- From: Kurt Cagle <kurt.cagle@g...>
- To: Stephen Green <stephengreenubl@g...>
- Date: Thu, 17 Feb 2022 09:17:40 -0800
Good point. Kurt Cagle Community/Managing Editor Data Science Central, A TechTarget Property
OK. But some objections here to RDF might apply to some of the stack but not apply to OWL. Owl is a part of the RDF stack, IMO.
Why RDF? Why not OWL? On Thu, 17 Feb 2022 at 09:09, Hans-Juergen Rennau < hrennau@y...> wrote:
A very interesting point, which I read as this: if you take responsibility for large-scale data modeling, think twice before daring to do it without being backed by an RDF view of the things you are dealing with.
Large-scale data modeling is, of course, the work of a very small group of people. On the other hand, what is of immediate and practical importance for a major part of development work is APIs. As you did not mention them, I suppose there are no important NIEM-related APIs which are based on RDF. If indeed not, this would even be a little surprising - could not graph patterns be important for users of NIEM encoded data?
Am Mittwoch, 16. Februar 2022, 23:46:18 MEZ hat Webb Roberts < webb@w...> Folgendes geschrieben:
On Feb 15, 2022, at 05:16, Hans-Juergen Rennau < hrennau@y...> wrote:
Thank you, Webb. One question: was the alignment of XML and RDF important for the use of the data? Such importance can be easily imagined - e.g. graph queries revealing patterns difficult to detect without a graph representation - but if it has been actually experienced is of course a different question.
I would say that NIEM's alignment between XML and RDF is *very* important for use of the data.
XML and XML Schema don't address a lot of issues fundamental to understanding data. What does a block of XML mean? What does type extension mean? What does an element containing another element mean? By defining the interpretation of NIEM data based on RDF, we get a real semantic model that explains a lot about the meaning of any given block of data.
But a lot of people don't care about that level of detail about the meaning of data — it's too philosophical, too esoteric.
For them, the XML data looks like a straightforward use of XML - elements with sub-elements, types with base types, IDREFs linking to IDs - all clearly named and not too hard to understand.
However, the rigor that the XML–RDF alignment provided helped to ensure that a lot of things were done in a consistent manner across a very large number of data definitions. And that diligence helps make a big pile of data understandable. The alignment to RDF benefits everyone who uses it, even those who don't care at all about RDF.
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