An Ontology for the Expression of Intellectual Property

Entities and Relations

Víctor Rodríguez

, Marc Gauvin

and Jaime Delgado

DMAG (Distributed Multimedia Applications Group)

Universitat Pompeu Fabra, Passeig de Circumval•lació, 8, 08003 Barcelona, Spain

Universitat Politècnica de Catalunya, Jordi Girona, 1-3, 08034 Barcelona, Spain

NetPortedItems, S.L.

Abstract. Ontologies represent knowledge in a particular area. Intellectual

Property (IP) Entities lifecycle lacks any explicit standard representation, and a

semantic expression of its processes and rules would report a series of benefits.

To formalise the expression of IP Entities and their relations, an Ontology Web

Language (OWL) ontology is proposed to establish a common framework

where the different interested parties can interact. As a demonstration, a sample

application based on the ontology is described, where a central reasoning server

receives qualified statements and queries over the ontology, giving the perti-

nent logical results.

1 Introduction

The word “ontology” comes from an ancient Greek word related to “being”. But be-

ing itself is an imprecise term. Webster’s dictionary defines two different meanings

for the verb “to be”. The first use is to give a name a predicate and the second is to

express existence. Thus, in one sense we can use the verb “to be” to attribute a prop-

erty to include a subject in a category or to express equivalence between two subjects;

in another sense, we can use it to assert the existence of a certain subject. Ontologies,

in the context of computer science, are also related to these two concepts and allow us

to represent both abstract models and their existing exemplars.

A model in an ontology is the explicit expression of the knowledge of a particular

domain. It represents a set of concepts as classes, their attributes, the relationships

between the classes and their restrictions. And although having a logical representa-

tion of a data model is by itself useful regardless the existence of individuals, ontolo-

gies exhibit fully their potential when they also express real beings as class instances

of the ontology.

In this paper, we present an ontology for representing the domain of Intellectual

Property (IP) Entities defined as the set of unique artistic and/or intellectual creations

and their manifestations, adaptations and subsequent stylistic instantiations.

Within this domain, a minimum set of actors (roles) are required to generate inde-

pendent (i.e. original works) or dependent IP Entities such that the relationship be-

Rodríguez V., Gauvin M. and Delgado J. (2007).

An Ontology for the Expression of Intellectual Property Entities and Relations.

In Proceedings of the 5th International Workshop on Security in Information Systems, pages 196-203

DOI: 10.5220/0002430101960203

 SciTePress

tween the different classes of actors are direct corollaries of the interdependence be-

tween the IP Entities created by them. A set of rights over actions that may be per-

formed on or with IP Entities may be attributed to other roles by the original rights

owner. These actions may create new dependant IP Entities whose rights transfer can

be performed along the value chain by virtue of provenance alone. Thus, the formal-

ised semantic expression of the relationships based on natural dependencies for using

and generating IP Entities provides a solid and common basis for computer based

inferring and reasoning about individuals of the different classes (IP Entities, roles

and rights).

In this sense, the model intends to be universal by focussing first on the notion of

an origin IP Entity called the original work and then the fundamental relationships

required for generating IP Entities dependent on the original work. For example, the

issue of how Intellectual Property is remunerated can vary substantially from country

to country but any system that supports IP, will necessarily support these fundamental

relationships if for nothing else to accurately attribute IP Entities to the appropriate

individuals (irrespective of economic or moral compensation). Precisely in this way,

the model herein is extendable to and interoperable with different specialisations of

IP Entity systems in the Semantic Web world based on ownership of original works

determined by provenance of their manifestations. This represents the key result and

benefit of expressing such knowledge in a standard machine readable way.

To show the benefits of using a semantic expression of the IP model, a small ap-

plication is also described, where IP Entities and actors are represented as individuals

of the Ontology.

After reviewing previous work in the field, this paper will first provide a descrip-

tion of an Intellectual Property model, then its expression as an Ontology and finally

a demonstrator application will be described.

