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0.3.5 • Public • Published

The Linked data Integration Toolkit (LIT) for JavaScript

This Linked data Integration Toolkit (LIT) is intended to contain a number of libraries, that collectively make up the LIT for multiple programming languages, initially Java and JavaScript. This broad toolkit is intended to be used by developers working with RDF.


A very simple library that provides JavaScript objects that represent the individual terms (i.e. the classes and properties) defined in RDF vocabularies (both existing vocabularies (like http://schema.org, FOAF, VCard, LDP, ActivityStreams, etc.) and your own custom RDF vocabularies).

A major feature of this library is that it provides easy access to any rdfs:label or rdfs:comment values provided for these vocabulary terms, and provides very easy-to-use support for multi-lingual values for these labels and comments (and generic message strings).


The demo directory provides an extremely basic working example that you can run with the following commands:

cd demo
npm install --registry=https://npm.pkg.github.com/inrupt
node index.js

For detailed examples going beyond the common usages featured here, please see the demonstration test suite.

The lit-vocab-term library is distributed as a Github NPM packages: @inrupt/lit-vocab-term For more information about Github NPM packages, please visit the dedicated documentation.

NOTE: This library is used extensively by the LIT Artifact Generator project that can automatically generate source-code (in multiple programming languages, including JavaScript) that provides LIT Vocab Term instances for every term defined within any RDF vocabulary. Due to the ease of simply pointing the LIT Artifact Generator at any RDF vocabulary, and have it automatically generate all the LIT Vocab Term instances for you automatically, we don't expect manual instantiation of LIT Vocab Terms to be very common. However, this documentation describes the LIT Vocab Term library without any dependency or requirement to use the LIT Artifact Generator whatsoever.

RDF library support

The LIT Vocab Term objects from this library are intended to be simple wrappers around 'NamedNode' objects conforming to the RDFJS interface. This means that LIT Vocab Term instances can be used natively with libraries that are RDFJS-compliant, such as rdf-ext or rdflib.js. A LitVocabTerm may be built by passing an RDFJS Datafactory implemented with any library, but it also embeds a basic Datafactory implementation for simplicity.

Introductory example

For example, if we have the following simple RDF vocabulary defining a single Person term (in this case a Class):

@prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> .
@prefix ex:   <https://example.com#>

ex:Person a rdfs:Class ;
  rdfs:label "My Person class"@en ;
  rdfs:comment "Full description of my Person class..."@en .

We could represent this as a LIT Vocab Term in JavaScript like so:

const {LitVocabTerm, buildStore} = require('@inrupt/lit-vocab-term')
// Any other implementation of the RDFJS interfaces would also be appropriate.
const rdf = require('rdf-ext')

// The third argument provides as a context - it will commonly store things like the current
// language preference of the user, which can be used to lookup term labels or comments
// in that language. It's always there for browsers, but in NodeJS we expose a local 
// implementation accessible through the method `buildStore`, which returns either
// said local implementation or the browser store depending on the environment.
// The last parameter indicates whether we want a 'strict' behaviour or not
// (see below for an explanation).  
const person = new LitVocabTerm('https://example.com#Person', rdf, buildStore(), true)
  .addLabel('My Person class','en')
  .addComment('Full description of my Person class...','en')

We can use this LIT vocab term in various ways:

// To access the term's full IRI value:
const personIri = person.value

// The label and the comment are available as RDFJS RDFLiteral instances:
// - get the RDFLiteral object (which contains not just the text value, but also the 
// language tag of that text (e.g. 'en' for English, or 'es' for Spanish).
// The LIT can potentially offer further meta-data - such as a description of how the
// text was determined. For example if a user's current language preference (as stored
// in localStorage) was 'French', but our original RDF vocabulary didn't provide a
// French label (in which case the LIT vocab term will fallback to using an English
// label by default), then we can describe that behaviour in another field saying:
// "Current language is French, but only German, Spanish and English labels are available: using English",
// which can be extremely useful in a User Interface tooltip for instance):
const personLabel = person.label
const personComment = person.comment

