MAINTAINING PROPERTY LIBRARIES IN PRODUCT

CLASSIFICATION SCHEMES

Joerg Leukel

Institute for Computer Science and Business Information Systems, University of Duisburg-Essen, Essen, Germany

Keywords: B2B e-commerce, product data, product ontologies, standardization.

Abstract: Semantic interoperability in B2B e-commerce can be achieved by committing to a product ontology that

establishes a shared and common understanding of a product domain. This issue is mainly subject of

standard product classification schemes. Recently, considerable research and industry work has been carried

out on enhancing the semantic richness of these schemes. Providing specific property lists for each product

class can be seen as a step towards true product ontologies. Horizontal classification schemes, however,

often consist of more than 10,000 classes, several thousand properties, and an even greater number of class-

property relations. Given the new requirement towards property-centric classification, maintaining these

business vocabularies is mainly determined by strategies for managing the property definitions and their

relationships to classes. This paper proposes measures for coping with the problem of extensive and steadily

growing property libraries. It can be shown that implementing these measures greatly influences both

standards makers and standards adopters.

1 INTRODUCTION

Executing business processes between independent

organizations faces often heterogeneity concerning

process models, data sources, software systems, and

available meta data describing these components.

Automating such processes increases the need for

aligning heterogeneities and finding consensus about

common concepts. Ontologies aim at fulfilling this

role by establishing a shared and common

understanding of a domain. In B2B e-commerce,

most processes incorporate essential information

about products (and services) being the subject of

procurement and sales respectively. Therefore, the

development of product ontologies can be regarded

as an enabler of machine-readable, unambiguous

representations of information about products

(Fensel et al., 2001) (Leukel, 2004).

A number of industry consortia and standards

bodies have proposed such domain ontologies called

standard product classification schemes (standard

PCS). Applying these business vocabularies benefits

searching for products in e-catalogs, comparing

similar products, standardizing product descriptions,

and facilitates spend analysis and product-sensitive

workflows (CEN/ISSS, 2005). Prominent horizontal

standards, such as eCl@ss, eOTD and UNSPSC

consist of 20,000 up to 60,000 product classes, and

represent a huge amount of knowledge about the

categorization of products.

For standards makers, the broad coverage of

horizontal standards leads to an enormous amount of

properties as new subjects of standardization

including proposal, negotiation, definition, and

maintenance. Taking in mind the distributed nature

of many standardization processes (e.g., work

groups for each sub-domain or branch of industry),

reducing or avoiding redundant properties becomes

an important task. For instance, work groups should

always check carefully the appropriateness of

existing properties before proposing a new property

for the vocabulary. This basic principle does not

affect the underlying model, but the standardization

process. It requires, however, that properties are

reusable. Reusability of properties depends on their

semantic precision, naming issues (i.e. synonyms,

homonyms), and the conflict between wide or

narrow definitions.

For standards adopters, properties must be seen

from a different perspective. Classification based on

a standard PCS requires (1) assigning each product

to a class and (2) describing each product with class-

specific properties. This initial effort is time-

Leukel J. (2006).

MAINTAINING PROPERTY LIBRARIES IN PRODUCT CLASSIFICATION SCHEMES.

In Proceedings of the Eighth International Conference on Enterprise Information Systems - SAIC, pages 3-10

DOI: 10.5220/0002442600030010

 SciTePress

consuming and costing; it depends mainly on the

number of products and the number of properties per

class. In addition, it requires continuous efforts

triggered by new PCS versions (new product classes,

new properties, redefinition of classes and

properties).

This paper proposes measures for coping with

the problem of extensive and steadily growing

property libraries. Our contribution to research is

that we (i) introduce the still overseen problem of

property growth, (ii) provide a comprehensive set of

measures that address this problem, and (iii)

reconstruct the current state of standard PCS by

checking whether some of the measures are

implemented as of today.

The remainder of our paper is structured as

follows. Section 2 discusses related work, and shows

that extensive property libraries have rarely been the

subject of research. In Section 3, we describe the

main problem based on empirical observations. In

addition, we present the basic conceptual data model

of property-centric classification schemes, which

will be extended in the course of our work. In

Section 4, we define measures for coping with

property libraries, and describe their impact on the

problem. In Section 5, we discuss the measures by

summarizing the impacts, extending the basic

model, and reviewing selected standard PCS.

Finally, we draw conclusions and point to future

avenues of research (Section 6).

