OMOS: ONTOLOGY BASED INFORMATION MANAGEMENT

FOR ICT SOCIETIES

Antonio Oliveri, Patrizia Ribino, Salvatore Gaglio, Giuseppe Lo Re

Dipartimento di Ingegneria Informatica (DINFO), Universita’ degli Studi di Palermo, Palermo, Italy

Tonio Portuesi, Aurelio La Corte, Francesco Trapani

Sicilia e-Innovazione s.p.a., Italy

Keywords:

Knowledge management, Knowledge management systems, Ontology, Software reuse, Rule-base processing.

Abstract:

Over the last few years, several projects for the development of innovative systems capable of collecting and

sharing information have been carried out, following the increasing companies’ interest on a correct knowledge

management. ICT companies’ managers have realized that knowledge and its management, more than the

mere data, constitute fundamental part of their activities. This paper proposes a Knowledge Management

System whose main feature is an underlying ontological knowledge representation. This data representation

allows the specialization of the reasoning capabilities and the provision of ad hoc behaviors. The system has

been designed for the management of projects and processes and has been tested using data coming from

projects and processes typical of government ICT companies, providing a Document Management System

and an Expert System to share documents and to plan how to best use ﬁrms’ knowledge.

1 INTRODUCTION

Nowadays most companies work in complex applica-

tion contexts which create huge amounts of informa-

tion. Organizations are constantly searching for new

solutions to adapt to new conditions in order to sur-

vive in increasingly competitive environments. It ap-

pears very useful for companies to have awareness of

their own information, contained in documents, en-

terprise processes, acquired experiences and so on.

The great amounts of data impose the adoption of

new computer-based information systems which en-

able the storage of structured data and the automation

of the information-processing activities of the orga-

nization. Enterprise Knowledge Management, a new

research area, classiﬁes knowledge as a company as-

set and studies methods and computer technologies to

increase its value, reuse and access. Recent studies

have drawn attention to problems related to knowl-

edge capitalization and management (Staab et al.,

2001),(O’Leary, 1998). During the last two decades

ad-hoc frameworks known as Knowledge Manage-

ment Systems (KMS) have been proposed, enabling

access and coordination of knowledge assets (Alavi

and Leidner, 2005). KMSs represent information sys-

tems which manage organizational knowledge with

the purpose of increasing the productivity of knowl-

edge operators. This paper is the product of a col-

laboration between the Computer Engineering De-

partment of Palermo University and the Sicilian lo-

cal Government ICT society Sicilia e-Innovazione. It

proposes an ontology-based knowledge management

framework capable of modeling the government of-

ﬁces structure and the ICT company’s projects, dis-

covering processes to be automatized and projects to

be reused or developed ad hoc. The system we present

is a KMS consisting of an expert system for decision

support and a document management engine. The

main goal of this work is the development of a sys-

tem for managing data and information that exploits a

new approach with a separation between knowledge

representation and knowledge management, so that

change in the infrastructure of concepts in the knowl-

edge base, done by the expert of the domain, does not

inﬂuence the inference mechanisms and logical rea-

soning processes.

The paper is structured as follows: section 2 provides

a vision of the state of the art of KMSs and expert

systems; in section 3 we introduce essential aspects

of KMSs, Expert Systems for decision support and

318

Oliveri A., Ribino P., Gaglio S., Lo Re G., Portuesi T., La Corte A. and Trapani F. (2009).

KROMOS: ONTOLOGY BASED INFORMATION MANAGEMENT FOR ICT SOCIETIES.

In Proceedings of the 4th International Conference on Software and Data Technologies, pages 318-325

DOI: 10.5220/0002254903180325

 SciTePress

Ontologies; in section 4 we present a detailed descrip-

tion of the system; section 5 illustrates the Document

Management Service of the KMS; section 6 presents

our case study. Finally, in section 7, we reach some

conclusions.

2 STATE OF THE ART

The challenge of KMS developers is to create a sys-

tem of tools to collect, organize, and share common

data, documents and individuals’ expertise. Research

has examined different aspects of the problem, study-

ing novel knowledge representation models and in-

volving modern AI techniques to extract new knowl-

edge.