2 State of the art

Digital Rights Management (DRM) systems were intended for managing IPR (Intel-

lectual Property Rights) in the digital world. The corresponding standards provide

means to represent actions related to rights, but only at a syntactic level. The most

extended DRM standards usually formalise XML schemas that define rights expres-

sion languages (REL), like MPEG-21 REL [1] or ODRL [2]. Some REL terms are

sometimes defined in a separate dictionary such as in the Rights Data Dictionary

(RDD) [3], but in this case the definition is a short description only for the human

comprehension. What this paper promotes is another approach where both the seman-

tics and the syntax are modelled in an Ontology so that computers may understand

and make use of the meanings that are expressed within the model..

This is not the first initiative in this field. There are other semantic representations

that cover the terms we deal with, and there are general purpose ontologies of legal

terms [4], but they do not include all the subtle details of an integral IP model. A first

formal effort was IPROnto [5], specifically aimed at describing a general model for

IPR. Other efforts include the formalisation of the MPEG 21 RDD (called RDDOnto

[6]). Yet another, OREL [7], proposes an alternate Rights Expression Language based

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also on an OWL Ontology aimed at replacing MPEG-21 REL licenses, and another

work [8] in a similar approach is based on making inferences over a MPEG-21 REL

model with CLIPS. Finally, the DMP Creation Model was specified with the intent to

express a minimum and sufficient set of uses and dependencies of and between IP

Entities common to any system where the ownership of original works are determined

by their provenance.

The work we present here, is less elaborate than IPROnto in that it does not intend

to express several related fields at once such as both genesis and legal treatment of IP

Entities. Also, it is not linked to any upper ontology such as SUMO [9]. Experience

has shown that overly complex Ontologies are difficult to manage in terms of main-

taining both consistency as per available machine based reasoners and corresponding

human understanding of the relationships between concepts. These relationships need

to be agreed to in order for the model to be trusted in its implementation. In this way,

a basic set of easily agreed principles can be extended to include any number of sce-

narios that adhere to the same core set of underlying precepts.

3 The Intellectual Property Entity Model

The scope of the model includes any setting where individuals generate original IP

and subsequent derived IP and that can be represented digitally. The basic chain of

actions in the IP value chain whereby different related IP Entities are generated is

similar to the one proposed by the Digital Media Project (DMP) [10], as follows:

original concept or idea, material manifestation, adaptation, reproduction and distri-

bution to others interested in enjoying it. In each of the steps new unique IP Entities

are made and can be classified as follows:

− Work: An original abstract idea that can be uniquely attributable.

− Adaptation. A work that is based on another work.

− Manifestation. The tangible physical expression of a work such as a musical score,

manuscript or event that can be recorded.

− Instance. A particular execution or rendition of a manifestation.

− Copy. A copy of an instance or a manifestation, equal to other copies.

− Product. A collection of one or more copies ready to be distributed.

The individuals that act on these basic IP Entities can be classified according to a

set of generic roles that can be adopted by an agent i.e. a person or group thereof who

incarnates one or more roles. The list of roles are:

− Creator. The author of the work, who translates his idea into a material realization.

− Adaptor: The creator of an adaptation from a work.

− Instantiator. An agent who executes a performance or rendition of the work.

− Producer. An agent who compiles commercial distributable products.

− Distributor. An agent who distributes the product.

− End User. The last agent to use the content.

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Work Manifestation Instance Product

Creator

Instantiator

Makes manifestation

Makes instance

Producer

Makes product

Distributor

Distibutes

End User

Create work

Fig. 1. Value IP Entity Value Chain and roles.

The creator has full rights over the work, and can trade with these rights. Each role

represents a set of actions that can be attributed to any agent capable of performing

those actions (i.e. a distributor can distribute products), but in order to have the right

to execute actions associated with roles, agents need the required authorisation (i.e.

the distributor can distribute a particular product if and only if he is authorised to do

so). Furthermore, the actions that can be performed on or with the IP Entities can be

grouped into:

− Actions that generate new independent and dependent IP Entities: create, adapt,

make manifestation, make instance, make product..