2 RELATED WORK

Related work to product classification schemes can

be found in several fields such as e-catalogs, product

data management, standardization, and ontology

engineering. Next, we provide an overview of

closely related work and outline their relevance to

the problems caused by extensive property libraries.

Early work on basic concepts of PCS presents

and evaluates standard PCS from a business

perspective. For instance, (Fairchild & Vuyst, 2002)

examined the role of standard PCS towards benefits

of spend analysis; properties are not necessary for

this business function.

Schulten et al. introduced product classification

as a reference domain for ontology engineering and

the Semantic Web, and called for concentrated

efforts to “design a generic model” for automated

mapping between two different PCS (Schulten et al.,

2001). Concerning product properties, the proposal

demonstrated the mapping problem between classes

only, but did not incorporate properties. Eventually,

the research prototypes in (Corcho & Gómez-Pérez,

2001) and (Beneventano et al., 2004) followed this

class-centered path.

Ng et al. described challenges in integrating

product schemes based on heterogeneous properties

(Ng, Yan & Lim, 2000). Property lists form schemas

that can be integrated by applying techniques from

database schema integration. Two interesting aspects

discussed by Ng et al. are shallowness (flat

structures, lists) and bushiness (clusters of a high

number of related properties). This database

approach is complemented and extended in (Bullig,

Schnadhorst & Wilkes, 2003), which analyzed

property mappings and practical issues in more

detail.

Leukel et al. proposed an XML-based exchange

format for PCS (Leukel, Schmitz & Dorloff, 2002).

Its contribution lies in identifying and defining data

elements and relationships, both being derived from

an empirical study of four standard PCS and three

XML e-business standards. The modeling of

properties is quite sophisticated and fulfills mainly

requirements of PCS adopters. Two measures for

supporting the “management and maintenance” of

property libraries – grouping and inheritance – are

described briefly.

Recently, the importance of properties as a

cornerstone of product classification has become

more evident. For instance, (Ondracek & Sander,

2003) argued on a “property based product

classification” from that multiple different

classification hierarchies for specific purposes can

be built, though they are based on common, thus

standardized properties. (Leukel, 2004) emphasized

the role of properties for providing additional

semantics to class hierarchies; properties are needed

to describe the scope of a class formally. (Kim et al.,

2004) developed a “semantic classification model”

based on properties in order to enable an in-depth

understanding of product classification. All this

work is in support of semantically rich PCS that

incorporate well-defined properties. The problems

caused by large property libraries are being overseen

though.

A first indication of problems related to

properties can be found in (Hepp, 2004). The

proposed quantitative measurements for PCS reveal

some shortcomings in property lists and can help

detect duplicate properties. In its conclusion, the

paper argues on the need for further work on

maintaining properties and organizing property

libraries. A comprehensive quantitative analysis of

classes and properties in PCS is subject of (Hepp,

Leukel & Schmitz, 2005). In addition, (Ondracek &

ICEIS 2006 - SOFTWARE AGENTS AND INTERNET COMPUTING

Sander, 2003) drew attention to the problem of

redundant properties in huge property libraries, and

claimed that separating definition and application of

properties would be “the only solution”.

3 PROPERTY-CENTRIC

PRODUCT CLASSIFICATION

In recent years, considerable industry efforts have

been undertaken to extend the semantic richness of

product classes by adding class-specific property

lists. A property list contains all properties that

should be used to describe products belonging to the

respective class. These lists greatly enhance the

formal precision of standard PCS by replacing class

labels with a structured, though human-language

description of its meaning. From an ontology

perspective, property lists can be regarded as a first

step towards true product ontologies, since they

provide standardized representations of product

concepts, thus machine-readable semantics (Hepp,

2005). Taking in mind the already huge number of

product classes, adding property lists is not only a

resource-intensive project, but it may also cause new

problems for both standards makers and standards

adopters. We refer to these problems as of property

growth.

3.1 Observations

Property growth can be assessed by comparing

multiple versions of the same standard PCS. Next,

we present some data for eCl@ss, a horizontal PCS

being developed by a consortium of mainly German

companies since the late 1990s (eCl@ss e. V.,

2004). It has gained a significant relevance for e-

procurement in many European countries. Table 1

shows basic figures for four versions of eCl@ss.

The number of classes and class-property

relations has tremendously increased (107% and

492%). The increase of properties, however, is not

constantly over time (significant decline in version

5.0). We can assume that eCl@ss has already

performed some actions to limit redundancy by

reorganizing the property library, although, the sheer

number of property remains high (140% increase in

version 5.1 compared to version 4.0).

