Different people may have different perspectives on provenance, and as a result different types of information might be captured in provenance records.

The answer to the question, “when should I use RDF-Star and when shouldn’t I?” is actually right in the RDF-Star working group charter; it is for making statements about statements, and that’s all. It’s not for making statements about things in your domain, like flights, doctor visits, procedures, or costs.

One of the issues that inhibits adoption of RDF is the the perception that it is lacking somehow in representational power.

One of the book club members made an interesting comment; he asked why Michael hadn’t modeled this in the ‘obvious’ and ‘simple’ way, by saying something like:

With RDF-Star, we add in the ability to make statements about statements. What sorts of things do we have to say about statements? We could tell “who claims this statement is true?” or “at what point in time was this statement true?” or even “when did we learn about this statement?”.

Using RDF-Star simply encouraged poor modeling practice, of ignoring the everyday name for something (a “flight”) and using a statement in its place. And when I say “everyday name”, for those of you who do enterprise data modeling, you should read “business terminology”, since in an enterprise setting, these terms are the terms that the business uses (who do you think taught me a word like “offer”? A data modeler? Or an investment banker? Or William Shatner?).

If at this point you have decided that modeling a visit isn’t such a bad thing to do, you might be wondering how to find notions like “visit”, that appear in our everyday discourse, and know when those are things you should be modeling. If you are wondering this, you’re in luck; Michael’s book (linked above) needs to go on your reading list.

One more triple doesn’t seem like a lot, but if you do this for every statement, that’s twice as many triples. And that means twice as much space, twice as much to think about, twice the overhead.

So what is RDF-Star? According to the working group charter, it is “[an extension of] RDF and SPARQL related recommendations, with the ability to concisely represent and query statements about statements.” In short, it is a way to include triples whose subject or object are themselves references to RDF triples.

exc:compose1 prov:qualifiedUsage [ a prov:Usage ; prov:entity exg:dataset1 ; prov:hadRole exc:dataToCompose ] .

article

regionList

role

Provenance can be used for many purposes, such as understanding how data was collected so it can be meaningfully used, determining ownership and rights over an object, making judgements about information to determine whether to trust it, verifying that the process and steps used to obtain a result complies with given requirements, and reproducing how something was generated.

here.

tutorials

There are things out there but only the academic who worked on it knows how to make it work. The documentation is usually non-extant and trying to figure things out can take a lot of precious time.

Inputs