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API v2 Design Overview

General Principles

  • DSP-API v2 requests and responses are RDF documents. Any API v2 response can be returned as JSON-LD, Turtle, or RDF/XML.
  • Each class or property used in a request or response has a definition in an ontology, which Knora can serve.
  • Response formats are reused for different requests whenever possible, to minimise the number of different response formats a client has to handle. For example, any request for one or more resources (such as a search result, or a request for one specific resource) returns a response in the same format.
  • Response size is limited by design. Large amounts of data must be retrieved by requesting small pages of data, one after the other.
  • Responses that provide data are distinct from responses that provide definitions (i.e. ontology entities). Data responses indicate which types are used, and the client can request information about these types separately.

API Schemas

The types used in the triplestore are not exposed directly in the API. Instead, they are mapped onto API 'schemas'. Two schemas are currently provided.

  • A complex schema, which is suitable both for reading and for editing data. The complex schema represents values primarily as complex objects.
  • A simple schema, which is suitable for reading data but not for editing it. The simple schema facilitates interoperability between DSP ontologies and non-DSP ontologies, since it represents values primarily as literals.

Each schema has its own type IRIs, which are derived from the ones used in the triplestore. For details of these different IRI formats, see Knora IRIs.


JSON-LD Parsing and Formatting

Each API response is represented by a class that extends KnoraResponseV2, which has a method toJsonLDDocument that specifies the target schema. It is currently up to each route to determine what the appropriate response schema should be. Some routes will support only one response schema. Others will allow the client to choose, and there will be one or more standard ways for the client to specify the desired response schema.

A route calls RouteUtilV2.runRdfRoute, passing a request message and a response schema. When RouteUtilV2 gets the response message from the responder, it calls toJsonLDDocument on it, specifying that schema. The response message returns a JsonLDDocument, which is a simple data structure that is then converted to Java objects and passed to the JSON-LD Java library for formatting. In general, toJsonLDDocument is implemented in two stages: first the object converts itself to the target schema, and then the resulting object is converted to a JsonLDDocument.

A route that receives JSON-LD requests should use JsonLDUtil.parseJsonLD to convert each request to a JsonLDDocument.

Generation of Other RDF Formats

RouteUtilV2.runRdfRoute implements HTTP content negotiation, and converts JSON-LD responses into Turtle or RDF/XML as appropriate.

Operation Wrappers

Whenever possible, the same data structures are used for input and output. Often more data is available in output than in input. For example, when a value is read from the triplestore, its IRI is available, but when it is being created, it does not yet have an IRI. In such cases, there is a class like ValueContentV2, which represents the data that is used both for input and for output. When a value is read, a ValueContentV2 is wrapped in a ReadValueV2, which additionally contains the value's IRI. When a value is created, it is wrapped in a CreateValueV2, which has the resource IRI and the property IRI, but not the value IRI.

A Read* wrapper can be wrapped in another Read* wrapper; for example, a ReadResourceV2 contains ReadValueV2 objects.

Each *Content* class should extend KnoraContentV2 and thus have a toOntologySchema method or converting itself between internal and external schemas, in either direction.

Each Read* wrapper class should have a method for converting itself to JSON-LD in a particular external schema. If the Read* wrapper is a KnoraResponseV2, this method is toJsonLDDocument.

Smart IRIs


The SmartIri trait can be used to parse and validate IRIs, and in particular for converting Knora type IRIs between internal and external schemas. It validates each IRI it parses. To use it, import the following:

import org.knora.webapi.messages.{SmartIri, StringFormatter}
import org.knora.webapi.messages.IriConversions._

Ensure that an implicit instance of StringFormatter is in scope:

implicit val stringFormatter: StringFormatter = StringFormatter.getGeneralInstance

Then, if iriStr is a string representing an IRI, you can can convert it to a SmartIri like this:

val iri: SmartIri = iriStr.toSmartIri

If the IRI came from a request, use this method to throw a specific exception if the IRI is invalid:

val iri: SmartIri = iriStr.toSmartIriWithErr(
    () => throw BadRequestException(s"Invalid IRI: $iriStr")

You can then use methods such as SmartIri.isKnoraApiV2EntityIri and SmartIri.getProjectCode to obtain information about the IRI. To convert it to another schema, call SmartIri.toOntologySchema. Converting a non-Knora IRI returns the same IRI.

If the IRI represents a Knora internal value class such as knora-base:TextValue, converting it to the ApiV2Simple schema will return the corresponding simplified type, such as xsd:string. But this conversion is not performed in the other direction (external to internal), since this would require knowledge of the context in which the IRI is being used.

The performance penalty for using a SmartIri instead of a string is very small. Instances are automatically cached once they are constructed. Parsing and caching a SmartIri instance takes about 10-20 µs, and retrieving a cached SmartIri takes about 1 µs.

There is no advantage to using SmartIri for data IRIs, since they are not schema-specific (and are not cached). If a data IRI has been received from a client request, it is better just to validate it using StringFormatter.validateAndEscapeIri.


The smart IRI implementation, SmartIriImpl, is nested in the StringFormatter class, because it uses Knora's hostname, which isn't available until the Akka ActorSystem has started. However, this means that the type of a SmartIriImpl instance is dependent on the instance of StringFormatter that constructed it. Therefore, instances of SmartIriImpl created by different instances of StringFormatter can't be compared directly.

There are in fact two instances of StringFormatter:

  • one returned by StringFormatter.getGeneralInstance which is available after Akka has started and has the API server's hostname (and can therefore provide SmartIri instances capable of parsing IRIs containing that hostname). This instance is used throughout the DSP-API server.
  • one returned by StringFormatter.getInstanceForConstantOntologies, which is available before Akka has started, and is used only by the hard-coded constant knora-api ontologies.

This is the reason for the existence of the SmartIri trait, which is a top-level definition and has its own equals and hashCode methods. Instances of SmartIri can thus be compared (e.g. to use them as unique keys in collections), regardless of which instance of StringFormatter created them.

Last update: January 19, 2023