Table 1: Classes and Properties in eCl@ss.

eCl@ss

4.0

eCl@ss

4.1

eCl@ss

5.0

eCl@ss

5.1

Publication

Date

Aug

2001

Sep

2002

Dec

2003

Sep

2004

Classes

(4th Level)

10,190 12,565 20,379 21,100

Properties 2,303 5,504 3,667 5,525

Class-Prop.

Relations

68,244 303,511 406,482 403,859

Looking closer at eCl@ss (table 2), we observe

that (i) property lists are added to more and more

classes, (ii) most property lists contain at least 30

properties (V5.0: 83% of all property lists; V4.1:

maximum of 294 properties!), and (iii) the recent

version has led to a decrease in number of properties

per class as indicated by the mean.

Table 2: Property Lists in eCl@ss.

eCl@ss

4.0

eCl@ss

4.1

eCl@ss

5.0

eCl@ss

5.1

Classes with

Property Lists

1,107

(10.9%)

6,507

(51.8%)

7,913

(38.8%)

10,930

(51.8%)

Properties per

Class: Minimum

66 3 1

Properties per

Class: Maximum

89 294 266 156

Properties per

Class: Mean

20.6 42.0 43.5 32.3

Properties per

Class: Derivation

10.3 16.7 13.3 15.2

The growing number of property lists and

properties per class causes significant classification

costs, thus calls for property-centric classification

strategies for PCS adopters (i.e. suppliers, buyers,

marketplaces). Moreover, we have to consider that

in most industries multiple standard PCS are

relevant, especially due to the competition between

major horizontal standards. Each standard PCS

defines its own classes, properties and property lists.

Therefore, the problem of property growth is

multiplied by the number of standard PCS.

3.2 Basic Model

Product classes are the core components of each

PCS. A product class is a categorization, collection

or type of similar products that share a set of

characteristics (e.g., the class “laptop” describes

portable computers). Product characteristics are

expressed by properties (e.g., CPU type, display

MAINTAINING PROPERTY LIBRARIES IN PRODUCT CLASSIFICATION SCHEMES

size, weight). Properties are not limited to a single

class, but should be reusable. While some properties

represent information that can be captured by

standard data types (e.g., string, integer, float,

Boolean), other properties limit the allowed values

to a specific list of values (e.g., color “red”, “green”,

“blue” etc.). In conceptual modeling, the definition

of enumerated domains can be expressed by a

tertiary relation between product class, property and

value as it is shown in figure 1. This data model

introduces elementary attributes for each entity type.

For instance, a property consists of its identification,

name, textual definition, data type, and unit of

measurement (UOM, e.g., meters, kilogram, and

volt). Similar models are used in (Bullig,

Schnadhorst & Wilkes, 2003), (Leukel, Schmitz &

Dorloff, 2002), and (Ondracek & Sander, 2003).

Property

PID

Name

Definition

UOM

Data Type

has_domain

VID

Name

Value

CID

Name

…

has_subclass

Keyword

is_synonym_for

Product

Class

KID

Name

described_by

Figure 1: Basic conceptual model.

The major drawback of this model can be

illustrated by a simple example: In industry segment

A, which is represented by a number of classes, the

property “length” is measured in inches, while

industry segment B – being represented by other

product classes of the same sub-tree – measures the

very same property in meters (e.g., hand tools vs.

pipes for gas transportation). Consequently, two

properties must be defined; their specification is

nearly equal and differs only in UOM. This is

especially for horizontal PCS, which cover a broad

range of industry segments, a common problem. It

can be solved by increasing the reusability of

properties, though this may require modifications of

the model.

4 MEASURES

In this Section, we define a comprehensive set of

measures that can be taken by standards makers. We

describe the rationale and, if necessary, point out to

extensions of the basic model. In addition, we assess

the impact of each measure on the given problem.

There are “two sides to every story” – standards

must be developed and maintained, and standards

should be applied; otherwise they are no standards.

The effect on standards makers concerns changes in

initial efforts (i.e., setting up the PCS) and

maintenance efforts (i.e., processing change

requests, releasing new versions). Similarly, the

effect on standards adopters refers to the initial

classification process and following re-classification

processes. However, an often overlooked aspect of

PCS adoption is the GUI presentation and actual

usage in applications such as e-procurement,

marketplaces, and product data management

systems. These issues will be considered, too.