In the last few years, the most important ICT com-

panies have demonstrated an increasing interest in

the development of internal knowledge management

instruments, many of them based on web corporate

portals. A case of a web and ontology-based KMS

in a company is the United Nations Food and Agri-

culture Organization’s WAICENT (World Agriculture

Information Centre). This platform makes FAO’s

knowledge about food security and agricultural de-

velopment widely available to users, with a decision-

support systems to improve food security through in-

formation use and a document management system

allowing people around the world to read and use

FAO’s documentation (O’Leary, 2008).

L. Razmerita et al. in (Razmerita et al., 2003) pro-

posed a KMS based on the ontological model of

the user proﬁle, representing characteristics such as

users’ preferences, competencies and so on, adopting

semantic web techniques. Many other KMSs in liter-

ature are designed and customized to satisfy the needs

of speciﬁc ﬁrms. Liping Sui in (Sui, 2005) studied the

beneﬁts of a decision support system within the busi-

ness management. D.J. Harvey and R.Holdsworth in

(Harvey and Holdsworth, 2005) observed the advan-

tage of using a KMS in the aerospace industry. An in-

teresting study conducted by Chun, Sohn and Grana-

dos in (Chun et al., 2008), shows the use of a Knowl-

edge Management System in an industrial engineer-

ing company. Through observation of the company’s

requests, they identiﬁed the features of a KMS which

were necessary in order for it to be considered a good

investment for the ﬁrm.

In this article we introduce a prototypal KMS applied

to a real case. Exploiting the advantages of the repre-

sentation of domain concepts through ontologies, two

knowledge management mechanisms have been im-

plemented, one related to efﬁcient document manage-

ment and the other concerning decisional problems

facing efﬁcient government.

3 OVERVIEW

3.1 Knowledge Management Systems

Knowledge Management (KM) consists of a tech-

nique that uses Information Technology tools for the

management of information, making knowledge ex-

plicit and sharing a ﬁrm’s professional expertises and

informative resources. A Knowledge Management

Systems, supporting the storage of knowledge, cre-

ates the opportunity to make information and knowl-

edge from different sources readily available. KMSs

contain both explicit and tacit knowledge. Explicit

knowledge, more familiar and easily written down,

includes data stored in documents. KMSs can also

store tacit knowledge, which is more difﬁcult to ex-

press, and includes people’s experiences, know-how

and expertise. The issue of how to better capitalize

and disseminate tacit knowledge is one of the actual

priorities in Knowledge Management. To realize such

goals, a KMS can make use of different technologies

such as:

a. Document based: for the creation, administration

and sharing of different documents, managing the

explicit knowledge.

b. Ontology/Taxonomy based: using ontologies

and classiﬁcation for knowledge representation.

Knowledge concepts are arranged in hierarchi-

cal structures, typically related by relationships.

Such methodologies act on both explicit and tacit

knowledge.

c. AI based: using particular inference engines to re-

solve peculiar domain problems, they generally

manipulates tacit knowledge (g.e. Knowledge-

base system).

3.2 Ontologies and Knowledge-based

Systems

In computer science the use of the term ”ontology”

means the study of the ”being”, the fundamental cat-

egories of which it is composed and the relation-

ships among them to formulate an exhaustive and rig-

orous conceptual scheme of a particular application

domain. Generally it is represented through a hier-

archical structure which contains all the noteworthy

entities, the existing relationships between them, the

rules, the axioms and the speciﬁc domain constraints.

Knowledge-Based Systems (KBS), a class of AI sys-

tems, are able to represent speciﬁc domain knowledge

KROMOS: ONTOLOGY BASED INFORMATION MANAGEMENT FOR ICT SOCIETIES

319

and apply it for solving problems through inference

processes. A particular subclass of KBSs is the rule-

based expert system, in which knowledge is captured

into a set of rules, each encoding a small piece of the

expert’s skills. Each rule is an ”if-then” statement. An

expert system emulates the domain expert in the same

conditions.

4 KNOWLEDGE MANAGEMENT

FOR DECISION SUPPORT:

KROMOS

In this paper we present Kromos, a KMS prototype

developed through the partnership between the Com-

puter Science Department (Dinfo) of Palermo Univer-

sity and an ICT company of the Sicilian government

which deals with the automation of government of-

ﬁce processes. Kromos is an ontology-based system

of knowledge management with the aim of optimiz-

ing business processes for creating and managing ICT

projects for government ofﬁces. To achieve this, Kro-

mos implements a system of document management

and an expert system for decision support.