− Actions required to use IP Entities , like the act of “playing” a song etc.

Rights may be transferred with exclusivity or not, and some may be resold or not.

The Creator may retain rights, and the execution of certain actions require his ap-

proval through transfer of the corresponding rights. In many cases not all of the roles

intervene, and the requirements for the transfer of rights may differ, but these differ-

ences should be capable of being expressed as particular specialization of the model

implemented as extensions. Although this present design of the ontology does not

consider the representation of conditions imposed on the execution of the rights (as

RELs usually do), conditions could be the basis for possible future extensions.

4 Intellectual Property Entity Ontology

The mere fact of expressing a model with a set of logical statements requires a precise

analysis that is by itself beneficial for the understanding of the problem. The result of

the analysis is a set of ontology classes, their attributes and the relations between

them; a description of an ontology is described therefore as a hierarchical list of

classes and relations.

OWL (Ontology Web Language) has been chosen as the particular Ontology lan-

guage as it is becoming the standard in the Semantic Web. OWL is built on top of

RDF [11] which in turn is XML based and its simplicity is kept containing only a set

of sentences expressed as triples with the form “subject – predicate - object”.

Mapping a class for each of the concepts in the previous sections, we have the fol-

lowing classes:

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Table 1. Main classes of the ontology.

Root classes Subclasses

IP Entities Work, Adaptation, Manifestation, Instance, Copy, Product

Roles Creator, Adaptor, Instantiator, Producer, Distributor, EndUser

Actions TransformingActions (adapt, perform, etc.), ConsumeRights (play

etc)

Auxiliary classes

Each of the above classes have a set of attributes describing the concept. For ex-

ample, each role has a creation date and time attribute, a reference code attribute so

they can be associated with external databases etc. Several auxiliary classes are also

defined. They are aimed at facilitating the expression of complex sentences, for ex-

ample, the class Authorisation is defined, which contains the proper relations of an

authorisation: who gives the permission, to whom, over which item and to do what.

More important are the relations that join the concepts. A relation binds two re-

sources (that can be classes), and for each relation a domain and a range can be de-

fined. A domain is the set of possible classes where the relation can be applied, and a

range is the set of possible values of a relation relator. The next table shows the main

relations in the ontology.

Table 2. Ontology relations.

Relation Domain Range

ResultsIn TransfomingAction IPEntity

ComesFrom IPEntity IPEntity

RequiresAuthorisationFrom Action Role

CanExercise Role Action

CanApply Action IPEntity

− ResultsIn. Maps TransformingActions into IPEntities, stating the resulting IP En-

tity after applying a certain transforming action. For example, there is a relation

“ResultsIn” that binds Adapt (subclass of TransformingAction) with Adaptation.

− RequiresAuthorisationFrom. This object property maps Actions to Roles, and says

for an action, which roles must authorise the execution of the right

− ComesFrom. Maps IPEntities to IPEntities, stating the IP Entity upon which an-

other depends for its genesis

− CanExercise. States regardless of authorizations, which Actions can be performed

by which roles. Not all roles can perform all actions, for example, an EndUser can

execute the right called play (providing t it has permissions), but cannot make an

adaptation as this is not a task proper of its role.

− CanApply. States which Actions can or cannot be applied over a given IP Entity.

For example, a Work cannot be Played.

Apart from the above, there are a number of relations that impose logical restric-

tions. There are some exclusivity relations (an individual of the ontology can not be

Action and Role at the same time, but can play different roles at the same time), and

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cardinality relations i.e every Work has one and only one Creator etc. (an abstract

creator can be an individual or a group).

5 A Sample Application

What we have seen in the previous sections becomes interesting in the context of

practical applications. The ontology is the main asset we present, but as a complement

and to show its utility, the description of a practical system implementation follows.

