An Ontology for eGovernment:
Linking the Scientific Model with Concrete Projects
Gertraud Orthofer*, Maria A. Wimmer°
* University of Linz, Institute of Informatics in Business and Government, Austria
° University of Koblenz, Institute for IS Research, Research Group eGovernment, Germany
* orthofer@iwv.jku.at, ° wimmer@uni-koblenz.de
Abstract
The field eGovernment has become an important topic of
research and development. In order to support the activities
going on in research and practice, an eGovernment portal
providing on the one hand an eGovernment ontology and on
the other hand an overview of practical projects in a certain
field would be helpful. Such a portal could be a central
entry point for the various stakeholders to a) learn about the
field eGovernment and its characteristics from a scientific
perspective, b) provide an instrument to further structure the
field, c) thematically cluster projects, and at the same time
d) provide a practical instrument for the users to overview
the projects in the field. Within the project eip.at, such a
portal has been created by using semantic technologies.
the applicability of semantic modeling technologies in the
field of eGovernment.
In the early phase of the project, four key user groups have
been identified. Furthermore, a number of benefits were
defined for each of these groups, some being valid for
several user groups. Figure 1 provides an overview of the
four user groups and their expected benefits to use the
portal. Further details can be found in (Knoblechner et al,
2005) and (Wimmer, 2006).
Introduction
In the last years, eGovernment has developed to a
renowned field of research. Likewise, a tremendous
number of projects both in research and in practice have
been initiated. Unfortunately, no structured approach was
used to develop a common understanding of expressions
used to form the field. Consequently, different disciplines
have created their own definitions. In the application area,
many projects address the same issues redundantly and it is
difficult to get an overview of projects in the field.
These problems led to the project eip.at (eGovernment
intelligent portal), which was initiated and carried out at
the Institute of Informatics in Business and Government
(IWV) at University of Linz (http://www.eip.at – German
only). The aims of the project were on the one hand to
structure the field eGovernment and to link the terms and
projects among each other by using semantic technologies.
The result should be an eGovernment ontology and an
eGovernment knowledge map. On the other hand, a
prototype for a knowledge portal should be implemented to
provide this information in a structured and semantically
enriched way. Apart from the rather practical objectives
listed before, a key research question was to learn about
Copyright © 2002, American Association for Artificial Intelligence
(www.aaai.org). All rights reserved.
Figure 1: Stakeholder groups and their identified benefits
to use the eip.at portal
In the subsequent part of this contribution, we first
describe the semantic modeling and ontology concept.
Then, the eGov ontology and the eGov knowledge map are
briefly explained conceptually and practically. The paper
concludes with a discussion of the lessons learnt in the
portal development and an outlook of further work to do.
Semantic Modeling and Ontology Concept
used
The starting point for developing the eGov ontology for
eip.at was to structure the information and aspects shaping
the eGovernment domain. Semantic modeling was used to
develop the knowledge map.
Due to space limitations, theories of semantic modeling are
not discussed here. Instead, the reader is referred to
focussed literature such as (Geroimenko and Chen, 2003),
(Hjelm, 2001), and (Staab and Studer, 2004). The
following aspects summarize some advantages of
ontologies in respect to other structuring concepts:
• unique, unambiguous definitions of expressions;
• avoidance of semantic conflicts of e.g. naming, value
ranges, abstraction levels, type of visualization;
• using a comprehensive set of elements;
• concepts classes and instances to structure the domain;
• clear description of relations (hierarchies / other);
• description of knowledge objects via attributes,
functions (i.e. specific relations), axioms;
• machine-computable;
• set of rules and axioms for automatic deduction;
• concept of inheritance.
In the project eip.at, the modeling tool k-infinity was used.
Background for modeling with k-infinity was a
cooperation with an Austrian contractual partner of iviews, who was interested in evaluating k-infinity for the
use in the modeling of a rather complex and larger
knowledge map.
The ontology approach used in eip.at bases on two main
concepts: classes of objects (e.g. a “person”) and concrete
instances of classes (e.g. “Lara Croft” is an instance of
“person”). Furthermore, extending concepts are provided
in k-infinity, some of which are:
• Roles: Roles are used to extend instances, which are not
directly extendable with “individuums”. E.g. the class
“author” is a possible extension (role) of a “person”.
• Attribution objects: Such objects are geographical
information, time etc., which could also be mapped via
attributes themselves. Yet then, an inter-linkage among
objects would not be possible, because an attribute
belongs to a specific object. For example, with the usage
of attribution objects, all events taking place in a year or
projects of a certain city or region can be searched for
quite easily.