Developer

Interface

User Interface

Knowledge Management

Document

management

Knowledge Base

Users

Knowledge engineer

Inference

engine

Document Repository

Kromos Ontologies

Ontology Editor

Domain Expert

Domain Ontology

Project Ontology

Figure 1: System architecture.

The knowledge representation is based on two on-

tological domain models, the former reproducing the

government ofﬁces’ structure and the latter modeling

the concepts of projects developed by the ICT com-

pany. The main idea is the separation between knowl-

edge representation and knowledge reasoning, so that

the same infrastructure of rules can be used adopting

different knowledge bases. The proposed system was

designed with the following features: speciﬁc domain

knowledge by building a knowledge base, reasoning

ability performed by a rule-based expert system, and

ﬁnally advanced techniques of document and infor-

mation retrieval. Figure 1 shows the system architec-

ture. The core of the architecture is the Knowledge

Management component, while the data level is com-

posed of a repository to store documents and a KB to

maintain domain information. All the components are

now presented in detail.

4.1 User Interface

The proposed system implements the typical client-

server paradigm using JSP and Java servlets (Avedal

et al., 2000). With a graphical interface the users

can select different application areas. The system is

divided in three different macro-areas: PA, Process

and Project managements. The ﬁrst allows the user

to manage information about government ofﬁces and

interacts with domain ontology. The second enables

the user to organize new processes in activities that

can be potentially automated. The ﬁrst two areas in-

volve more ontology domain formalization and build-

ing processes; the third allows the Project Manager

(PM) to access the system functionalities. Using that

area the user can create complex queries for the Ex-

pert System.

4.2 Knowledge Base

The Knowledge Base of Kromos represents the

knowledge container. KB relations and concepts are

described using an ontological structure of instances

in order to collect and manage data. The rationale be-

hind the Kromos ontology is to provide a minimal but

sufﬁcient ontology, suitable for application-domain

purpose. Ontologies of the proposed system are per-

formed through Frames (Minsky, 1974) and built us-

ing Prot

e, a free and open source platform devel-

oped by Stanford University, that supports frame-

based ontologies according to the Open Knowledge

Base Connectivity Protocol (OKBC)(Chaudhri et al.,

1998).

In a frame-based model, an ontology is composed by:

• a set of classes, hierarchically organized to de-

scribe the domain concepts;

• a set of slots for the classes, which describes prop-

erties and relations between concepts;

• a set of class instances, examples of concept with

their speciﬁc values and properties.

The use of such an ontological model transforms ab-

stract concepts into logical descriptions.

4.2.1 Kromos Ontologies

Modeling knowledge about the government ofﬁces

world required some assumptions about its structure

ICSOFT 2009 - 4th International Conference on Software and Data Technologies

320

and activities, as well as about the nature of the

”observer” expected to use, understand, and rely

on the model. Our ontology was designed from

scratch for the Kromos KMS and can be considered

a collection of two correlated ontologies, a domain

ontology and a projects ontology; in order to keep

the ontology easy to understand, only a few concepts

from the government ofﬁces’ domain and from com-

puter engineering projects are collected. This results

in a simpliﬁed description of Projects, Processes

and Structure of government ofﬁces and a group of

details, attributes and relations.

INTERDEPARTMENTAL

AREA

FUNCTIONALITY

MANAGER

STRUCTURE

MANAGER

PROJECT

MANAGER

AREAS

AREA

ACTIVITY

SERVICE

DISTRICT

COUNCIL

DEPARTMENT

Figure 2: Domain ontology of the Kromos platform.

The Domain Ontology, a formal representation of

the government ofﬁces structure and activities is used

to characterize the environment in which the system

works, and is organized as a set of concepts and rela-

tions allowing deduction of new knowledge; it repro-

duces the logical architecture of government ofﬁces

arranged in levels, each depending on the previous in

a pyramidal organization (ﬁg. 2).

REQUIREMENT

MANAGER

STRUCTURE

MANAGER

PROJECT

MANAGER

PROJECT

SERVICE

HARDWARE

REQUIREMENT

PROJECT

SOFTWARE

REQUIREMENT

PROJECT

FUNDING

Figure 3: Project ontology of the Kromos platform.