4.1 Maximum Number of Properties

Rationale: The number of properties per class is

limited to a fix number (e.g., 15); this limitation

applies to all property lists, thus to the entire PCS. It

prevents property growth locally, especially with

regard to product segments in which product

descriptions can be very detailed. This measure does

not modify the basic model, but adds a constraint on

the cardinality of the class-property relation.

Standards makers:

The implementation of this

measure requires making a single decision on the

maximum number. Eventually, the size of the

property library is limited as well (only by the

number of classes and the reuse of existing

properties). There is even a significant change in

maintenance efforts, since adding a new property to

a property list is not possible if the maximum

number has already been reached.

Standards adopters:

Both the classification and

re-classification efforts are reduced and can be

forecasted. The GUI representation is improved due

to lower space requirements and may fit on a single

screen in all cases (e.g., imagine the list of 294

properties compared to the reduced list of the 15

most important properties).

4.2 Optional Properties

Rationale: Properties are distinguished whether their

usage is optional or mandatory. This distinction aims

at reducing the number of essential properties that

have to be used for product description, while it does

not remove properties from property lists. The

number of optional and mandatory properties

ICEIS 2006 - SOFTWARE AGENTS AND INTERNET COMPUTING

depends on the product class; for instance, all

properties may be optional, or mandatory (min/max-

approach). This measure adds a new attribute

“mandatory” to the class-property relation.

Standards makers: For each property of each

property list, the question of mandatory or optional

has to be answered. This initial effort can be reduced

by setting all properties to optional followed by

searching for the most important, thus mandatory

properties. Because of product innovation, optional

properties may be shifted to mandatory and vice-

versa (maintenance effort).

Standards adopters:

Depending on the share of

optional properties, the classification effort is

reduced. This measure allows diverse classification

strategies, i.e. support only mandatory properties.

Adopters decide on supporting optional properties,

especially if these are required by their customers.

Moreover, there are two consequences on GUI

representation: (i) optional properties can be marked,

thus separated from mandatory properties, and (ii)

parametric, property-based search for products has

to be restricted to mandatory properties.

4.3 Naming Conventions

Rationale: The name of a property must adhere to

specific naming conventions in order to prevent

redundant properties (e.g., “diameter, max.” vs.

“maximum diameter” vs. “max. diam.”). This

measure addresses the problem of finding the right

property in the property library, in addition to

keywords. Types of conventions: prefix vs. postfix

qualifiers, singular vs. plural, use of abbreviations,

separation of UOM from property name (e.g.,

“diameter” instead of “diameter in mm”). This

measure does not modify the basic model.

Standards makers:

Initially, naming conventions

must be developed, and applied to all property

names. Additional property names to the harmonized

name can be stored in the keyword list. Applying

these conventions can reveal redundant properties

that should be removed from the property library.

Standards adopters:

The classification process is

not directly affected; searching for the right property

is slightly improved. Since the naming can be used

to build logical groups of properties, the GUI

representation of large property lists is improved.

For instance, postfixes to property names (e.g.,

“length, max.”, “length, min.”) express a

specialization of closely related properties.

4.4 Property Groups

Rationale: Each property belongs to a predefined

group (e.g., design, dimensions, shape, and business

properties). This categorization eases the handling of

huge property lists, since the flat list is transformed

into a hierarchical structure. The basic model has to

be modified: define a list of groups, and add a N:1

relation between property group to property.

Standards makers:

Implementing this measure

requires defining non-overlapping groups and

assigning each property of the property library to

one group. The maintenance effort is slightly

effected (assign each new property to one group).

The subdivision of the property library helps

overlooking all properties, though it does not affect

the total number of properties.

Standards adopters:

Similarly to naming

conventions, this measure does not influence the

classification process. In the same way, it improves

the GUI representation by explicitly defined groups

of similar properties.

4.5 Views on Property Lists

Rationale: Instead of defining a single

comprehensive property list, define overlapping

views on property lists for each stage of the product

life-cycle. The rationale is that the relevance of a

property depends mainly on the product life-cycle

and the respective business function of product data.

For instance, the requirements of spend analysis

differ from those of engineering. In consequence,

each view-specific property list can be reduced to

purely relevant properties. Eventually, the class-

property relation must be modified to reflect the

view.

