of my radar as well; I like the sounds of the flexibility here for a number of reasons, including simplicity and scaling. Hope it works as you describe. Thanks for the heads up from @ivan_herman

    .02 – MM

    Comment by Mark Montgomery — May 14, 2010 @ 23:38

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