The Project Ontology is useful to describe ICT

company projects; it maps the structure of the

project components containing semi-structured ex-

plicit knowledge. During the execution of queries,

each component of this ontology is used to get all the

elements of the domain in agreement with the query

(ﬁg.3).

4.3 Decision Support System

The main goal of an Expert System (ES) for decision

support is to assist employees during their activities,

ﬁnding solutions that usually need the intervention of

speciﬁcally skilled people. The goal is to incorpo-

rate implicit knowledge about the speciﬁc ﬁeld in a

computational model. The ES prototype implemented

for the Kromos platform is a rule-based system devel-

oped in Jess (Java Expert System Shell) (Hill, 2003),

that can be used for reasoning in different knowledge

base contents, adapting rules to different kinds of do-

mains. It provides rule-based programming suitable

for automating an expert system, and is often referred

to as an expert system shell. Rather than a procedu-

ral paradigm, where a single program has a loop that

is activated only once, the declarative paradigm used

by Jess matches a rule with a single fact speciﬁed as

its input and processes that fact as its output. When

the program is run, the rules engine will activate one

rule for each matching fact. The ES exploits two dif-

ferent kinds of knowledge: declarative facts, captured

by the ontological model, and procedural facts, ex-

pressed using rules deﬁned by an expert.

Use cases: Use cases in which our ES can offer

support are decisional processes such as:

a) Project planning process - During planning of

company projects there are many different con-

straints to be considered in order to improve en-

terprise yields and avoid wasting resources. Plan-

ning is a process for the deﬁnition of a future goal,

the activities to exploit in order to reach that ob-

jective, and all the resources to be used to com-

plete these activities. The planning process has to

identify business components directly connected

to the real progress of business activities, measur-

ing their impact and connected beneﬁts, and to an-

alyze the investment policy, producing a Business

Plan, as ﬁgure 4 shows.

RESOURCES

PRIORITY

IMPACT

BENEFIT

FUNDING

PLANNING CONDITIONS

BUSINESS

PLAN

Figure 4: Use case a: Project planning process.

b) Project management process - Supervision of the

state and progress of projects. This process guides

the business management to the attainment of pre-

viously planned objectives, showing the differ-

KROMOS: ONTOLOGY BASED INFORMATION MANAGEMENT FOR ICT SOCIETIES

321

ences between them and the results obtained, so

that managers can decide and actuate appropri-

ate corrective actions. For instance, ﬁgure 5 il-

lustrates that process.

RESOURCES

TIMING

COSTS

MANAGEMENT PROGRESS

CORRECTIVE

ACTIONS

Figure 5: Use case b: Project management process.

c) Evaluation of previous projects’ functionalities

reuse - Analysis of government requirements and

already developed projects to ﬁnd reusable com-

ponents. The organization we are analyzing pro-

duces a great amount of ICT products to autom-

atize district processes. A process is a set of in-

terrelated activities, grouped in phases. There-

fore each project is composed by a set of com-

ponents, each supporting a singular phase of the

entire process. Different district processes could

have certain phases in common, so that the orga-

nization could choose to reuse some components

taken from other projects during automation ac-

tivities, in order to reduce developmental costs.

PROJECTS

MATCHING

SUGGESTIONS

DISTRICT

PROCESSES

Figure 6: Use case c: Evaluation of previous projects’ func-

tionalities for reuse.

For instance, ﬁgure 6 shows the ES used to iden-

tify which project components could be reused to

automate district processes phases.

4.3.1 Examples of Rules

The code portion reported below shows a typical

ES behavior in the third use case. In this scenario

the expert system uses the declarative part of the

knowledge that expresses the active part of proce-

dural knowledge emulating the behavior of a human

expert.

(defrule search_department ?instance

<-(object (is-a DEPARTMENT)

(name ?n&:(call ?*ric* equals

(slot-get"+ Dep+"name)

(lowcase ?n))))=>(bind $?area

(slot-get (instance-name ?instance)

comprehend_areas

(foreach ?j $?area

(if (call ?*ric* different

(slot-get (instance-name ?j) name) empty)

then...

5 KROMOS DOCUMENT

MANAGEMENT SERVICE

The Document Management Service (DMS) provided

by Kromos is a module capable of pre-processing

documents, retrieving data, indexing texts and search

engine managing. In ICT companies the volume of

documents produced during working activities grows

rapidly, collecting them in traditional forms becomes

almost impractical and also searching them without

automatic search engines is a great waste of time.