Standards makers:

Views on property lists result

in multiple, overlapping property lists for the same

product class; hence the initial and maintenance

efforts are considerably higher. While the number of

properties in those lists is reduced because of

including only view-relevant properties, the total

number of properties in the property library remains

unchanged.

Standards adopters:

Due to strictly view-relevant

properties, the efforts for classification can be

reduced in those cases where not all product

lifecycle phases are relevant. Often, standard PCS

are only used for procurement or sales and not for

intra-organizational purposes; therefore, this benefit

is quite relevant. In addition, the GUI representation

no longer contains non-relevant properties.

MAINTAINING PROPERTY LIBRARIES IN PRODUCT CLASSIFICATION SCHEMES

4.6 Property Templates

Rationale: Instead of defining properties completely,

the property library contains templates only. These

generic properties can be used for multiple specific

purposes by concretizing the template. This concept

is very similar to separating property definition and

property application as described in (Ondracek &

Sander, 2003). For instance, the template includes

name and definition, while the concretization adds

data type and UOM. Regarding the basic model, the

class-property relation is extended by further

attributes that were formerly part of the property

entity type.

Standards makers:

The first step for

implementing this measure is deciding which

attributes still belong to the generic property and

which attributes belong to the class-specific

property, thus to the class-property relation.

Eventually, a rather small number of generic

properties needs to be defined from which more

specific properties can be instantiated. Concerning

maintenance, adding a new property can often be

based on a similar, already existing property (i.e.,

concretizing the generic property instead of defining

the new property completely).

Standards adopters:

This measure does not

influence the classification process nor does it

improve the GUI representation. The reason is that

property templates concern only the organization of

the property library.

4.7 Property Inheritance

Rationale: So far, all measures were directed at

properties only. Considering that properties are

assigned to product classes forming a class

hierarchy, property inheritance says that properties

are inherited to all lower classes. Moreover, an

inherited property can be modified (concretized) on

lower levels. This measure does affect the basic

model as follows: the class-property relation as well

as the class-property-value relation is available for

all classes, not only for leaves of the class tree.

Standards makers:

Setting up a PCS based on

property inheritance calls for thoroughly defined

properties that can be assigned to nodes of the class

tree; otherwise the benefits of inheritance will not be

realized. Moreover, the class hierarchy itself has to

be suitable for assigning properties that are common

for complete sub-trees. Maintaining such a PCS

requires fewer efforts, since the property library

contains lesser properties and sub-trees truly

represent similar product classes characterized by a

set of common properties.

Standards adopters:

Similarly to property

templates, this measure concerns the property library

only.

5 DISCUSSION

In this Section, we discuss the proposed measures by

summarizing the expected effects, modifying the

basic model, and checking selected standard PCS to

which degree they take care of property growth.

5.1 Summarization of Effects

Next, we compile the previously assessed effects of

each measure on the problem of property growth

(see table 3). For both standards makers and

adopters, we state expected changes regarding initial

and maintenance efforts (“-“ for decrease; “+” for

increase, “o” for no change). Effects on the total

number of properties and GUI representation are

further criteria of our assessment (“reduced” and

“improved” respectively).

Comparing the effects on standards makers and

adopters, we have to state that 6 out of 7 measures

increase the initial effort for standards makers, while

classification efforts are reduced or remain

unchanged; a reduction of the number of properties

can be expected for four measures, while the GUI

representation is improved by five measures.

5.2 Modification of the Basic Model

Since the proposed measures concern the definition

Table 3: Effects on Standards Makers and Standards Adopters.

Measure Initial Effort Maintenance

Effort

Number of

Pro

erties

Initial Effort Maintenance

Effort

GUI

Maximum Numbe

- - reduced - - improved

tional Pro

erties

+oo - oimproved

Namin

Conventions

+ o reduced o o improved

Pro

ert

Grou

+ooooimproved

iews on Pro

ert

Lists

++o - -improved

Pro

ert

Tem

lates

+ - reduced o o o

Pro

ert

Inheritance

+ - reduced o o o

Standards Makers Standards Adopters

ICEIS 2006 - SOFTWARE AGENTS AND INTERNET COMPUTING

of single properties being elements of a property

library, the basic model for PCS needs to be

modified. Therefore, we collect the modifications

described before and alter the basic model as shown

in Figure 2. The modifications include (i) adding one

new attribute (mandatory), (ii) adding two new

entity types (property group, view), (iii) redefining

one relationship (described_by), and (iv) moving

attributes from the property entity type to the

described_by relationship (here: data type, uom).

