GraphQL in Sante for mulang

Purpose

To develop a specification that uses URIs in GraphQL

Initial Study

After analyzing the content of both pages, here are the main differences between the GraphQL-LD approach by Comunica and the GraphQL approach by Stardog:

1. Query Language and Data Source:

   • Comunica's GraphQL-LD uses GraphQL as a query language for Linked Data, which means it queries data that is structured using RDF (Resource Description Framework). It uses JSON-LD (JSON for Linking Data) context to interpret the GraphQL queries.
   • Stardog's GraphQL, on the other hand, is a query language specifically designed for their database. It allows users to query data stored in a Stardog database using GraphQL.

2. Implementation:

   • Comunica's GraphQL-LD is a client-side approach. It translates GraphQL queries to SPARQL (a query language for RDF) before executing them against any SPARQL endpoint.
   • Stardog's GraphQL is a server-side approach. It translates GraphQL queries into SPARQL queries internally within the Stardog database.

3. Use of Context:

   • In GraphQL-LD, the JSON-LD context plays a crucial role. It provides the semantics for the GraphQL queries, allowing the system to understand the meaning of the terms used in the query.
   • In Stardog's GraphQL, the context is defined by the database schema. The schema provides the structure and types for the data, which guides the formation of the GraphQL queries.

4. Flexibility:

   • Comunica's GraphQL-LD is designed to be flexible and adaptable. It can query multiple heterogeneous data sources at the same time.
   • Stardog's GraphQL is more rigid in terms of data sources. It is designed to work specifically with data stored in a Stardog database.

5. Target Users:

   • GraphQL-LD is aimed at developers who want to query Linked Data using GraphQL without needing to understand SPARQL or RDF.
   • Stardog's GraphQL is aimed at users of the Stardog database who want to use GraphQL as a query language.

While both approaches use GraphQL, they target different use cases and data sources. GraphQL-LD is more about querying Linked Data using GraphQL, while Stardog's GraphQL is about using GraphQL to query a Stardog database.

Here are some similarities between the GraphQL-LD approach by Comunica and the GraphQL approach by Stardog:

1. Use of GraphQL: Both approaches use GraphQL as the query language. GraphQL is a powerful query language for APIs and a runtime for executing those queries with our existing data.

2. Translation to SPARQL: Both systems translate GraphQL queries into SPARQL, a query language for RDF. This allows them to leverage the power and flexibility of SPARQL while providing a simpler and more intuitive query interface through GraphQL.

3. Schema-Based: Both approaches are schema-based. In GraphQL-LD, the schema is provided by the JSON-LD context, while in Stardog's GraphQL, it's provided by the database schema. In both cases, the schema provides the structure and types for the data, guiding the formation of the GraphQL queries.

4. Data Retrieval: Both systems are designed to retrieve data from databases or data sources based on the GraphQL queries. They provide a structured and efficient way to fetch data.

5. Targeted at Developers: Both GraphQL-LD and Stardog's GraphQL are designed with developers in mind, providing tools and interfaces that make it easier to query and manipulate data.

6. Semantic Web Technologies: Both approaches leverage Semantic Web technologies. GraphQL-LD uses JSON-LD for linking data, while Stardog's GraphQL operates on data stored in a Stardog database, which supports RDF and other Semantic Web standards.

While they have different implementations and target different use cases, both GraphQL-LD and Stardog's GraphQL share a common foundation in GraphQL and Semantic Web technologies. They both aim to make it easier and more efficient to query and retrieve data.

Synopsis of the Purpose

This specification assumes that we're using GraphQL to query a database or API that supports URIs as identifiers for resources.

To use URIs in GraphQL in a Java Spring Boot application, we would typically define a GraphQL schema that includes fields for the URIs, and then implement resolvers that fetch the data associated with those URIs. Here's a basic example of how we might do this:

1. Add Dependencies: First, we need to add the necessary dependencies to our pom.xml file. we'll need graphql-spring-boot-starter, graphql-java-tools, and spring-boot-starter-web.