Documents contain most of the information about

projects, functionalities, people involved and so on.

The Kromos platform uses Apache Lucene, an Infor-

mation Retrieval (IR) engine adapted for the insertion,

indexing and retrieval of documents in different for-

mats. Lucene is an open-source, high performance,

scalable, full-featured text search engine and informa-

tion retrieval library written in Java and suitable for

any application requiring a full text search (Gospod-

netic and Hatcher, 2005), through which any piece of

data convertible to a textual format can be indexed and

made searchable (Pirro and Talia, 2007). The main

functionalities of the Kromos Document Management

Service are: pre-processing of documents and their

content to obtain a text representation without any

lexical or sematic redundance; document indexing to

store information about ﬁles in an ordered structure to

use for the search phase; searching for documents us-

ing keywords, calculating the degree of satisfaction

of the requirements expressed in the query. These

requirements are fulﬁlled by three Kromos modules:

pre-processing, indexing and searching.

5.1 Pre-processing Module

Pre-processing is a necessary procedure in docu-

ment management, through which data and informa-

tion stored in documents in a speciﬁc format can be

elicited by analyzing and tokenizing content. Or-

ganizations generally create and use a great amount

of documents that can be stored in different kinds

of formats like text ﬁles (.txt), document ﬁles (.doc,

.pdf), web pages (.xml, .html) (Zhou and Xie, 2007).

The analysis of heterogeneous format contents, the

removal of meaningless terms and the maintenance

of information useful to retrieve and recover docu-

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322

ments will depend on the DMS. The proposed DMS

works in different steps in order to pre-process and

organize documents. When an organization’s mem-

bers insert documents to be collected by the KMS, a

two-step parsing then occurs: content elicitation and

content tokenization. Content elicitation to withdraw

textual content from different kinds of ﬁles eliminates

irrelevant information, such as typesetting format, and

transforms content into a character data stream. Con-

tent tokenization breaks the content into words and

sentences and transforms the data stream into a set of

terms for the subsequent content parsing procedure.

5.2 Indexing Module

Apache Lucene was adopted for indexing and docu-

ment storage, the search interface for querying index

and the reading interface to read texts and documents.

The fundamental concepts in Apache Lucene are in-

dex, document, ﬁeld and term (Bennett, 2004) (ﬁg.

7).

TEXT CONTENT

CONTENT ANALYZER

(PARSING CONTENT - INDEX CREATION)

INDEX

FILES

Figure 7: Index creation in document management system.

An index contains a sequence of documents,

which are a sequence of ﬁelds. Each ﬁeld gets tok-

enized and generates pairs of ﬁeld name and text to-

kens called terms. The index stores input in a data

structure called inverted index, making efﬁcient use

of disk space while allowing quick keyword lookups.

Kromos provides a user interface for document inser-

tion, giving users the opportunity to collect them in a

unique repository.

5.3 Searching Module

After the initial collection of documents and the cre-

ation of an index, users need to retrieve documents

from the remote ﬁle system, seeking them using a

search interface. The user interface is also a web-

based interface, so that user works as if the interface

were a common web search engine, typing keywords,

title, project name and so on. The system searches in

the indexed documents and retrieves the relevant doc-

uments, as ﬁgure 8 shows.

DOCUMENT SEARCH

REQUEST PARSER

(TERM FREQUENCY / INVERSE DOCUMENT FREQUENCY / ...)

INDEX

FILES

Figure 8: Document search in document management sys-

tem.

The result is a list of documents, each linked to the

related ﬁle; when opened, the system displays a read-

ing interface in a What You See Is What You Get view.

In Kromos documents are retrieved on the basis of

their content as if they were composed by atomic text

entities, a set of different concepts considered here

by calculating their frequency in the document, dis-

regarding the document’s overall structure.

6 CASE STUDY

As previously mentioned, Sicilia e-Innovazione is the

research and development company of Sicilian local

government in the ICT ﬁeld, and represents one of

the most interesting setting in order to acquire experi-

ences for the development of a Knowledge Manage-

ment System. This is due to several reasons such as

the novelty of the company mission, the heterogene-

ity of data sources, the difﬁculty of adopting tradi-

tional tools, and the involvement of different users.