Property

PID

Name

Definition

described_by

Mandatory

Data Type

UOM

View

VID

Name

has_domain

VID

Name

Value

CID

Name

…

has_subclass

Property

Group

belongs_to

Keyword

is_synonym_for

Product

Class

KID

Name

Figure 2: Modified conceptual model.

5.3 Evaluation of Selected Standards

By analyzing existing standard PCS whether they

implement at least some of the proposed measures,

we reconstruct the current state of standard PCS

concerning the problem. We select five PCS for this

purpose: the two most important horizontal

standards (eCl@ss and EGAS; the latter adds

property lists to UNSPSC), and three vertical

standards (RNTD covers electronic and IT

components; ETIM and proficl@ss are vertical

European initiatives). For basic information on these

and many other schemes see (CEN/ISSS, 2004).

Table 4 shows the results of our evaluation.

We have to state that the coverage is quite little.

eCl@ss, which is often regarded as a thoroughly

developed PCS, implements one single measure

only: property groups by referring to a

categorization described in the IEC 61360 standard.

While no standard implements all measures, both

horizontal standards fall behind the vertical

standards. Naming conventions are provided and

followed by proficl@ss and RNTD, while the other

schemes do not describe conventions. However, due

to some of the actual property names it is probable

that implicit conventions exist (‘No’ in brackets

represents this). The support of the three most

sophisticated measures – views, templates, and

inheritance – is even lower with inheritance being

not implemented at all.

6 CONCLUSIONS

The main contribution of our paper lies in proposing

new measures for coping with the problem of

extensive and steadily growing property libraries

being prime examples of real-world business

vocabularies. The assessment of the impact on

standards makers and standards adopters revealed

that the effects concern not only the total number of

properties, but also initial efforts, maintenance

efforts, and GUI representation issues. Therefore,

decisions on implementing these measures should

bear in mind all these criteria. The results of the

assessment as well as the modified model may serve

standards makers in their decision process on

reorganizing property libraries.

The quantitative analysis (see Section 3.1) of the

property library in eCl@ss has drawn attention to the

problem of defining, maintaining and actually using

huge sets of product properties. While this quite

elaborated standard PCS claims to be unique in its

property-centered approach, the conceptual model of

its property library is rather simple. We conclude

that eCl@ss still focuses on semantic richness (i.e.

extending the coverage of industry segments) rather

than formal precision and efficient maintenance.

This example, nevertheless, underlines the need for

re-thinking the current organization of property

libraries, since measures tackling the described

problems are at hand, their impact can be predicted,

and some of the proposed measures have already

been tested in vertical standards.

Considering recent developments in finding

Table 4: Evaluation of Standard Product Classification Schemes.

Measure eCl

ss EGAS ETIM

roficl

ss RNTD

Maximum Number

No No No No No

tional Pro

erties

No No No Yes No

Namin

Conventions

(No) (No) (No) Yes Yes

Propert

Groups

Yes Yes No No No

iews on Propert

Lists

No No No No Yes

Propert

Templates

No No Yes Yes No

Propert

Inheritance

No No No No No

MAINTAINING PROPERTY LIBRARIES IN PRODUCT CLASSIFICATION SCHEMES

consensus about the basic components, underlying

conceptual models as well as maintenance policies

of PCS, standards bodies and industry consortia

have joined efforts in harmonizing their proprietary

approaches in several initiatives and on different

levels of obligation. For instance, the CEN project

on product classification (CEN/ISSS, 2005) states

that a “good” PCS necessarily incorporates

properties and property lists. Standard PCS that are

purely based on classes are expected to add

properties in order to broaden the range of

application and to provide extended semantics.

Concerning the current state of standard PCS,

these transformation processes will be quite

demanding. From this point of view, we plan future

work on validating the measures by quantitative

analysis of standard PCS, thus reengineering their

property libraries based on automated conversion,

and developing transformation strategies for

standards makers. Another field of interest derives

from the role and suitability of reference models for

PCS. These models will become more important

since many standard PCS aim at converting their

proprietary data models to the ISO 13584 standard

(ISO, 2001). This standard requires some

modifications to the property library, though it does

not address the maintenance problem explicitly as

described in this paper, since its main purpose is to

achieve semantic interoperability between different

property libraries. Therefore, we see the need for

extending the scope of this reference model to

content management issues that greatly determine

the costs and efforts of defining and implementing

respective standard PCS.

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