What is the difference between GraphQL and SPARQL?

Question

I'm doing a lot of research right now on Semantic Web and complex data models that represent relationships between individuals and organizations. I knew a little semantic ontologies although I never understood what it was used if not make graphs.

I saw on university wiki that the language to question an ontology is the SPARQL (tell me if I'm wrong).

But recently I saw a company that had created a semantic ontology put it in the form of GraphQL that I did not know (https://diffuseur.datatourisme.gouv.fr/graphql/voyager/).

It seems to me that semantic ontologies are made to better find information, for example to make a chatbot (it's what I want to do), but here they transformed a semantic ontology into an API, is it right? To make a GraphQL, should I build first a semantic ontology?

Could you explain to me a little the difference between all this, honestly it's a little vague for me.

Answer 1

Context

Datatourisme is a platform that allows to publish (via the Producteur component) and to consume (via the Diffuseur component) POI-related open data.

It seems you have linked to a particular application developed over Diffuseur with a help of GraphQL Voyager. The application illustrates capabilities of the GraphQL API exposed by Diffuseur.

The API documentation is available here (in French):

• datatourisme.frama.io/api
• framagit.org/datatourisme/api

Problem

• Datatourisme stores data in the RDF format (presumably using the Blazegraph triplestore)
• Datatourisme provides access via GraphQL (not SPARQL)

Why RDF

• Partly due to some "schemaless", RDF is convenient in heterogeneous data integration tasks:

  Tourism national ontology structuring in a common sharing format the whole tourism data extracted from different official French data bases: entertainment and events, natural and cultural sites, leisure and sports activities, touristic products, tours, accomodations, shops, restaurants.

• RDF is semantic: in particular, RDF is self-describing.

SPARQL

• SPARQL is W3C-standardized language for RDF querying. There were also proposed other RDF query languages.

  BTW, it is possible to query non-RDF sources with SPARQL, e. g. defining R2RML mappings.

• RDF self-descibeness and SPARQL standardness remove the need to create or to learn a new (shitty) API every day.

GraphQL

• Similar to SPARQL, GraphQL allows to avoid multiple requests.

• GraphQL allows to wrap different data sources of different kinds, but typically they are REST APIs.

  As you can see, it is possible to wrap a SPARQL endpoint (there also exists HyperGraphQL).

Why GraphQL

Why Datatourisme have preferred GraphQL?

• GraphQL is closer to developers and technologies they use en masse. In the past, JSON-LD had the same motivation (however, see my note about JSON-LD here).

• As it seems, Diffuseur's GraphQL layer provides API keys support and prevents too complex SPARQL queries.

Are data still semantic

• The answer depends on what you mean by semantic. There was an opinion that even relational model is quite semantical...

• I'd answer affirmatively, if it's possible to extract e. g. the comment to the :rcs property with GraphQL (and the answer seems to be negative).

Conclusion

Answering your direct question:

• it is not necessary (though possible) to create a semantic ontology first in order to use GraphQL;
• it is not necessary (though possible) to use GraphQL after creating a semantic ontology.

Answering your indirect question:

• probably you need a semantic ontology in order to build such chatbot;
• probably you need something else in addition.

See also: How is the knowledge represented in Siri – is it an ontology or something else?

Update

In addition to HyperGraphQL, there are other interesting convergence projects:

• in Stardog
• in Topbraid
• in Ontotext Platform