Moreover, previously the start of the project, the prob-

lem of data and knowledge management had received

small attention. In that period, only few documents

on business processes and organization of government

ofﬁces were produced, while a huge amount of techni-

cal documents were produced and stored without any

management organization. All these reasons make

this company an ideal scenario where experimenting

a process of knowledge engineering, in order to pro-

mote the adoption of a knowledge management sys-

tem as tool for sharing the already acquired knowl-

edge, and for the production of the new one.

The Previous Situation. Sicilia e-Innovazione was

created in 2006 and since its establishment carried

out a lot of projects, mostly for the automatization of

all for government ofﬁce processes. Each project is

described and documented by several technical doc-

uments that represent a valuable source of precious

knowledge. Each document contains descriptions of

KROMOS: ONTOLOGY BASED INFORMATION MANAGEMENT FOR ICT SOCIETIES

323

the systems, in its current and future forms, ﬁnanc-

ing sources, responsibility information, technical and

developing choices, and the processes to be auto-

mated. All this knowledge is precious and could be

used in several different ways, for instance, to esti-

mate costs and necessary resources for new projects,

to ﬁnd similarities in different contexts, to increase

the code reusability. When the project started, the

company was organized as a collection of atomic

groups, each working independently by the others;

different teams replied the same development activ-

ities, so reuse was minimal, there was no effort to

organize and share experiences and knowledge ac-

quired by previous projects, and any technical tool

(such as search engines) to search and compare dif-

ferent projects. This situation produced knowledge is-

lands not shared among product groups and program

teams, with generational gaps between seasoned and

newly hired employees, limited ability to learn from

existing knowledge and no uniﬁed vision.

The Application of Kromos. The experience car-

ried out during the process of development in the bo-

som of Sicilia e-Innovazione gave us the chance to

deﬁne an ontological representation of the speciﬁc

domain, and to test our general-purpose Knowledge

Management prototypal system in a real applicative

environment.

Our working activity in the ﬁrm consisted of two dif-

ferent phases: the ﬁrst one, after the acquisition of

speciﬁc knowledge through the observation of busi-

ness activities and processes, allowed us to build an

ontological model for the domain representation; the

latter was centered on the ﬁtting of Kromos reasoner

and document management services to the company’s

needs. In the meanwhile some new requirements

emerged and that permitted us to reﬁne our system

with new features in order to improve Knowledge

accessibility to different skilled users. This expe-

rience provided all the information to comprehend

the importance of a correct and efﬁcient knowledge

resources, people and organization management; to

estimate the efﬁcacy of adopted technical solutions,

their advantages and disadvantages; and to evaluate

needs satisfaction degree using these solutions. The

document management and information acquisition

mechanisms, such as those developed for this proto-

type, proved to be necessary in a dynamic environ-

ment like the one we observed.

Beneﬁts using the KMS Kromos. The adoption

of Kromos for the data management evidenced the

advantages of a correct knowledge management in

every organization, emphasizing the importance of

sharing and reusing information with different skilled

workers. The use of a modiﬁable ontology below

the expert system gave ﬂexibility to the platform, so

that its use is also an activity which continually re-

ﬁnes the knowledge base. During use of the system,

more information was collected and ontology struc-

ture changed and grew, but the functionalities of the

expert system did not require any modiﬁcation. The

web based interface, hiding the complexity of the sys-

tem’s functionalities, gave the platform a characteris-

tic of usability, so that the collection of data and doc-

uments and the sharing of information seemed to be

incremented.

7 CONCLUSIONS

The key thrust of this article has been to analyze the

beneﬁts of knowledge-based systems for knowledge

management and the deﬁnition of expert system rules

which can adapt their results to changes in ontol-

ogy. Reuse and information sharing are essentially

Knowledge Management problems. From this point

of view Kromos provides: an improvement of knowl-

edge sharing between employees because it acceler-

ates the transfer of knowledge; an improvement on the

knowledge retrieval through document management

system; an improvement in knowledge reuse through

an expert system able to provide a support in the adap-

tation of old solution to new problems. The use of

such a system in a real case, an ICT Sicilian Govern-

ment company, gave the opportunity to measure the

increase in information sharing and reuse, seconding

the advice obtained by the elaboration of the expert

system.

ACKNOWLEDGEMENTS

The authors would like to acknowledge the contribu-

tion of Marco Sicilia and Mirella Marrone to the sup-

port for Kromos graphics.

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