rdf-canonize

rdf-canonize

An implementation of the RDF Dataset Canonicalization specification in JavaScript.

Introduction

See the RDF Dataset Canonicalization specification for details on the specification and algorithm this library implements.

Installation

Node.js + npm

npm install rdf-canonize

const canonize = require('rdf-canonize');

Node.js + npm + native bindings

This package has support for rdf-canonize-native. This package can be useful if your application requires doing many canonizing operations asynchronously in parallel or in the background. It is highly recommended that you understand your requirements and benchmark using JavaScript vs native bindings. The native bindings add overhead and the JavaScript implementation may be faster with modern runtimes.

The native bindings are not installed by default and must be explicitly installed.

npm install rdf-canonize
npm install rdf-canonize-native

Note that the native code is not automatically used. To use the native bindings you must have them installed and set the useNative option to true.

const canonize = require('rdf-canonize');

Browser + npm

Install in your project with npm and use your favorite browser bundler tool.

Examples

// canonize a dataset with the default algorithm

const dataset = [
  // ...
];
const canonical = await canonize.canonize(dataset, {algorithm: 'RDFC-1.0'});

// parse and canonize N-Quads with the default algorithm

const nquads = "...";
const canonical = await canonize.canonize(nquads, {
  algorithm: 'RDFC-1.0',
  inputFormat: 'application/n-quads'
});

Using with React Native

Using this library with React Native requires a polyfill such as data-integrity-rn to be imported before this library:

import '@digitalcredentials/data-integrity-rn'
import * as canonize from 'rdf-canonize'

The polyfill needs to provide the following globals:

• crypto.subtle
• TextEncoder

Algorithm Support

• "RDFC-1.0": Supported.
  • Primary algorithm in the RDF Dataset Canonicalization specification.
• "URDNA2015": Deprecated and supported as an alias for "RDFC-1.0".
  • Former algorithm name that evolved into "RDFC-1.0".
  • NOTE: There are minor differences in the canonical N-Quads form that could cause canonical output differences in some cases. See the 4.0.0 changelog or code for details. If strict "URDNA2015" support is required, use a 3.x version of this library.
  • See the migration section below if you have code that uses the "URDNA2015" algorithm name.
• "URGNA2012": No longer supported.
  • Older algorithm with significant differences from newer algorithms.
  • Use older versions of this library if support is needed.

URDNA2015 Migration

• The deprecated "URDNA2015" algorithm name is currently supported as an alias for "RDFC-1.0".
• There is a minor difference that could cause compatibility issues. It is considered an edge case that will not be an issue in practice. See above for details.
• Two tools are currently provided to help transition to "RDFC-1.0":
  • If the API option rejectURDNA2015 is truthy, it will cause an error to be thrown if "URDNA2015" is used.
  • If the global RDF_CANONIZE_TRACE_URDNA2015 is truthy, it will cause console.trace() to be called when "URDNA2015" is used. This is designed for development use only to find where "URDNA2015" is being used. It could be very verbose.

Complexity Control

Inputs may vary in complexity and some inputs may use more computational resources than desired. There also exists a class of inputs that are sometimes referred to as "poison" graphs. These are structured or designed specifically to be difficult to process but often do not provide any useful purpose.

Signals

The canonize API accepts an AbortSignal as the signal parameter that can be used to control processing of computationally difficult inputs. signal is not set by default. It can be used in a number of ways:

• Abort processing manually with AbortController.abort()
• Abort processing after a timeout with AbortSignal.timeout()
• Abort after any other desired condition with a custom AbortSignal. This could track memory pressure or system load.
• A combination of conditions with an aggregated AbortSignal such as with AbortSignal.any() or signals.

For performance reasons this signal is only checked periodically during processing and is not immediate.

Limits

The canonize API has parameters to limit how many times the blank node deep comparison algorithm can be run to assign blank node labels before throwing an error. It is designed to control exponential growth related to the number of blank nodes. Graphs without blank nodes, and those with simple blank nodes will not run the algorithms that use this parameter. Those with more complex deeply connected blank nodes can result in significant time complexity which these parameters can control.

The canonize API has the following parameters to control limits:

• maxWorkFactor: Used to calculate a maximum number of deep iterations based on the number of non-unique blank nodes.
  • 0: Deep inspection disallowed.
  • 1: Limit deep iterations to O(n). (default)
  • 2: Limit deep iterations to O(n^2).
  • 3: Limit deep iterations to O(n^3). Values at this level or higher will allow processing of complex "poison" graphs but may take significant amounts of computational resources.
  • Infinity: No limitation.
• maxDeepIterations: The exact number of deep iterations. This parameter is for specialized use cases and use of maxWorkFactor is recommended. Defaults to Infinity and any other value will override maxWorkFactor.

Usage

In practice, callers must balance system load, concurrent processing, expected input size and complexity, and other factors to determine which complexity controls to use. This library defaults to a maxWorkFactor of 1 and no timeout signal. These can be adjusted as needed.

Related Modules

• jsonld.js: An implementation of the JSON-LD specification.

Tests

This library includes a sample testing utility which may be used to verify that changes to the processor maintain the correct output.

The test suite is included in an external repository:

https://github.com/w3c/rdf-canon

This should be a sibling directory of the rdf-canonize directory or in a test-suites directory. To clone shallow copies into the test-suites directory you can use the following:

npm run fetch-test-suite

Node.js tests:

npm test

Browser tests via Karma:

npm run test-karma

If you installed the test suites elsewhere, or wish to run other tests, use the TEST_DIR environment var:

TEST_DIR="/tmp/tests" npm test

To generate EARL reports:

# generate a JSON-LD EARL report with Node.js
EARL=earl-node.jsonld npm test

# generate a Turtle EARL report with Node.js
EARL=js-rdf-canonize-earl.ttl npm test

# generate official Turtle EARL report with Node.js
# turns ASYNC on and SYNC and WEBCRYPTO off
EARL_OFFICIAL=true EARL=js-rdf-canonize-earl.ttl npm test

Benchmark

See docs in the benchmark README.

Source

The source code for this library is available at:

https://github.com/digitalbazaar/rdf-canonize

Commercial Support

Commercial support for this library is available upon request from Digital Bazaar: [e-mail]