<dependencies>
    <!-- other dependencies -->

    <dependency>
        <groupId>com.graphql-java</groupId>
        <artifactId>graphql-spring-boot-starter</artifactId>
        <version>latest_version</version>
    </dependency>
    <dependency>
        <groupId>com.graphql-java</groupId>
        <artifactId>graphql-java-tools</artifactId>
        <version>latest_version</version>
    </dependency>
    <dependency>
        <groupId>org.springframework.boot</groupId>
        <artifactId>spring-boot-starter-web</artifactId>
    </dependency>
</dependencies>

2. Define GraphQL Schema: Next, define our GraphQL schema. This schema defines the structure of our data and the operations that clients can perform. In this case, we might have a URI type with fields for the URI itself and any other data we want to associate with it. Here's an example schema (schema.graphqls):

type Query {
    uri(id: ID!): URI
}

type URI {
    id: ID!
    uri: String!
    description: String
}

3. Implement Resolvers: Now we need to implement the resolvers that fetch the data for our URIs. In Spring Boot, we would typically do this by creating a @Component that implements GraphQLQueryResolver (for queries) and/or GraphQLMutationResolver (for mutations). Here's an example:

@Component
public class URIQueryResolver implements GraphQLQueryResolver {
    private URIService uriService;

    public URIQueryResolver(URIService uriService) {
        this.uriService = uriService;
    }

    public URI getUri(String id) {
        return uriService.getUri(id);
    }
}

In this example, URIService is a Spring service that fetches URI objects from our data source. we would need to implement this service ourself based on our specific data source and requirements.

4. Start the Server: Finally, we can start our Spring Boot server and it will automatically start a GraphQL server at /graphql on the same port. we can then send GraphQL queries to this endpoint to fetch our URIs.

Please note that this is a very basic example. Depending on our specific requirements, we might need to add more types to our schema, implement more complex resolvers, handle errors, etc. Also, remember to replace latest_version with the actual version of the dependencies.

Experimental Study

Query merge of the approaches by Comunica's GraphQL-LD and Stardog's GraphQL.

This query uses GraphQL's syntax, but also includes JSON-LD context via the @config directive, which is similar to how Comunica's GraphQL-LD approach works. The context provides the semantics for the GraphQL query, allowing the system to understand the meaning of the terms used in the query.

Sample query:

query withContext @config(context: {"name": "http://www.w3.org/2000/01/rdf-schema#label",
     "Human": "http://dbpedia.org/ontology/Person"}) 
{
 Human {
    name
  }
}

Here's a breakdown of our query:

• withContext @config(context: {"name": "http://www.w3.org/2000/01/rdf-schema#label", "Human": "http://dbpedia.org/ontology/Person"}): This part of the query sets the JSON-LD context. It maps the term "name" to the RDF property rdfs:label, and the term "Human" to the RDF class dbpedia:Person.

• Human { name }: This part of the query is standard GraphQL syntax. It requests all "Human" resources (which, according to the context, are resources of type dbpedia:Person), and for each one, it requests the "name" property (which, according to the context, is the rdfs:label property).

This type of query would allow we to use GraphQL to query Linked Data, similar to Comunica's GraphQL-LD approach, while also being compatible with a GraphQL server like Stardog's, assuming the server supports the @config directive or a similar mechanism for providing JSON-LD context.

However, please note that the actual implementation would depend on the specific capabilities of our GraphQL server and our data source. Not all GraphQL servers support directives like @config, and not all data sources support RDF or JSON-LD.

Adding a parameter to a GraphQL query that doesn't exist in the GraphQL schema

In GraphQL, we can't add parameters that are not defined in the schema. The schema defines the structure of the data, the types of data that can be queried, and the parameters that can be used in those queries.

