A Semantic Web Approach to Digital Rights

Management

Roberto García González

Table of Contents

• Introduction• DRM State of the Art• Objective• Knowledge

Representation• Semantic Web• Methodology

• Specification• Conceptualisation• Implementation• Evaluation• Conclusions• Future Work

Introduction

• Digital media DRM• Internet DRM interoperability• Need for a DRM standard• Internet/Web not standard friendly• Let standards “emerge”• Facilitate it concentrating discussion on

the roots, the semantics• Semantic Web, Web Ontologies• Copyright Ontology• Web Ontology Language (OWL)

implementation

DRM State of the Art

• Windows Media DRM, iTunes FairPlay,… • DRM Watch “2005 Year in Review: DRM

Standards” 1

– “…consumer complaints have moved beyond overly restrictive DRMs to lack of interoperability among them…”

– “…we see no production implementations…”

– “…ContentGuards’ asserts its patents apply to any rights expression language implementation in DRM…”

11 http://www.drmwatch.comhttp://www.drmwatch.com

DRM State of the Art

• Interoperable Rights Expression Language (REL)

• Efforts: MPEG-21, ODRL, CreativeCommons,…

• Syntax standardisation (grammar)• CC: limited, predefined licenses

DRM State of the Art

• Complex domain• Difficult to implement• Difficult to interoperate• REL patent• Just usage licenses• Detail level problems,

generalisation/specialisation

Objectives

• Rights expressions interoperability• Support copyright law• Model the whole copyright value chain• Work at the semantic level, more

expressivity, less ambiguity• Formalise domain knowledge• Facilitate interoperability and

implementation• In the Internet/Web

Knowledge Representation

• Knowledge is tacit

environment

system

control

facts

information

knowledge

flow WorldWorld'

predict

ActionSensation

PredictionRepresentation

measure

interpret decide

change

Knowledge Representation

• Social agents share knowledge– Limitations tacit knowledge exchange, e.g.

imitation– Make knowledge explicit

• Informally, more expressive, ambiguities

• Formally, enables automation• Formal Knowledge Representation:

– Logic: formal structure and rules of inference– Ontology: defines kinds of things in domain – Computation: automate computable models

Knowledge Representation

• Logic: – Syntax: grammar rules– Semantics: how tokens are related to things they

stand for– Inference: deduction

• Representational semantics: relate information to senses defined by ontologies

• Ontology: a formal machine readablespecification abstract modelof a shared based on consensusconceptualitzation in terms of concepts,

relations,...

Semantic Web

• Web + Knowledge Representation• RDF: semantic network, graph model• RDF Schema: classes, inheritance,…• Web Ontology Language (OWL)

– OWL-DL: based on DL, Semantic Networks formalisation, decidable and tractable, OWA.

Methodology

• Methontology• XML Semantics Reuse

Specification

Conceptualisation

Implementation

Evaluation

Conclusions

Future Work

Thank you for your attention

Roberto García González