• Content explanations: Content explanations reflect
objects such as descriptions, definitions, project foci and
relations. The first two serve to explain expressions
used. Project foci has been added to enable the
recognition of projects targeted towards the same key
aspects. The object relations are used to demonstrate and
model linkage between different knowledge objects.
In the course of the project eip.at, the modeling tool
k-infinity was assessed in comparison with other tools for
semantic modeling (SemTalk, OntoEdit, OpenCYC, OilEd
and Protégé). The evaluation results are available in a
diploma work (cf. Knoblechner and Seliger, 2005) and are
briefly summarized in (Knoblechner et al, 2005) and in
(Wimmer, 2006). Further comparison results of semantic
modeling tools are in (Gómez-Pérez, 2002).
eip.at’s eGov Ontology and Knowledge Map
The point of departure for the eGov ontology was the
development of a scientifically structured field as detailed
in figure 2. The structure was taken from the holistic view
on eGovernment developed by (Wimmer and Traunmüller,
2002). As figure 2 shows, the root node of the egov
knowledge map was called “eGovernment intelligent
portal”. Underneath, three sub-classes were created:
practical view, scientific perspective and modeling
artifacts.
Figure 2: Upper part of the eGov knowledge map and
eGov ontology (partial view, not all nodes are shown)
Figure 3: Practical view: main concepts (classes)
The eGov ontology is reflected in the scientific
perspective, which was divided into four key areas as
shown in figure 2. The cross-perspective issues describe
aspects that cannot clearly be assigned to one of the core
scientific perspectives shown in figure 2 (e.g. standards
and interoperability may be part of technical, data/info/
knowledge, process, and organization issues alike). The
eGovernment part covers e.g. the definitions (currently
over 60 identified and inserted). The Topics related to
eGovernment provide an auxiliary part to link e.g. future
ontologies of eDemocracy, eHealth etc.
The node called practical view (cf. figure 2) covers the
aspects related to projects and specific instances in
eGovernment. Examples are actors, information source,
ICT infrastructure, projects, specific standards, events,
public services and life events as shown in figure 3.
Another auxiliary node as shown in figure 2 is modeling
artifacts. It covers terms that can neither clearly be
assigned to the practical nor to scientific perspective.
The status of the current eGov knowledge map and eGov
ontology are:
• The eGov ontology is developed in German to cover a
large part of the core eAdministration domain.
• The eGov knowledge map is not yet modeled largely,
since the data should partially be generated in an
automatic way from an external eGovernment projects
database. The interface specifications have been proven,
yet access to the eGovernment projects database is not
yet possible.
Portal Development, Lessons Learnt and
Outlook
After the eGov knowledge map had reached a reasonable
size, a web portal was implemented to provide the eGov
knowledge map to the users via a simple web interface.
For the export of the knowledge map from k-infinity to the
oracle 9i database of the web portal, RDF (Resource
Description Framework) and the Jena Framework were
used.
In the following, a few of many lessons learnt from the
project eip.at are summarized, and future work on these
topics is described.
First of all, developing the eGov ontology and knowledge
map was a highly know-how intense and time-consuming
work. Many discussions and reflections were needed to
develop the currently existing knowledge map. Apart from
that, the existing ontology and knowledge map reflect the
understanding of the team developing it. The model needs
to be proven by experts in the field. Apart from that, the
domain is still evolving and, hence, requires a rather
dynamic and flexible (i.e. evolving) ontology. Next steps
in this respect are on one hand to develop an English
version of the eGov ontology in order to open the
discussion within the eGov community. On the other hand,
the knowledge map needs to be further developed to
include the eGov projects and other sub-domains such as
eDemocracy.
As regards the modeling tool, several weaknesses and
constraints have been found while modeling in k-infinity.
Consequently, we are currently discussing the migration to
another modeling tool. Here, further investigations are
required to select a proper tool that fits the requirements
best. In this respect, suitable semantic modeling languages
shall be examined as well.
As regards the web portal, the search process is not yet
satisfactorily implemented. It suffers from performance
problems. Adequate search algorithms are needed to
handle vast amounts of data in large knowledge maps.
Apart from that, further work shall evaluate different
combinations of database systems and frameworks.
Finally, a portal is more attractive for everyone if more
communication features are integrated (chat, fores, etc.) to
interactively discuss and develop the knowledge map,
different understandings and so on.
Acknowledgement: The project eip.at was carried out with
the help of M. Knoblechner, M. Krieger, M. Leitner, H.
Luger, and T. Seliger. The authors express their special
thanks for the valuable work of this excellent team.
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