Probable solution is that we would need to modify the GraphQL schema to include that parameter. This would typically involve updating the server-side code that defines the schema, and possibly also the resolver functions that handle the queries.

In a Spring Boot application like Santé using GraphQL, we would define our schema in a .graphqls file and our resolvers in Java classes. Here's how we might update our schema and resolvers to add a query argument to the resource field.

1. Update the Schema: Create a .graphqls file (if we haven't already) and define our schema there. For example:

type Query {
  resource(type: String!, query: String!, orderBy: String, limit: Int): [Resource]
}

type Resource {
  name: String
}

2. Update the Resolver: Create a Java class to serve as the resolver for our resource field. This class should have a method that corresponds to the resource field and takes the necessary arguments. Here's an example:

import com.coxautodev.graphql.tools.GraphQLQueryResolver;
import org.springframework.stereotype.Component;

@Component
public class Query implements GraphQLQueryResolver {

    public Resource resource(String type, String query, String orderBy, Integer limit) {
        // Fetch the data based on the arguments. This is just a placeholder,
        // replace it with our actual data fetching logic.
        Resource data = fetchData(type, query, orderBy, limit);

        return data;
    }

    // Placeholder for our data fetching logic.
    private Resource fetchData(String type, String query, String orderBy, Integer limit) {
        // Implement our data fetching logic here.
        // For now, we'll just return a new Resource.
        return new Resource("Resource Name");
    }
}

In this example, Resource is a Java class that represents the Resource type in our GraphQL schema. We would need to define this class in our code, for example:

public class Resource {
    private String name;

    public Resource(String name) {
        this.name = name;
    }

    public String getName() {
        return name;
    }
}

3. Test our Changes: After updating the schema and resolvers, we should test our changes to make sure everything works as expected. We can do this by running our Spring Boot application and sending GraphQL queries to it. We can use tools like GraphiQL or Apollo Studio for this.

4. Deploy our Changes: Once we're confident that our changes work correctly, we can deploy our updated server code. The exact steps for this will depend on our deployment environment.

Including a Search Field in the Query

In GraphQL, the structure of the query determines the structure of the response. If you want to include a search field in your query that takes a query argument, you would need to define this in your schema and implement a corresponding resolver.

Here's an example of how you might define this in your schema:

type Query {
  search(query: String!): [Person]
}

type Person {
  name: String
  friends: [Person]
}

In this schema, the search field takes a query argument and returns a list of Person objects. Each Person has a name and a list of friends.

Here's an example of how you might implement a resolver for this in a Spring Boot application:

import com.coxautodev.graphql.tools.GraphQLQueryResolver;
import org.springframework.stereotype.Component;

@Component
public class Query implements GraphQLQueryResolver {

    public List<Person> search(String query) {
        // Fetch the data based on the query. This is just a placeholder,
        // replace it with your actual data fetching logic.
        List<Person> data = fetchData(query);

        return data;
    }

    // Placeholder for your data fetching logic.
    private List<Person> fetchData(String query) {
        // Implement your data fetching logic here.
        // For now, we'll just return a list with a single Person.
        Person person = new Person("Wilhuff Tarkin", Arrays.asList(new Person("Darth Vader", new ArrayList<>())));
        return Arrays.asList(person);
    }
}

In this example, Person is a Java class that represents the Person type in your GraphQL schema. You would need to define this class in your code, for example:

public class Person {
    private String name;
    private List<Person> friends;

    public Person(String name, List<Person> friends) {
        this.name = name;
        this.friends = friends;
    }

    public String getName() {
        return name;
    }

    public List<Person> getFriends() {
        return friends;
    }
}

With this setup, you could send a query like this:

{
  search(query: "my query") {
    name
    friends {
      name
    }
  }
}

And get a response like this:

{
  "data": {
    "search": [
      {
        "name": "Wilhuff Tarkin",
        "friends": [
          {
            "name": "Darth Vader"
          }
        ]
      }
    ]
  }
}