Comparison of OData and Semantic Web/Linked Data

Question

I'm trying to get my head around two very different approaches to data sharing: OData and Semantic Web/Linked Data. Is there a good comparison of the two?

As I understand it, OData combines syndication/CRUD (AtomPub), serialisation formats (XML, JSON), a data model, a query language, and some semantics/conventions governing use of those existing technologies. It's primarily intended for exposing data from one system so that others can consume it.

Linked Data is a data model, a rigorous commitment to URIs, an (optional?) serialisation format (RDF/XML), but (correct me if I'm wrong) doesn't say anything about transport, CRUD, etc. It seems intended to allow inferencing across lots of little chunks of data drawn from a wide variety of sources. (Not something of major importance to us right now - we would be synchronising large slabs of data between a small number of sources, and wanting to preserve provenance information).

I'm interested in technologies for sharing data between certain data management platforms, some of which I work on directly. OData seems more appealing as it's very straightforward to explain to developers: implement this API, follow that Atom standard, serialise the data like this. We're already doing something very similar for one platform: sharing XML-serialised data on an Atom feed, with URL parameters used to filter.

By contrast, my past experiences working with RDF have given me an impression of brittle, opaque (massive slabs of RDF/XML), inaccessible (using SPARQL vs SQL) technology - but perhaps I'm confusing the experience of working with a triplestore like Jena with simply exposing an existing database via a linked data API.

Any pointers, comments etc on the differences and similarities between these two approaches in terms of scope, technologies, ease, future potential etc would be great.

Answer 1

I think discussing this in depth is not really what Stackoverflow is meant for, but just to give you some pointers to interesting discussions about differences and overlap:

• Oh - it is data on the Web
• Microsoft, OData and RDF

One of the key differences seems to be that OData has no means to link data from different sources to each other. Essentially, you're still stuck in a silo.

It might also be interesting to check out various attempts to convert data between the two approaches. See a.o. http://answers.semanticweb.com/questions/1298/has-anyone-written-a-mapping-from-odata-to-rdf .

Answer 2

OData may be easier, but its not better, by any means. SPARQL and RDF (forget RDF/XML, better to look at Turtle) satisfies everything in OData along with providing many more cutting edge features such as:

• Federation Extensions
• Linked Data
• Reasoning and Inference (for the more brave)

Equally, the software supporting the standards is actually quite sophisticated. Most people interested in OData generally come from a Microsoft background, so take a look at dotNetRdf

Answer 3

Here's a comparison matrix:

http://uoccou.wordpress.com/2011/02/17/linked-data-odata-gdata-datarss-comparison-matrix/

Unfortunately the table formatting is pretty horrible, but the content is useful.