The application is in the form of a logical validator which determines if a given

agent can exercise a particular right over a particular IP Entity. The application con-

sists of a central server which receives sentences expressing facts and queries over IP

Entities; and its answers will be the logical result of the received expressions.

Central Validator

Bob´s computer

Bob is a Creator

Bob creates

OntoSong.mp3

Bob gives Alice right

to Adapt OntoSong.mp3

Alice´s computer

Alice is an Adaptor

Query

-- May I Adapt OntoSong.mp3?

-- Authorised

Fig. 2. Schema of a simple application.

As can be seen in Figure 2, a Central Validator receives assertions like “Bob is a

Creator”, and “Bob Creates OntoSong.mp3”, and queries of the kind: “May Alice

adapt OntoSong.mp3?” which in turn are answered according to the logical result of

the previously introduced knowledge.

Externally it takes the form of a web application, where the central server offers a

site where users can log in once authenticated. Each of the remote clients (like Bob or

Alice) can issue assertions valid within their domain. That is to say, Bob cannot say

“Alice created a song”, but he can create a new composition.

The composition of these assertions is facilitated by an easy to use web interface,

but what is actually sent over the network is one or more OWL triples (RDF triples),

which the Central Validator stores. The queries are translated in turn into an

SPARQL [12] expressions, a specific query language for RDF.

The Central Validator contains the rules of the model as an OWL file, and addi-

tionally stores the incoming sentences in a database. The triples in an RDF model can

be easily kept in a single SQL table with 3 columns, therefore all RDF operations are

inherently implementable as SQL operations and thus the system retains simplicity.

Storage of data in the form of Ontology individuals does not compete with other ad-

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hoc relational databases in efficiency or security but information structure is known

to everybody and reasoning can be directly performed over these expressions.

The Central Validator has a core module able to parse, read and store all the OWL

triples, and reason over them. Many middleware platforms facilitate these tasks, and

our particular choice points at a Java based system, which makes use of the Jena [13]

and Pellet [14] libraries. These libraries are intended for the former to read and parse

OWL triples and the later to perform the first order logical inferences. These are par-

ticular choices of minor interest, because the Ontology is given in XML, a platform

that is technologically neutral. On top of these libraries, an API with a set of functions

is defined. The API has already been programmed and submitted to the DMP.

OWL IP Ontology

Pellet + Jena

API Functions Set

WebService server

Central Validator

WebService client

Web Interface

Client

IP Model

Individuals

database

Fig. 3. Architecture model of the application.

The communication between the Central Validator and the clients is carried out

with Web Services. The server parses the OWL triples that it receives and checks

their validity before adding them to the knowledge store, and accepts queries under

two forms: as functions belonging to a set of predefined calls in an API, and as free

SPARQL queries. The client thus makes no triple processing at all, keeping a light

client interface. Figure 3 shows the architecture structure of the application.

6 Conclusions

An Ontology was presented for describing an Intellectual Property model. Objects

referred to as IP Entities were represented along the value chain, as well as the actors

that play roles over them. The expression of the model was achieved using an Ontol-

ogy Web Language whose short description was also given. A practical application

was described in order to support the comprehension of the proposed model.

The authors believe that based on the natural inter-dependence between IP Entities,

roles and subsequent rights upon which both business and legal rules must depend on,

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expression of a corresponding Ontology using the standard Semantic Web Language

is necessary to provide the required machine readable expressivity. Furthermore, a

world where digital communication of original works and subsequent IP Entities re-

quires trusted machine based management of the associated relationships between

roles, further attests to the importance of such an effort.

This work, in response to a call for technology, has been accepted by the Digital

Media Project, for its inclusion in the Interoperable DRM Platform (IDP) specifica-

tion as of v.2.1. [12].

Acknowledgements

This work has been partly supported by NetPortedItems S.L. (CMOnto Project), the

Spanish Administration (DRM-MM project, TSI 2005-05277) and the FP6 Network

of Excellence VISNET-II.

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