// Get the term's label or comment as a simple string value:
const personLabelAsString = person.label.value
const personCommentAsString = person.comment.value

To use the emmbedded Datafactory implementation to build a LitVocabTerm, the previous example would become:

const {buildBasicTerm, buildStore} = require('@inrupt/lit-vocab-term')

const person = buildBasicTerm('https://example.com#Person', buildStore(), true)
  .addLabel('My Person class','en')
  .addComment('Full description of my Person class...','en')

NOTE: The lit-vocab-term library is implemented in TypeScript, and embeds its typing. The following snippet of code demonstrate a basic TypeScript usage:

import {buildBasicTerm, buildStore, LitVocabTerm} from '@inrupt/lit-vocab-term'

const person: LitVocabTerm = buildBasicTerm(
).addLabel('My Person class','en')
.addComment('Full description of my Person class...','en')


An important feature of the lit-vocab-term is support for parameterized messages. This can be extremely useful when defining your own RDF vocabularies and including message strings (thereby providing those message with globally unique IRI identifiers and allowing for easy translations of those messages). For instance, to report errors to the user with contextual information (and in multiple languages).

const term = new LitVocabTerm("https://test.com/vocab#Unauthorized", rdf, buildStore(), true)
    .addMessage('Your account ({{0}}), does not have sufficient credentials for this operation', 'en')
    .addMessage('Votre compte ({{0}}) ne dispose pas des informations d'identification suffisantes pour cette opération', 'fr')
term.messageParams('Current Account').value // Evaluates to "Your account (Current Account)..."


Unless we explicitly mandate a specific language, English will be used as the default language. Best practice for RDF vocabularies in general is to provide labels (short human readable descriptions) and comments (longer, more detailed descriptions), and to also provide these descriptions in multiple languages if appropriate and possible. (Technical note: the language tag defaults to an empty string in the case of fallback to the local part of the term's IRI (see the next section about strictness)).

const storage = buildStore()
const person = new LitVocabTerm('https://example.com#Person', rdf, storage, true)
  .addLabel('Personne', 'fr')
  .addLabel('Persona', 'es')

// Default to the English label (if there is one).
var personLabel = person.label

// Request an explicit language for the label (but if there isn't one, fallback to the
// English one, if there is one).
personLabel = person.asLanguage('fr').label

// Change the default language in our context (i.e. localStorage).
storage.setItem(LitContext.CONTEXT_KEY_LOCALE, 'es')

personLabel = person.label // personLabel now contains the Spanish literal.


The last parameter to the LIT Vocab Term constructor indicates if the behaviour of the term should be strict or loose. In the case of "loose" behaviour, in the absence of any label, term.label will default to the local part (i.e. the last segment of the path component) of the term's IRI. With "strict" behaviour it will return undefined. When the local part of the IRI is returned as a label the language tag will be empty (i.e. "").

// Here we specify 'loose' behaviour(i.e. 'false' parameter to constructor)...
var person = new LitVocabTerm('https://example.com#Person', rdf, buildStore(), false)

// 'personLabel' will default to an RDF literal with the value "Person", and an empty
// language tag (i.e. "").
var personLabel = person.labelLiteral 
// Now strict behaviour...
person = new LitVocabTerm('https://example.com#Person', rdf, buildStore(), true)
// personLabel will default to 'undefined'.
personLabel = person.labelLiteral

This behaviour (i.e. returning the local part of the IRI, or undefined) may be overridden to instead throw an error when no label is found by using the .mandatory accessor.

// Here 'strictness' has no impact...
const person = new LitVocabTerm('https://example.com#Person', rdf, buildStore(), true)

// An exception will be thrown here, because our term has no label.
const personLabel = person.mandatory.label 




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