KR
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
Copyright
c
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
´
eg
´
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-
ICSOFT 2009 - 4th International Conference on Software and Data Technologies
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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